JP4266002B2 - Image processing apparatus, image forming apparatus, image processing method, image processing program, and recording medium - Google Patents

Description

  The present invention relates to a technique for performing color conversion processing on input image data, and in particular, an image processing apparatus, an image forming apparatus, and the like that perform black generation processing and undercolor removal processing on an image signal subjected to color correction processing. The present invention relates to an image processing method, an image processing program, and a recording medium.

  In recent years, the digitalization of office automation equipment in offices has progressed rapidly, and the demand for color image output has increased. In response to this increase in demand, output devices such as electrophotographic digital color copying machines and ink jet and thermal transfer color printers have become widespread.

  If these output devices are used, for example, image data input from an input device such as a digital camera or a scanner, or an image represented by image data created on a computer can be output. In such an input / output device, generally, an image output to which stable color reproduction is always applied based on input image data is required. Therefore, color conversion processing of input image data based on digital image processing technology plays an important role in such an input / output device.

  Here, the color conversion process means a conversion process of a signal in the color space of the input image data, which is executed based on the input document and the characteristics of the input device. For example, a color space signal such as R (red) G (green) B (blue) or the like is converted into a color space signal of output image data suitable for an output device such as a printer, such as C (cyan) M (magenta) Y ( The process of converting to (yellow) is actually performed.

  At this time, the output device outputs an image represented by the input image data using a color material (toner or ink) corresponding to the color space signal subjected to color conversion. Many output devices use a color material of K (black) in addition to CMY as a color material. By using the K color material, it is possible to reproduce a dark color that cannot be reproduced with only the CMY color material. Furthermore, by using the K color material, it is possible to reduce the amount of CMY color material used or improve the gray reproducibility (see, for example, Non-Patent Document 1 and Non-Patent Document 2).

  However, the optimum black generation amount (K generation amount) at the time of color conversion is different between reproducing dark and vivid colors and reproducing gray such as black characters. Therefore, there is a problem that it is difficult to determine an appropriate black generation amount. As a technique for solving this problem, for example, a technique described in Patent Document 1 has been proposed.

In the technique described in Patent Document 1, a two-dimensional black color is corrected based on a difference (MAX−MIN) between a maximum value MAX signal and a minimum value MIN signal among color-corrected CMY signals and a MIN signal. By controlling the amount of black generation using a generation / undercolor removal LUT (Look Up Table), both gray reproducibility and dark vivid color reproducibility can be achieved.
JP 2003-60929 A (publication date February 28, 2003) Journal of Japan Printing Society, Vol. 31, No. 4 (1994), p. 290-297 The Journal of Electrophotographic Society, Vol. 36, No. 4 (1997), p. 343-352

  However, since the black character region is an achromatic region, it is not necessary to consider the saturation component. That is, one-dimensional black generation is suitable for the black character region instead of two-dimensional black generation. Therefore, in the conventional apparatus described in Patent Document 1, it is necessary to prepare a one-dimensional black generation circuit separately from the two-dimensional black generation circuit for such a region. Therefore, the conventional apparatus has a problem that the scale of the hardware configuration increases, the amount of memory used increases, and the cost increases.

  The present invention has been made in view of the above problems, and an object thereof is to selectively perform one-dimensional and two-dimensional black characteristic amount calculation processing using the same hardware configuration. An object is to provide an image processing apparatus, an image forming apparatus, an image processing method, an image processing program, and a recording medium.

  In order to solve the above problems, an image processing apparatus according to the present invention performs an image for performing black generation processing or undercolor removal processing by using a black characteristic amount for image data representing an image composed of a plurality of color components. In the processing device, parameter generation means for generating a first parameter reflecting the achromatic characteristic of the image and a second parameter reflecting the chromatic characteristic of the image from pixel values included in the image data Selecting the first or second parameter based on a predetermined criterion and outputting the selected parameter as a selection parameter; and the first and second parameters based on the first parameter and the selected parameter. Black characteristic amount determining means for obtaining a black characteristic amount to be applied to the image data from binary function data defining a relationship between the two parameters and the black characteristic amount. It is characterized in that.

  This apparatus is an apparatus that performs black generation processing or undercolor removal processing on image data representing an image composed of a plurality of color components. By performing these processes, the apparatus newly generates a black component amount not included in the input image data, or removes the lower color amount from each color component amount included in the input image data. At this time, the apparatus performs black generation processing or undercolor removal processing by using the black characteristic amount. Here, the “black characteristic amount” is a general term for the black generation amount used when the black generation processing is performed and the under color removal amount used when the under color removal processing is performed.

  Here, according to the above configuration, the parameter generation unit generates the first and second parameters from the pixel values included in the image data. For example, when the pixel included in the image represented by the image data is composed of three types of color components C (cyan), M (magenta), and Y (yellow), the parameter generation unit may determine the amount of these color components included in the image data. Based on, the first and second parameters are generated.

  As described above, the image represented by the image data processed by this apparatus is composed of a plurality of color components. The lightness, hue, and saturation of the image represented by the image data change according to the density ratio of these color components. Therefore, the parameter generation unit generates these parameters as variables reflecting the achromatic color characteristic and the chromatic color characteristic of the image data, respectively. That is, the parameter generation unit generates the first and second parameters according to the color characteristics of the image represented by the image data.

  The “binary function data” is data in which the relationship between the first parameter and the second parameter generated by the parameter generation unit and the black characteristic amount is determined in advance. That is, the function data is data representing a function for specifying and outputting the black characteristic amount corresponding to the input first parameter and second parameter by a predetermined method. This function data can be, for example, a black characteristic amount table in which one black characteristic amount is stored in association with a one-to-one relationship with respect to a set of first parameter and second parameter. The function data can also be mathematical data that returns a black characteristic amount by performing a predetermined calculation based on the input first parameter and second parameter.

  Here, the parameter selection means selects the first or second parameter based on a predetermined criterion and outputs it as a selection parameter. Therefore, when the parameter selection unit selects the first parameter as the selection parameter, the calculated black characteristic amount is calculated from only the first parameter. Therefore, in this case, the black characteristic amount determining means performs a two-dimensional black characteristic amount calculation process that obtains a result equivalent to the one-dimensional black characteristic amount calculation process, assuming that the two input data represent achromatic region characteristics. As the black characteristic amount to be applied to the image data, a black characteristic amount suitable for the achromatic region is calculated.

  On the other hand, when the parameter selection unit selects the second parameter as the selection parameter, the black characteristic amount determination unit performs a two-dimensional black characteristic amount calculation process on the assumption that the two input data represent the achromatic color characteristic and the chromatic color characteristic. Then, the black characteristic amount for the image data is calculated.

  Accordingly, the present apparatus uses only the configuration for performing the two-dimensional black characteristic amount calculation processing, that is, the configuration for performing the two-dimensional black characteristic amount calculation processing and the configuration for performing the one-dimensional black characteristic amount calculation processing are separated. In this case, only the configuration for performing the two-dimensional black characteristic amount calculation processing is performed, and by switching the selection parameter, the determination of the black characteristic amount in consideration of the saturation component (chromatic color characteristic) and the achromatic region are performed. It is possible to determine a suitable black characteristic amount, and there is an effect of reducing memory resources and simplifying the device configuration.

  In order to solve the above-described problems, an image processing method according to the present invention performs image generation processing or undercolor removal processing using black characteristic amounts on image data representing an image composed of a plurality of color components. An image processing method for generating the black characteristic amount in the apparatus, wherein a first parameter reflecting an achromatic characteristic of the image and a chromatic characteristic of the image are reflected from a pixel value included in the image data. A parameter generation step for generating the second parameter, a parameter selection step for selecting the first or second parameter and outputting it as a selection parameter, and the obtained first and second black characteristic amounts From the binary function data defining the relationship between the first and second parameters and the black characteristic amount based on the first parameter and the selection parameter, It is characterized by containing a black characteristic quantity determination step of determining a black characteristic amount to be applied to the data.

  Thus, since this method is a structure provided with each step corresponding to each means with which this apparatus is equipped, there exists an effect | action and effect similar to this apparatus.

  In order to solve the above problems, an image processing apparatus according to the present invention performs an image for performing black generation processing or undercolor removal processing by using a black characteristic amount for image data representing an image composed of a plurality of color components. In the processing device, parameter generation means for generating a first parameter reflecting the achromatic characteristic of the image and a second parameter reflecting the chromatic characteristic of the image from pixel values included in the image data Based on the first parameter, the first black characteristic amount suitable for the achromatic color region is obtained from the first function data in which the relationship between the first parameter and the black characteristic amount suitable for the achromatic color region is determined in advance. Second function data in which the relationship between the first black characteristic amount acquisition means for acquiring the black characteristic amount in consideration of the first parameter and the saturation component is determined, or the first function data From Second black characteristic amount acquisition means for selecting function data based on a predetermined criterion and acquiring a second black characteristic amount based on the first parameter from the selected function data; and the acquired first and A black characteristic amount determining unit for obtaining a black characteristic amount to be applied to the image data by performing an interpolation operation based on the first parameter and the second parameter from the second black characteristic amount; It is characterized by that.

  This apparatus is an apparatus that performs black generation processing or undercolor removal processing on image data representing an image composed of a plurality of color components. By performing these processes, the apparatus newly generates a black component amount not included in the input image data, or removes the lower color amount from each color component amount included in the input image data. At this time, the apparatus performs black generation processing or undercolor removal processing by using the black characteristic amount. Here, the “black characteristic amount” is a general term for the black generation amount used when the black generation processing is performed and the under color removal amount used when the under color removal processing is performed.

  Here, according to the above configuration, the parameter generation unit generates the first and second parameters from the pixel values included in the image data. For example, when the pixel included in the image represented by the image data is composed of three types of color components C (cyan), M (magenta), and Y (yellow), the parameter generation unit may determine the amount of these color components included in the image data. Based on, the first and second parameters are generated.

  As described above, the image represented by the image data processed by this apparatus is composed of a plurality of color components. The lightness, hue, and saturation of the image represented by the image data change according to the density ratio of these color components. Therefore, the parameter generation unit generates these parameters as variables reflecting the achromatic color characteristic and the chromatic color characteristic of the image data, respectively. That is, the parameter generation unit generates the first and second parameters according to the color characteristics of the image represented by the image data.

  Here, according to the above configuration, the first black characteristic amount acquisition unit obtains the first function data from the first function data in which the relationship between the first parameter and the black characteristic amount suitable for the achromatic color region is determined in advance. On the basis of the first parameter, one first black characteristic amount suitable for the achromatic region is acquired from the first function data. In addition, the second black characteristic amount acquisition unit may obtain the relationship between the first parameter and the black characteristic amount in consideration of the saturation component from the second function data that is determined in advance, or the first function data. Function data is selected based on a predetermined criterion, and a second black characteristic amount is acquired from the selected function data based on the first parameter. The “function data” is data in which the relationship between the first parameter generated by the parameter generation unit and the black characteristic amount is determined in advance. That is, the function data is data representing a function for specifying and outputting a black characteristic amount corresponding to the input first parameter by a predetermined method. The function data can be, for example, a black characteristic amount table in which the first parameter and the black characteristic amount are stored in association with a one-to-one relationship. The function data can also be mathematical formula data that returns a black characteristic amount by performing a predetermined calculation based on the input first parameter.

  As described above, the second black characteristic amount acquisition unit acquires the second black characteristic amount from the first function data or the second function data based on the first parameter. Therefore, when the second black characteristic amount is acquired from the first function data, the second black characteristic amount acquired by the second black characteristic amount acquisition unit is the second black characteristic amount acquired by the first black characteristic amount acquisition unit. 1 equal to the black characteristic amount. In this case, the black characteristic amount determining means performs an interpolation operation based on the first parameter and the second parameter from two equal first black characteristic amounts. As a result, the black characteristic amount calculated by the interpolation calculation becomes the first black characteristic amount itself. This coincides with the black characteristic amount acquired from the first function data based on the first parameter. Therefore, in this case, the black characteristic amount determination means performs a two-dimensional black characteristic amount calculation process that obtains a result equivalent to the one-dimensional black characteristic amount calculation process, and uses the achromatic region as the black characteristic amount applied to the image data. Therefore, a black characteristic amount suitable for the above is calculated.

  On the other hand, when the second black characteristic amount acquisition unit acquires the second black characteristic amount from the second function data, the black characteristic amount determination unit differs from the first and second black characteristic amounts in two different ways. An interpolation calculation based on the first parameter and the second parameter is performed. The plurality of black characteristic amounts acquired at this time include a black characteristic amount suitable for the achromatic color region and a black characteristic amount that takes into account the saturation component. Then, the black characteristic amount determining means obtains a black characteristic amount suitable for the image data using these black characteristic amounts.

  Accordingly, the present apparatus shares the first and second function data, thereby determining the black characteristic amount suitable for the achromatic region and the black characteristic amount considering the saturation component, that is, one-dimensional. In addition, there is an effect that both the two-dimensional black characteristic amount calculation processing can be performed. Furthermore, in the present apparatus, since the black characteristic amount taking the saturation component into consideration can be determined using function data in which the relationship between the first parameter and the black characteristic amount is determined in advance, the first and second parameters and the black characteristic amount are determined. There is no need to prepare more complicated function data in which the relationship with the characteristic amount is predetermined. For example, when the function data is composed of a black characteristic amount table, it is only necessary to prepare a one-dimensional black characteristic amount table, and there is no need to separately prepare a two-dimensional black characteristic amount table. In this case, the effects of reducing the memory resources and simplifying the device configuration for performing the black characteristic amount calculation processing are particularly great.

  In order to solve the above-described problems, an image processing method according to the present invention performs image generation processing or undercolor removal processing using black characteristic amounts on image data representing an image composed of a plurality of color components. An image processing method for generating the black characteristic amount in the apparatus, wherein a first parameter reflecting an achromatic characteristic of the image and a chromatic characteristic of the image are reflected from a pixel value included in the image data. Based on the first parameter, the parameter generation step for generating the second parameter and the first function data in which the relationship between the first parameter and the black characteristic amount suitable for the achromatic region is determined in advance. The relationship between the first black characteristic amount acquisition step for acquiring the first black characteristic amount suitable for the achromatic color region and the black characteristic amount in consideration of the first parameter and the saturation component is predetermined. Second function Or a second black characteristic amount acquisition step for acquiring a second black characteristic amount from the first function data based on the first parameter, and the acquired first and second black characteristic amounts. And a black characteristic amount determining step for obtaining a black characteristic amount to be applied to the image data by performing an interpolation calculation based on the first parameter and the second parameter.

  Thus, since this method is a structure provided with each step corresponding to each means with which this apparatus is equipped, there exists an effect | action and effect similar to this apparatus.

  In the image processing apparatus according to the present invention, the binary function data further includes first function data in which a relationship between the first parameter and a black characteristic amount suitable for an achromatic region is determined in advance, A second function data that predetermines the relationship between the first parameter and the black characteristic amount taking the saturation component into account, and from the first function data based on the first parameter, A first black characteristic amount suitable for an achromatic color region is acquired, and a second black characteristic amount that takes a saturation component into consideration based on the first parameter is acquired from the second function data. The black characteristic amount acquisition unit further includes a black characteristic amount determination unit, wherein the black characteristic amount determination unit selects the first parameter and the selection parameter selected by the parameter selection unit from the acquired first and second black characteristic amounts. Interpolation calculation based on It is preferable to determine the black characteristic amount applied to the image data by.

  According to the above configuration, the black characteristic amount obtaining unit obtains the relationship between the first parameter and the black characteristic amount suitable for the achromatic region from the first function data that is determined in advance based on the first parameter. One first black characteristic amount suitable for the achromatic region is acquired from the first function data. Further, the black characteristic amount acquisition means obtains the saturation component based on the first parameter from the second function data in which the relationship between the first parameter and the black characteristic amount taking the saturation component into consideration is predetermined. Obtain a second black characteristic quantity taking into account.

  Here, when the parameter selection unit selects the first parameter as the selection parameter, the black characteristic amount determination unit performs an interpolation operation based on the two first parameters from the first and second black characteristic amounts. It will be. At this time, since the parameter based on the interpolation calculation is the same first parameter, the calculated black characteristic amount matches the first black characteristic amount acquired based on the first parameter. Therefore, in this case, the black characteristic amount determination means performs a one-dimensional black characteristic amount calculation process, and calculates a black characteristic amount suitable for the achromatic region as the black characteristic amount applied to the image data.

  On the other hand, when the parameter selection unit selects the second parameter as the selection parameter, the black characteristic amount determination unit performs interpolation based on two different first and second parameters from the first and second black characteristic amounts. An operation is performed. At this time, the two first and second black characteristic amounts are black characteristic amounts suitable for an achromatic region and a black characteristic amount considering a saturation component. Then, the black characteristic amount determining means obtains a black characteristic amount to be applied to the image data from these black characteristic amounts by performing an interpolation operation based on the first and second parameters. That is, the black characteristic amount determining means performs a two-dimensional black characteristic amount calculation process, and calculates a black characteristic amount taking the saturation component into consideration as the black characteristic amount to be applied to the image data.

  Accordingly, the present apparatus uses only the configuration for performing the two-dimensional black characteristic amount calculation processing, that is, the configuration for performing the two-dimensional black characteristic amount calculation processing and the configuration for performing the one-dimensional black characteristic amount calculation processing are separated. In this case, only the configuration for performing the two-dimensional black characteristic amount calculation processing is performed, and by switching the selection parameter, the determination of the black characteristic amount in consideration of the saturation component (chromatic color characteristic) and the achromatic region are performed. It is possible to determine a suitable black characteristic amount, and there is an effect of reducing memory resources and simplifying the device configuration.

  In the image processing apparatus according to the present invention, the binary function data is a two-dimensional look-up table that associates black characteristic amounts with first and second parameters, and the black characteristic amount determining means includes the first characteristic data. It is preferable to obtain a black characteristic amount to be applied to the image data from the two-dimensional lookup table based on the parameter and the selection parameter selected by the parameter selection means.

  In the above configuration, when the parameter selection unit selects the first parameter as the selection parameter, the black characteristic amount determination unit applies the image data from the two-dimensional lookup table based on the two first parameters. Obtain the black characteristic amount. Therefore, in this case, the black characteristic amount determination means performs processing equivalent to the one-dimensional black characteristic amount calculation processing, and calculates a black characteristic amount suitable for the achromatic region as the black characteristic amount applied to the image data. become.

  On the other hand, when the parameter selection unit selects the second parameter as the selection parameter, the black characteristic amount determination unit determines the black characteristic to be applied to the image data from the two-dimensional lookup table based on the first and second parameters. Find the amount. Therefore, in this case, the black characteristic amount determination means performs a two-dimensional black characteristic amount calculation process, and calculates a black characteristic amount taking the saturation component into account as the black characteristic amount applied to the image data. .

  Accordingly, the present apparatus uses only the configuration for performing the two-dimensional black characteristic amount calculation processing, that is, the configuration for performing the two-dimensional black characteristic amount calculation processing and the configuration for performing the one-dimensional black characteristic amount calculation processing are separated. In this case, only the configuration for performing the two-dimensional black characteristic amount calculation processing is performed, and by switching the selection parameter, the determination of the black characteristic amount in consideration of the saturation component (chromatic color characteristic) and the achromatic region are performed. It is possible to determine a suitable black characteristic amount, and there is an effect of reducing memory resources and simplifying the device configuration.

  Further, in the image processing apparatus according to the present invention, the parameter selection unit uses the characteristic of the image as the predetermined reference, and based on the characteristic signal representing the characteristic, the first parameter or the first parameter. It is preferable to select one of the two parameters.

  The “image characteristics” here include, for example, characteristics that can be determined by performing a predetermined determination process based on image data, or characteristics that the user designates through the operation panel. In the former example, there are areas (character areas, photo areas, etc.) to which pixels and pixel groups in the image belong. In the latter example, there are document modes (text document mode, photo mode, etc.). In any case, depending on the characteristics of the image, it is preferable to use the black characteristic amount applied to the image data in consideration of the saturation component, and the black characteristic amount suitable for the achromatic region. It is preferable to do this.

  Here, in the above configuration, the parameter selection unit selects the first or second parameter based on the characteristic signal representing the characteristic of the image. As described above, when the parameter selection unit selects the first parameter, the black characteristic amount determination unit performs the two-dimensional black characteristic amount calculation process, which is the same as the one-dimensional black characteristic amount calculation process. While determining the black characteristic amount suitable for the chromatic area, when the parameter selection unit selects the second parameter, the two-dimensional black characteristic amount calculation processing is performed to determine the black characteristic amount taking the saturation component into consideration. To do.

  That is, according to the characteristics of the image, the apparatus determines whether the black characteristic amount to be applied to the image data is a two-dimensional black characteristic amount considering the saturation component or a black characteristic amount corresponding to the achromatic region. Decide on. Therefore, this apparatus has an effect of determining an optimum black characteristic amount according to the characteristics of the image.

  Further, in the image processing apparatus according to the present invention, the second black characteristic amount acquisition unit uses the characteristic of the image as the predetermined reference, and the first black characteristic amount based on the characteristic signal representing the characteristic. Alternatively, it is preferable to obtain the second black characteristic amount from the second function data.

  The “image characteristics” here include, for example, characteristics that can be determined by performing a predetermined determination process based on image data, or characteristics that the user designates through the operation panel. In the former example, there are areas (character areas, photo areas, etc.) to which pixels and pixel groups in the image belong. In the latter example, there are document modes (text document mode, photo mode, etc.). In any case, depending on the characteristics of the image, it is preferable that the black characteristic amount applied to the image data is a black characteristic amount suitable for the achromatic region, and the black characteristic amount considering the saturation component. It is preferable to do this.

  Here, in the above configuration, the second black characteristic amount acquisition unit acquires the second black characteristic amount from either the first or second function data based on the characteristic signal representing the characteristic of the image. . As described above, the black characteristic amount determination unit obtains a result equivalent to the one-dimensional black generation process when the second black characteristic amount acquisition unit acquires the second black characteristic amount from the first function data. The two-dimensional black characteristic amount calculation processing is performed to determine a black characteristic amount suitable for the achromatic region, and the second black characteristic amount acquisition unit acquires the second black characteristic amount from the second function data. In this case, a two-dimensional black characteristic amount calculation process is performed to determine a black characteristic amount that takes the saturation component into consideration.

  That is, the apparatus determines, based on the characteristics of the image, the black characteristic amount to be applied to the image data as either a black characteristic amount corresponding to the achromatic region or a black characteristic amount considering the saturation component. become. Therefore, this apparatus has an effect of determining an optimum black characteristic amount according to the characteristics of the image.

  Further, in the image processing apparatus according to the present invention, the binary function data is composed of a plurality of different function data corresponding to the characteristics of the image, and the plurality of function data is converted into a characteristic signal representing the characteristics. A function data storage unit that stores the data in association with each other is further provided, and the black characteristic amount acquisition unit is configured to generate the second characteristic data from the two function data corresponding to the characteristic signal in the function data storage unit based on the characteristic signal. It is preferable to obtain the first and second black characteristic quantities.

  In the above configuration, the binary function data includes a plurality of different function data corresponding to the characteristics of the image. The function data storage unit stores the plurality of function data in association with the characteristic signal representing the characteristic.

  Here, the black characteristic amount acquisition means designates function data corresponding to the characteristic signal from the binary function data in the function data storage unit. Then, the black characteristic amount determination unit acquires the black characteristic amount from the function data designated by the black characteristic amount acquisition unit. That is, the black characteristic amount acquired by the black characteristic amount determining means is a black characteristic amount corresponding to the image characteristic.

  Therefore, since the present apparatus determines the black characteristic amount to be applied to the image data based on the black characteristic amount corresponding to the image characteristic, the image quality of the image represented by the image data after the black generation process or the under color removal process is determined. The effect is optimized.

  In the image processing apparatus according to the present invention, the first and second function data are each composed of a plurality of different function data according to the characteristics of the image, and the plurality of function data is A function data storage unit that stores the data in association with a characteristic signal that represents a characteristic; and the first black characteristic amount acquisition unit corresponds to the characteristic signal in the first function data based on the characteristic signal. The first black characteristic amount is obtained from the function data, and the second black characteristic amount acquisition means is configured to obtain, based on the characteristic signal, function data corresponding to the characteristic signal in the second function data; Alternatively, it is preferable that the second black characteristic amount is acquired from function data corresponding to the characteristic signal in the first function data.

  In the above configuration, each of the first and second function data includes a plurality of different function data corresponding to the characteristics of the image. The function data storage unit stores the plurality of function data in association with the characteristic signal representing the characteristic.

  Here, the first black characteristic amount acquisition unit and the second black characteristic amount acquisition unit respectively acquire the black characteristic amount from the function data corresponding to the characteristic signal in the function data storage unit. That is, these black characteristic amounts are black characteristic amounts corresponding to the image characteristics.

  Therefore, since the present apparatus determines the black characteristic amount to be applied to the image data based on the black characteristic amount corresponding to the image characteristic, the image quality of the image represented by the image data after the black generation process or the under color removal process is determined. The effect is optimized.

  In the image processing apparatus according to the present invention, the characteristic signal further includes at least one of a character area, a color blur area, a halftone area, or a photographic area to which each pixel or pixel group included in the image belongs. An area identification signal indicating a type of an area to be included, and the parameter selection unit selects the first parameter and determines the selection when determining that the area identification signal is a signal indicating a character area or a color blur area. On the other hand, when it is determined that the area identification signal is a signal representing a halftone dot area or a photographic area, it is preferable to select the second parameter as the selection parameter.

  In the above configuration, when it is determined that the region identification signal is a signal representing a character region or a color blur region, the parameter selection unit selects the first parameter as a selection parameter. As described above, when the parameter selection unit selects the first parameter, the black characteristic amount determination unit performs a process equivalent to the one-dimensional black characteristic amount calculation process to obtain a black characteristic amount suitable for the achromatic region. decide. Therefore, the black characteristic amount determination means determines a black characteristic amount suitable for an achromatic color area for a character area that is an achromatic color and a color blur area that is determined to be a chromatic color but should be originally an achromatic color. To do. Thereby, there is an effect that the reproducibility of gray in these regions can be improved or the amount of color material used can be reduced.

  On the other hand, when it is determined that the region identification signal is a signal representing a halftone dot region or a photographic region, the parameter selection unit selects the second parameter as a selection parameter. As described above, when the parameter selection unit selects the second parameter, the black characteristic amount determination unit performs a two-dimensional black characteristic amount calculation process, and determines the black characteristic amount considering the saturation component. . Thereby, since the color reproducibility in these regions can be improved, the image quality can be improved.

  In the image processing apparatus according to the present invention, the characteristic signal further includes at least one of a character area, a color blur area, a halftone area, or a photographic area to which each pixel or pixel group included in the image belongs. An area identification signal representing the type of the area to be included, and when the second black characteristic amount acquisition means determines that the area identification signal is a signal representing a character area or a color blur area, the first function data If the second black characteristic amount is obtained from the second function data, while the region identification signal is determined to be a signal representing a halftone dot region or a photographic region, the second black characteristic amount is obtained from the second function data. It is preferable to obtain.

  In the above configuration, when it is determined that the area identification signal is a signal representing a character area or a color blur area, the second black characteristic amount acquisition unit acquires the second black characteristic amount from the first function data. . As described above, the black characteristic amount determination unit obtains the same effect as the one-dimensional black generation process when the second black characteristic amount acquisition unit acquires the second black characteristic amount from the second function data. A two-dimensional black characteristic amount calculation process is performed to determine a black characteristic amount suitable for the achromatic region. Therefore, the black characteristic amount determination means determines a black characteristic amount suitable for an achromatic color area for a character area that is an achromatic color and a color blur area that is determined to be a chromatic color but should be originally an achromatic color. To do. Thereby, there is an effect that the reproducibility of gray in these regions can be improved or the amount of color material used can be reduced.

  On the other hand, when it is determined that the region identification signal is a signal representing a halftone dot region or a photographic region, the second black characteristic amount acquisition unit acquires the second black characteristic amount from the second function data. As described above, the black characteristic amount determination unit performs a two-dimensional black characteristic amount calculation process when the second black characteristic amount acquisition unit acquires the second black characteristic amount from the second function data, and The black characteristic amount taking into account the degree component is determined. Thereby, since the color reproducibility in these regions can be improved, the image quality can be improved.

  An image forming apparatus according to the present invention includes any one of the above-described image processing apparatuses.

  According to the above configuration, by using the common function data, it is possible to determine the black characteristic amount suitable for the achromatic region and the black characteristic amount considering the saturation component. It is possible to reduce the memory resources and simplify the configuration of the apparatus that performs the black characteristic amount calculation process, and it is possible to provide an image forming apparatus that can output a high-quality image.

  Note that the above-described image processing apparatus may be realized by a computer. In this case, an image processing program for causing the image processing apparatus to be realized in the computer by operating the computer as each of the above means, and a computer-readable recording medium on which the image processing program is recorded also fall within the scope of the present invention.

  An embodiment of the present invention will be described with reference to FIGS.

First, a digital color copying machine 1 will be described as an embodiment of an image forming apparatus including a color image processing apparatus 20 to which the present invention is applied. FIG. 2 is a block diagram illustrating a configuration of an image forming apparatus to which the color image processing apparatus 20 is applied. As shown in this figure, the digital color copying machine 1 includes a color image input device 10, a color image processing device 20, a color image output device 30, and an operation panel 40.
[Color image input device 10]
The color image input device 10 includes a scanner unit including a CCD (Charge Coupled Device), for example. The color image input device 10 reads a reflected light image from an input original as an RGB (R: red / G: green, B: blue) signal by CDD. The color image input device 10 generates image data based on the read result, and outputs the image data to the color image processing device 20.
[Color image output device 30]
The color image output device 30 outputs an image represented by the image data input from the color image processing device 20 to an output medium such as paper. Examples of the color image output device 30 include a color image output device using an electrophotographic method or an inkjet method. The output method of the color image output device 30 is not particularly limited.
[Color image processing apparatus 20]
The color image processing apparatus 20 includes an A / D conversion unit 21, a shading correction unit 22, an input tone correction unit 23, a region separation processing unit 24, a color correction unit 25, a black generation and under color removal unit 26, and a spatial filter processing unit 27. , An output gradation correction unit 28 and a gradation reproduction processing unit 29. The analog signal read by the color image input device 10 passes through the color image processing device 20 within an A / D conversion unit 21, a shading correction unit 22, an input tone correction unit 23, a region separation processing unit 24, and a color correction unit 25. , Black generation and lower color removal unit 26, spatial filter processing unit 27, output gradation correction unit 28, and gradation reproduction processing unit 29, and are sent in the order CMYK (C: cyan, M: magenta, Y: yellow). The digital color signal is output to the color image output device 30.
[A / D converter 21]
The A / D (analog / digital) converter 21 converts an analog RGB signal into a digital RGB signal.
[Shading correction unit 22]
The shading correction unit 22 removes various distortions included in the signal generated in the illumination system, the imaging system, and the imaging system of the color image input apparatus 10 from the digital RGB signal sent from the A / D conversion unit 21. Apply processing.
[Input tone correction unit 23]
The input tone correction unit 23 adjusts the color balance of the RGB signal (RGB reflectance signal) from which various distortions have been removed by the shading correction unit 22 and at the same time, the color image processing device 20 such as a density signal. The signal is converted into a signal that can be handled easily by the image processing system employed in the system.
[Area Separation Processing Unit 24]
Based on the RGB signal sent from the input tone correction unit 23, the region separation processing unit 24 sets each pixel or pixel group in the input image to at least one of a character region, a dot region, a photographic region, and a color blur region. Separate the crab. Details of this region separation processing will be described later. Note that the region separation processing by the region separation processing unit 24 is not limited to this. For example, the region separation processing unit 24 may separate each pixel or pixel group in the input image into a character region and a halftone dot region, or a character region and a photo region. Further, the region separation processing unit 24 may separate the region into a background region in addition to the character region, the halftone dot region, the photograph region, and the color blur region. Alternatively, the region separation processing unit 24 does not perform the region separation processing for each pixel or pixel group, but performs the region separation processing for each rectangular region or a region (pixel group) having a plurality of pixels. Also good.

The region separation processing unit 24 generates a region identification signal SEG indicating what region each pixel or pixel group belongs to based on the region separation result. Then, the region separation processing unit 24 outputs the generated region identification signal SEG to the subsequent black generation and under color removal unit 26, the spatial filter processing unit 27, and the gradation reproduction processing unit 29. Further, the region separation processing unit 24 outputs the input RGB signal output from the input tone correction unit 23 to the subsequent color correction unit 25 as it is.
[Color correction unit 25]
The color correction unit 25 removes color turbidity components based on the spectral characteristics of the CMY color material including unnecessary absorption components in order to faithfully reproduce the color of the image represented by the input image data. At this time, the color correction unit 25 uses a method of using an LUT (Look Up Table) that holds the correspondence between the input RGB signal and the output CMY signal, or a conversion matrix shown in the following equation (1). The color masking method used is used.

When the color masking method is used, the color correction unit 25 outputs an L * a * b * value (CIE 1976 L * a * b * signal (CIE: Commission International de l'Eclairage: RGB data when a scanner reads a color patch having the same L * a * b * as L *: brightness, a *, b *: chromaticity)) Are prepared in advance in correspondence with a set of CMY data given to the image output apparatus. Then, the color correction unit 25 calculates the coefficients of the conversion matrix from a11 to a33 shown in Expression (1) from the combination, and performs color correction processing using the calculated coefficients. Here, the color correction unit 25 adds a second-order or higher-order term when the accuracy of color correction is further increased.
[Black generation and under color removal unit 26]
The black generation / under color removal unit 26 performs black generation processing and under color removal processing. More specifically, the black generation and under color removal unit 26 performs black generation processing for generating a black signal (K signal) from the three-color CMY signals after color correction output from the color correction unit 25. Further, the black generation and under color removal unit 26 performs under color removal processing for generating a new CMY signal by subtracting the under color removal signal (UCR signal) obtained by the under color removal amount calculation processing from the original CMY signal. Do. That is, the black generation and lower color removal unit 26 converts the three-color CMY signal into the four-color CMYK signal. Details of this conversion will be described later. The black generation and under color removal unit 26 outputs the CMYK signal after color conversion to the spatial filter processing unit 27.
[Spatial filter processing unit 27, output tone correction unit 28, tone reproduction processing unit 29]
The spatial filter processing unit 27 performs spatial filter processing using a digital filter on the image data composed of CMYK signals based on the region identification signal SEG, and corrects spatial frequency characteristics, thereby blurring or graininess of the output image. Prevent deterioration. Similar to the spatial filter processing unit 27, the gradation reproduction processing unit 29 performs a gradation reproduction process for reproducing a pseudo gradation on image data composed of CMYK signals based on the region identification signal SEG.

  For example, for a region separated into character regions by the region separation processing unit 24, the spatial filter processing unit 27 performs sharp enhancement processing to increase the reproducibility of characters in particular, thereby increasing the high frequency enhancement amount. To do. In addition, the gradation reproduction processing unit 29 selects and performs binarization or multi-value processing on a high-resolution screen suitable for high-frequency reproduction.

  In addition, for the region separated into halftone dot regions by the region separation processing unit 24, first, the spatial filter processing unit 27 performs low-pass filter processing for removing the input halftone dot component. Next, the output tone correction unit 28 performs output tone correction processing for converting a signal such as a density signal into a halftone dot area ratio that is a characteristic value of the color image output device 30. Finally, the gradation reproduction processing unit 29 performs gradation reproduction processing (halftone generation) so that the image is finally separated into pixels and each gradation can be reproduced.

A gradation reproduction processing unit 29 performs binarization or multi-value processing on the screen with an emphasis on gradation reproducibility for the region separated into the photographic regions by the region separation processing unit 24.
[Operation panel 40]
The operation panel 40 includes, for example, a touch panel in which a display unit such as a liquid crystal display and an operation unit such as a setting button are integrated. Based on information input through the operation panel 40, operations of the color image input device 10, the color image processing device 20, and the color image output device 30 are controlled.

The image data to be subjected to each processing described above is temporarily stored in a storage unit (not shown), read at a predetermined timing, and finally input to the color image output device 30. The above processing is controlled by a CPU (Central Processing Unit) (not shown).
[Overview of Black Generation and Undercolor Removal Unit 26]
The black generation and under color removal unit 26 is a device that performs black generation processing and under color removal processing on image data representing an image composed of a plurality of color components. By performing these processes, a black component amount not included in the input image data is newly generated, or a lower color amount is removed from each color component amount included in the input image data. At this time, black generation processing or under color removal processing is performed by using the black characteristic amount. The “black characteristic amount” here is a generic term for the black generation amount K used when performing the black generation processing and the under color removal amount UCR used when performing the under color removal processing.

Here, the color image processing apparatus 20 selectively performs one-dimensional and two-dimensional black generation processing (under color removal processing) by using the same single hardware configuration. The color image processing apparatus 20 realizes this in the black generation and under color removal unit 26. The color image processing device 20 performs either one-dimensional or two-dimensional black generation processing based on a region identification signal SEG that is output by the region separation processing unit 24 serving as a characteristic signal output unit and represents the type of region of the input image. Choose what to do. Therefore, the configuration and processing of the region separation processing unit 24 and the black generation and under color removal unit 26 will be described in detail below.
[Configuration of Region Separation Processing Unit 24]
First, a detailed configuration of the region separation processing unit 24 will be described with reference to FIG. FIG. 3 is a block diagram illustrating a configuration of the region separation processing unit 24. According to this figure, the region separation processing unit 24 is generally configured to include a region separation unit 31 and a color blur determination unit 32. Here, the color blur determination unit 32 includes a chromatic color determination unit 33, an edge extraction processing unit 34, and a neighboring pixel determination unit 35.

As described above, the region separation processing unit 24 separates each pixel into at least one of a character region, a dot region, a photographic region, and a color blur region, and outputs a region identification signal SEG indicating the separation result. Here, in the region separation processing unit 24, first, the region separation unit 31 separates the input image data into a character region, a halftone dot region, or a photo region. Next, the color blur determination unit 32 determines whether the area including the character area and the neighboring pixels is causing color blur.
[Area Separation Method by Region Separation Processing Unit 24]
The area separation processing unit 24 is described in, for example, Japanese Patent Application Laid-Open No. 2001-223915 as an area separation method for separating input image data into a character area, a halftone dot area, or a photographic area and discriminating a color blur area. Method is used. Therefore, a method in which the region separation processing unit 24 first separates input image data into a character region, a halftone dot region, or a photo region will be described. The region separation processing unit 24 first sets one pixel included in the input image data as a target pixel. Then, the region separation processing unit 24 performs the determination described below in a block composed of M × N (M and N are natural numbers) pixels centered on the target pixel. Based on the determination result, the region separation processing unit 24 determines the type of region to which the target pixel belongs.

  First, the region separation processing unit 24 calculates an average value (Dave) of signal levels for the nine pixels in the center of the block. Next, the region separation processing unit 24 binarizes each pixel in the block using the calculated Dave. At the same time, the region separation processing unit 24 obtains the maximum pixel signal level (Dmax) and the minimum pixel signal level (Dmin).

Here, when the halftone dot region is identified, the region separation processing unit 24 uses the property that the halftone dot region has a large variation in the image signal in the small region and has a higher density than the background. More specifically, the region separation processing unit 24 changes the number of change points changing from 0 to 1 and the number of change points changing from 1 to 0 in the main scanning and sub-scanning directions for the binarized data. Ask for. Then, the region separation processing unit 24 sets these values as Kh and Kv, respectively, and compares them with the threshold values TH and TV. Further, the region separation processing unit 24 compares Dmax, Dmin, and Dave with the threshold values B1 and B2 to prevent erroneous determination with the background. That is,
Dmax-Dave> B1
Dave-Dmin> B2
KH> TH
KV> TV
If it is determined that all of the above conditions are satisfied, the region separation processing unit 24 determines that the region to which the target pixel belongs is a halftone dot region, and if it is determined that it is not satisfied, determines that the region is a region other than the halftone dot region. .
[Identification of area]
Next, the region separation processing unit 24 determines the identification of the character region using the fact that the difference between the maximum signal level and the minimum signal level is large and the color density is likely to be high in the character region. First, the region separation processing unit 24 compares the maximum and minimum signal levels previously obtained in the non-halftone region and the difference (Dsub) with the threshold values PA, PB, and PC, respectively. Then, the region separation processing unit 24 determines that the region determined to satisfy the following condition is a character region, and determines the region determined not to be satisfied as a photo region. That is,
Dmax> PA
Dmin <PB
Dsub> PC
When it is determined that any one of the above conditions is satisfied, the region separation processing unit 24 determines that the region to which the target pixel belongs is a character region, and otherwise determines that the region is a photo region.

Finally, the region separation processing unit 24 determines whether the color blur is generated in the character region extracted by the above method in the color blur determination unit 32. At that time, the region separation processing unit 24 uses the following conditions for the region including the character region and its neighboring pixels (for example, about several pixels) based on the occurrence of color bleeding outside the edge of the black character. Then, it is determined whether or not color bleeding has occurred. In other words, the pixel of interest is determined by
When it is determined that all three conditions are satisfied, that is, a chromatic color, an edge, and a black character region pixel in any of the surrounding pixels, the region separation processing unit 24 sets this pixel as a color blur region. Judge as belonging.

Based on the region separation results (character region, halftone dot region, photo region, color blur region) obtained by the above processing, the region separation processing unit 24 uses a signal representing the type of these regions as a region identification signal SEG. The data is sent to each processing unit in the subsequent stage. Each processing unit that receives the region identification signal SEG performs an optimum process according to the input region identification signal SEG.
[Configuration of Black Generation and Undercolor Removal Unit 26]
Next, the configuration and processing of the black generation and under color removal unit 26 will be described with reference to FIGS. FIG. 4 is a block diagram illustrating a configuration of the black generation and under color removal unit 26. According to this figure, the black generation and under color removal unit 26 is roughly configured to include a maximum / minimum value calculation unit 41 (parameter calculation means), a blur processing unit 42, an under color removal amount calculation unit 43, and a black generation amount calculation unit. 44 and an under color removal processing unit 45.
[Maximum / Minimum Value Calculation Unit 41]
The maximum value / minimum value calculation unit 41 receives the CMY signal output from the color correction unit 25. Then, the maximum value / minimum value calculation unit 41 compares the input CMY signals with each other, and calculates the maximum value and the minimum value of them. Further, the maximum value / minimum value calculation unit 41 uses the calculated maximum value and minimum value as the MIN signal (first parameter) and the MAX signal (second parameter), respectively, the blur processing unit 42, and the under color removal. This is output to the amount calculation unit 43 and the black generation amount calculation unit 44.
[Bludge processor 42]
The blur processing unit 42 receives the region identification signal SEG, the MAX signal, and the MIN signal. As shown in FIG. 5, the blur processing unit 42 includes an average value calculation unit 51 and a blur signal selection unit 52.
[Average Value Calculation Unit 51]
The average value calculation unit 51 receives the MAX signal and the MIN signal. The average value calculation unit 51 calculates the average value of the input MAX signal and MIN signal, and outputs the calculated average value to the blur signal selection unit 52 as an AVE signal.
[Blurring signal selection unit 52]
The blur signal selection unit 52 receives the CMY signal, the AVE signal, and the region identification signal SEG. The blur signal selection unit 52 determines the C1M1Y1 signal using the input CMY signal and AVE signal. At this time, the blur signal selection unit 52 selects a CMY signal and an AVE signal based on the region identification signal SEG and determines different C1M1Y1 signals. More specifically, when the blur signal selection unit 52 determines that the area identification signal SEG is a signal representing a character area or a color blur area, the value of each C1M1Y1 signal is the same as the value of the AVE signal. Value. On the other hand, if the blur signal selection unit 52 determines that the region identification signal SEG is a signal representing a halftone dot region or a photograph region, the input CMY signal is directly used as the C1M1Y1 signal. In any case, the blur signal selection unit 52 outputs the calculated C1M1Y1 signal to the under color removal processing unit 45.

As a result of such a calculation method, the size of each CMY signal is aligned with that of the AVE signal in the pixels belonging to the achromatic region. Therefore, the saturation component is removed from the color signal of the region, and the color of the region approaches gray. Thereby, the reproducibility of the character color is improved.
[Under Color Removal Amount Calculation Unit 43]
The under color removal amount calculation unit 43 receives the MIN signal, the MAX signal, and the region identification signal SEG. The under color removal amount calculation unit 43 calculates the under color removal amount UCR by using a under color removal amount table (UCR table) or the like based on the MIN signal and the MAX signal. At this time, the under color removal amount calculation unit 43 switches the under color removal amount table to be selected based on the region identification signal SEG. Details of these will be described later. The under color removal amount calculation unit 43 outputs the calculated under color removal amount UCR to the under color removal processing unit 45.
[Black generation amount calculation unit 44]
The black generation amount calculation unit 44 receives the MIN signal, the MAX signal, and the region identification signal SEG. The black generation amount calculation unit 44 calculates a black generation amount K ′ by using a table (K table) or the like based on the MIN signal and the MAX signal. At that time, the black generation amount calculation unit 44 switches the table to be selected based on the region identification signal SEG. Details of these will be described later. Note that the black generation amount calculation unit 44 outputs the calculated black generation amount K ′ to the spatial filter processing unit 27.
[Under Color Removal Processing Unit 45]
The under color removal processing unit 45 receives the C1M1Y1 signal and the under color removal amount UCR. The under color removal amount calculation unit 43 calculates a C′M′Y ′ signal using these input signals and parameters. At that time, the under color removal processing unit 45 performs under color removal processing using the calculation method shown in the following equation.

C '= C1-UCR
M '= M1-UCR
Y '= Y1-UCR
As shown in these equations, the under color removal processing unit 45 performs under color removal processing for dividing the under color removal amount UCR from each of the inputted C1M1Y1 signals, and outputs the C′M′Y ′ signal. calculate. The under color removal processing unit 45 outputs the calculated C′M′Y ′ signal to the spatial filter processing unit 27.

Here, the under color removal amount calculation unit 43 and the black generation amount calculation unit 44 perform essentially the same processing, and calculate the under color removal amount or the black generation amount to be output. The only difference between these processing units is whether the lookup table used is a UCR table or a K table. Therefore, in the following, the configuration and processing of the black generation amount calculation unit 44 will be described in detail, and description of the undercolor removal amount calculation unit 43 will be omitted.
[Details of Black Generation Amount Calculation Unit 44]
The configuration of the black generation amount calculation unit 44 will be described with reference to FIG. FIG. 1 shows an embodiment of the present invention, and is a block diagram showing a main configuration of a black generation amount calculation unit 44. According to this figure, the black generation amount calculation unit 44 is generally configured to include a signal selection unit 101 (parameter selection means) and a black generation unit 102. Here, the black generation unit 102 includes a K table memory 103 (function data storage unit), a K table memory access unit 104 (black characteristic amount acquisition unit), and a black generation amount calculation unit 105.
[Signal Selection Unit 101]
The signal selection unit 101 receives the MIN signal, the MAX signal, and the region identification signal SEG. The signal selection unit 101 selects either the input MAX signal or MIN signal. At that time, the signal selection unit 101 selects the MIN signal or the MAX signal based on the input region identification signal SEG. More specifically, when the signal selection unit 101 determines that the region identification signal SEG is a signal representing a character region or a color blur region, the signal selection unit 101 outputs a MIN signal as a selection signal SIG (selection parameter). On the other hand, when the signal selection unit 101 determines that the region identification signal SEG is a signal representing a halftone dot region or a photographic region, the signal selection unit 101 outputs a MAX signal as the selection signal SIG. The reason why the signal selection unit 101 performs such signal selection based on the region identification signal SEG will be described later. The signal selection unit 101 outputs the selection signal SIG to the black generation amount calculation unit 105.
[K table memory 103]
The K table memory 103 is storage means (memory) for storing a plurality of K tables. More specifically, as shown in FIG. 1, the K table memory 103 stores n (n is a positive integer) K tables T1 to Tn. Each of these K tables T1 to Tn is optimized corresponding to the region identification signal SEG. Also, as shown in FIG. 6, each of the K tables T1 to Tn includes two one-dimensional K tables (one-dimensional K table LUT1, one-dimensional K table LUT2). Here, each of the one-dimensional K tables LUT1 and LUT2 stores a plurality of MIN signals and black generation amounts in association with one-to-one relationships.
[K table memory access unit 104]
The K table memory access unit 104 receives the MIN signal and the area identification signal SEG. The K table memory access unit 104 accesses the K table memory 103 and selects one K table. At this time, the K table memory access unit 104 selects a K table that is optimized in accordance with the region identification signal SEG, based on the input region identification signal SEG. For example, if the K table memory access unit 104 determines that the region identification signal SEG is a signal representing a character region, the K table memory access unit 104 selects a K table in which the black generation amount optimized for the character region is stored.

  As described above, the K table selected by the K table memory access unit 104 includes the one-dimensional K tables LUT1 and LUT2. Therefore, the K table memory access unit 104 reads the black generation amount K1 and the black generation amount K2 from these tables based on the MIN signal. More specifically, the K table memory access unit 104 reads the black generation amount K1 from the one-dimensional K table LUT1, and reads the black generation amount K2 from the one-dimensional K table LUT2. The K table memory access unit 104 outputs the read black generation amount K1 and black generation amount K2 to the black generation amount calculation unit 105.

  The one-dimensional K table LUT1 is an achromatic color axis black generation amount table corresponding to an achromatic color region (gray region). In other words, the one-dimensional K table LUT1 stores the MIN signal (first parameter) and the black generation amount suitable for the achromatic region in a one-to-one relationship. On the other hand, the one-dimensional K table LUT2 is a black generation amount table (saturation) based on a combination of values with the highest saturation for a certain MIN signal when the MAX signal is maximum (255). A black generation amount table that takes into account the components (hereinafter referred to as a high saturation axis black generation amount table). That is, the one-dimensional K table LUT2 stores the MIN signal and the black generation amount taking the saturation component into consideration in a one-to-one relationship. Of the two one-dimensional K tables included in one K table memory, one is always an achromatic color axis black generation amount table, and the other is always a high saturation axis black generation amount table. Therefore, the K table memory access unit 104 reads the black generation amounts one by one from the two one-dimensional K tables having different color characteristics.

In the present embodiment, as described above, the K table memory 103 stores a plurality of K tables in which two one-dimensional K tables are paired. However, the K table memory 103 may store a plurality of one-dimensional K tables as they are without being paired as they are. In this case, the K table memory access unit 104 selects two different one-dimensional K tables based on the region identification signal SEG. Then, the K table memory access unit 104 reads the black generation amount K1 and the black generation amount K2 from the two selected one-dimensional K tables based on the MIN signal. In this case, the K table memory access unit 104 always has one achromatic color axis black generation amount table (one-dimensional K table LUT1) and one high saturation axis black generation amount table (one-dimensional K table LUT2). A process of selecting and reading the black generation amount K1 and the black generation amount K2 may be performed.
[Black generation amount calculation unit 105]
The black generation amount calculation unit 105 receives a black generation amount K1, a black generation amount K2, a MIN signal, and a selection signal SIG. The black generation amount calculation unit 105 performs interpolation calculation using these input parameters, and calculates a black generation amount K ′ for the image data. The black generation amount calculation unit 105 outputs the calculated black generation amount K ′ to the spatial filter processing unit 27.

  Here, in the area determined as the halftone dot area or the photographic area by the area separation processing unit 24, as described above, the blur processing unit 42 outputs the input CMY signal as it is as the C1M1Y1 signal. Therefore, when the black generation amount calculation unit 105 obtains the black generation amount K ′, the black generation amount K1 read from the one-dimensional K table LUT1 (achromatic color axis black generation amount table) corresponding to the achromatic region, and the saturation An interpolation operation based on the MIN signal and the MAX signal is performed from the black generation amount K2 read from the one-dimensional K table LUT2 (high saturation axis black generation amount table) taking into account the components, and the optimum according to the saturation It is preferable to obtain a black generation amount K ′ to be applied to the image data by performing a two-dimensional black generation process.

  On the other hand, the region determined as the character region or the color blur region by the region separation processing unit 24 is originally a gray (achromatic) region. Then, as described above, the blur processing unit 42 performs processing for such a region by aligning the input CMY signal with the AVE signal that is an average value of the MIN signal and the MAX signal to obtain the C1M1Y1 signal. Therefore, the black generation amount calculation unit 105 calculates the black generation amount K1 read from the one-dimensional K table LUT1 based on the MIN signal as it is as the black generation amount K ′ for such regions. It is preferable to obtain a black generation amount K ′ to be applied to image data by performing a one-dimensional black generation process that is not affected.

The black generation amount calculation unit 105 performs one interpolation calculation as described below to selectively perform either one-dimensional or two-dimensional black generation processing according to the region separation result. Realized by. This interpolation calculation will be described with reference to FIGS.
[Interpolation calculation]
FIGS. 7 and 8 show that the black generation amount calculation unit 105 performs two-dimensional black generation processing by interpolation from the two black generation amounts read from the two one-dimensional K tables, and generates the black generation amount for the image data. It is a figure which shows the concept of the method of calculating K '. As shown in these figures, the interpolation calculation performed by the black generation amount calculation unit 105 obtains the black generation amount K ′ from the read two black generation amounts K1 and K2 based on the ratio of the coefficients α and β. . Here, α = SIG value−MIN value, and β = 255−SIG value.

  As shown in FIG. 7, the black generation amount calculation unit 105 displays the black generation amount K1 selected from the one-dimensional K table LUT1 and the black generation amount K2 selected from the one-dimensional K table LUT2 on one graph. , A straight line having a black generation amount K1 as a start point and a black generation amount K2 as an end point is assumed. The black generation amount calculation unit 105 assumes that the black generation amount K ′ calculated by the interpolation calculation is included on this line segment. Next, the black generation amount calculation unit 105 calculates the black generation amount corresponding to the selection signal SIG on the assumed straight line as the black generation amount K ′ for the image data based on the ratio of α and β described above. .

  The interpolation calculation performed by the black generation amount calculation unit 105 will be described in more detail with reference to FIG. In the graph 80 shown in FIG. 8, the horizontal axis represents the MIN signal, and the vertical axis represents the selection signal SIG. A straight line 82 included in the graph 80 represents a high saturation axis corresponding to the high saturation axis black generation amount table (one-dimensional K table LUT2). On the other hand, a straight line 84 included in the graph 80 represents a gray axis corresponding to the black generation amount table for the achromatic color axis (one-dimensional K table LUT1). Here, the black generation amount calculation unit 105 calculates a value between the black generation amount K2 on the straight line 82 and the black generation amount K1 on the straight line 84 based on the ratio of α and β. That is, the black generation amount calculation unit 105 calculates the black generation amount at the position corresponding to the MAX signal on the K1-K2 straight line on the vertical axis of the graph 80 as the black generation amount K ′ to be applied to the image data.

  As described above, when performing the interpolation calculation, the black generation amount calculation unit 105 divides α and β by the 255-MIN signal, and calculates each as a weighting factor. Then, the black generation amount calculation unit 105 calculates the black generation amount K ′ by multiplying the weight coefficients α and β by the black generation amount K1 and the black generation amount K2, respectively, and adding them. That is, the black generation amount calculation unit 105 calculates the black generation amount K ′ using the following equation (2).

  Here, as described above, when it is determined that the region identification signal SEG is a signal representing a halftone dot region or a photograph region, the signal selection unit 101 outputs a MAX signal as the selection signal SIG. In this case, the black generation amount calculation unit 105 calculates the black generation amount K ′ by performing the interpolation calculation shown in Expression (2) based on the MAX signal and the MIN signal from the black generation amount K1 and the one-dimensional K table LUT2. .

  In this case, as shown in Expression (2), FIG. 7 and FIG. 8, the calculated black generation amount K ′ includes information on two black generation amounts K1 and K2 read from different one-dimensional K tables. Will be reflected. More specifically, the black generation amount K ′ reflects the achromatic color characteristic of the black generation amount K1 and the chromatic color characteristic of the black generation amount K2. Thereby, the calculated black generation amount K ′ is equivalent to the black generation amount obtained from the two-dimensional black generation table in which the MIN signal, the MAX signal, and the black generation amount are stored in a two-to-one relationship in advance. It will be a thing. That is, the black generation amount calculation unit 105 performs a process comparable to the two-dimensional black generation process on the halftone dot area or the photographic area. As a result, an appropriate black generation process corresponding to the saturation is performed in the halftone dot region and the photo region, so that the image quality is improved.

  On the other hand, as described above, when the signal selection unit 101 determines that the region identification signal SEG is a signal representing a character region or a color blur region, the signal selection unit 101 outputs a MIN signal as the selection signal SIG. Therefore, in this case, the black generation amount calculation unit 105 performs the interpolation calculation shown in Expression (2) based on the two MIN signals, the black generation amount K1, and the black generation amount K2, and calculates the black generation amount K ′. To do. Here, in the equation (2), when the MIN signal is substituted for the selection signal SIG, it becomes equal to the following equation (3).

  That is, in Expression (3), the weighting coefficients α and β in Expression (2) are deleted, and the black generation amount K ′ and the black generation amount K1 have the same value. That is, when the selection signal SIG is a MIN signal, the black generation amount calculation unit 105 does not substantially perform the interpolation calculation shown in Expression (2). This will be specifically described with reference to FIG. 9 and FIG.

  9 and 10 show that when the MIN signal is the selection signal SIG, the black generation amount calculation unit 105 performs two-dimensional black generation processing by interpolation calculation from the black generation amounts read from the two one-dimensional K tables. It is a figure which shows the concept of the method of calculating the black generation amount K 'with respect to image data by not performing substantially. As shown in these drawings, the black generation amount calculation unit 105 calculates a point where the selection signal SIG = MIN signal on the K1-K2 straight line as the black generation amount K ′. That is, the black generation amount calculation unit 105 calculates the black generation amount K1 value corresponding to the MIN signal as the black generation amount K ′. Therefore, the black generation amount calculation unit 105 calculates the black generation amount K1 selected from the one-dimensional K table LUT1 as it is as the black generation amount K ′ for the image data.

  In other words, when the black generation amount calculation unit 105 performs the interpolation calculation using Expression (2), when the MIN signal and the selection signal SIG are equal, the calculated black generation amount K ′ is the black generation amount K1. Will be equal. Here, the black generation amount K1 is the black generation amount read from the one-dimensional K table LUT1 (achromatic color axis black generation amount table). Therefore, the black generation amount calculation unit 105 performs one-dimensional black generation processing on the character area or the color blur area. In this case, the black generation amount calculation unit 105 performs black generation processing that is not affected by saturation using the one-dimensional K table LUT1 suitable for the gray region. Therefore, the effect of excellent character reproducibility is achieved.

  The operations and effects of the black generation amount calculation unit 44 will be described together below. When it is determined that the area identification signal SEG is a signal representing a character area or a color blur area, the signal selection unit 101 selects the MIN signal as the selection signal SIG. As described above, when the signal selection unit 101 selects the MIN signal, the black generation amount calculation unit 44 performs a process equivalent to the one-dimensional black generation process, and calculates the black generation amount K ′ suitable for the achromatic region. decide. Therefore, the black generation amount calculation unit 44 performs a black generation amount K suitable for an achromatic color region with respect to a character region that is an achromatic color or a color blur region that is determined to be a chromatic color but should originally be an achromatic color. 'Determine. Thereby, the reproducibility of gray in these areas can be improved, and the amount of color material used can be reduced.

  On the other hand, when it is determined that the region identification signal SEG is a signal representing a halftone dot region or a photographic region, the signal selection unit 101 selects the MAX signal as the selection signal SIG. As described above, when the signal selection unit 101 selects the MAX signal, the black generation amount calculation unit 44 performs a two-dimensional black generation process and determines a black generation amount that takes the saturation component into consideration. Therefore, the black generation amount calculation unit 44 determines the black generation amount in consideration of the saturation component for the halftone dot region and the photographic region. Thereby, the color reproducibility in these regions can be improved, so that the image quality can be improved.

  That is, as a result, the black generation amount calculation unit 44 can selectively perform either one-dimensional or two-dimensional black generation processing based on the region identification signal SEG. That is, the black generation amount calculation unit 44 can switch between the one-dimensional and two-dimensional black generation processing based on the region identification signal SEG, in other words, according to the type of region (image characteristics).

  As described above, the black generation amount calculation unit 44 selects and performs different one-dimensional or two-dimensional black generation processing according to the value of the selection signal SIG. Here, the signal selection unit 101 selects the selection signal SIG from the MIN signal or the MAX signal based on the region identification signal SEG. Therefore, the black generation amount calculation unit 44 performs one-dimensional black generation processing or two-dimensional black generation processing based on the region identification signal SEG, in other words, according to the type of region (image characteristics). Become.

  Accordingly, the color image processing apparatus 20 including the black generation amount calculation unit 44 can perform both one-dimensional and two-dimensional black generation processing using the same hardware. Therefore, the color image processing apparatus 20 does not need to include a number of dedicated hardware for performing black generation processing of a specific dimension, can simplify the configuration of the apparatus, and can reduce the cost of the apparatus. Furthermore, since the color image processing apparatus 20 uses a one-dimensional K table, the amount of memory for storing the K table can be significantly reduced as compared with the case where a two-dimensional K table is used.

Note that the interpolation calculation performed by the black generation amount calculation unit 105 is not limited to the linear interpolation calculation shown in Expression (2). For example, the black generation amount calculation unit 105 may perform an interpolation calculation performed on a curve that passes through the black generation amount K1 and the black generation amount K2, in which the state of change is set in an expression in advance. In this case, the interpolation calculation expression may be an expression in which the black generation amount K ′ is equal to the black generation amount K1 when the selection signal SIG is equal to the MIN signal that is the first parameter.
[Flow of black generation processing and under color removal processing]
The flow of the black generation process and the under color removal process described above will be described with reference to the flowcharts shown in FIGS.

  FIG. 11 is a flowchart showing the overall processing flow in the black generation amount calculation unit 44. According to this figure, first, the maximum value / minimum value calculation unit 41 calculates the maximum value MAX signal and the minimum value MIN signal of the input CMY signal (step S10). Next, using the calculated MIN signal and MAX signal, the blur processing unit 42 performs a blur process on the CMY signal (step S11). Next, the black generation amount calculation unit 44 calculates a black generation amount K ′ (step S12). Next, the under color removal amount calculation unit 43 calculates the under color removal amount UCR (step S13). Finally, the under color removal processing unit 45 performs under color removal processing by subtracting the value of the under color removal amount UCR calculated in step S13 from the value of the C1M1Y1 signal after the blurring process (step S14).

  FIG. 12 is a flowchart showing the flow of color blur processing. According to this figure, first, the blur signal selection unit 52 determines whether or not the region identification signal SEG is a signal representing a character region or a color blur region (step S21). Here, when the determination result in step S21 is “true” (YES), the average value calculation unit 51 calculates an AVE signal that is an average value of the MIN signal and the MAX signal (step S22). Then, the blur signal selection unit 52 replaces all the C1M1Y1 signals after the blur process with AVE signals and outputs them to the under color removal processing unit 45 (step S24). On the other hand, when the determination result in step S21 is “false” (NO), the blur signal selection unit 52 sets the input CMY signal as the C1M1Y1 signal and outputs it as it is to the under color removal processing unit 45 (step S23).

  FIG. 13 is a flowchart illustrating an example of the flow of black generation amount calculation processing. According to this figure, first, the signal selection unit 101 determines whether or not the region identification signal SEG is a signal representing a character region or a color blur region (step S31). Here, when the determination result in step S31 is “true” (YES), the signal selection unit 101 sets a MIN signal as the selection signal SIG and outputs it to the black generation amount calculation unit 105 (step S32). . On the other hand, when the determination result in step S31 is “false” (NO), the signal selection unit 101 sets the MAX signal as the selection signal SIG and outputs it to the black generation amount calculation unit 105 (step S33).

  Next, the K table memory access unit 104 selects one K table according to the region identification signal SEG (step S34), and from the two one-dimensional K tables LUT1 and LUT2 included in the selected K table, MIN Based on the signal, the black generation amount K1 and the black generation amount K2 are read (step S35). Finally, the black generation amount calculation unit 105 uses the black generation amount K1, the black generation amount K2, the MIN signal, and the selection signal SIG (that is, the MIN signal or the MAX signal) to perform the interpolation calculation shown in Expression (2). Then, the black generation amount K ′ is calculated (step S36).

FIG. 14 is a flowchart illustrating an example of the flow of undercolor removal amount calculation processing. According to this figure, the under color removal process performed by the under color removal amount calculation unit is performed by performing the same process as the black generation process except that the lookup table to be used is a UCR table instead of a K table. This is a process of calculating the color removal amount UCR. Therefore, since the flow of this process is substantially the same as the flow shown in FIG. 13, the description of S41 to S46 is omitted instead of the description of S31 to S36.
[Black generation amount calculation unit 200]
Note that the object of the present invention can also be achieved by the black generation amount calculation unit 200 configured to select the K table to be used instead of selecting the MIN signal and the MAX signal, as shown in FIG. Therefore, the configuration and processing of the black generation amount calculation unit 200 will be described in detail below.

FIG. 15 shows another embodiment of the present invention, and is a block diagram showing the configuration of the black generation amount calculation unit 200. According to this figure, the black generation amount calculation unit 200 roughly includes a K table memory access unit 201 (black characteristic amount acquisition unit), a K table memory 204 (function data storage unit), and a black generation amount calculation unit 205. This is a configuration provided. Here, the K table memory access unit 201 includes a first access unit 202 and a second access unit 203.
[K table memory 204]
The K table memory 204 stores n (n is a positive integer) one-dimensional K tables T1 to Tn. Each of these one-dimensional K tables T1 to Tn stores a plurality of black generation amounts corresponding to the MIN signal. These one-dimensional K tables T1 to Tn are all optimized in accordance with the region identification signal SEG. The one-dimensional K tables T1 to Tn are composed of a plurality of achromatic color axis black generation amount tables and a plurality of high saturation axis black generation amount tables.
[K table memory access unit 201]
The K table memory access unit 201 receives the region identification signal SEG and the MIN signal. The K table memory access unit 201 accesses the K table memory 204 and selects two one-dimensional K tables. At that time, the K table memory access unit 201 determines a one-dimensional K table to be selected based on the region identification signal SEG. More specifically, the first access unit 202 and the second access unit 203 provided in the K table memory access unit 201 both access the K table memory 204 based on the region identification signal SEG, and the optimal 1 One dimension K table is selected. Then, the first access unit 202 and the second access unit 203 read the black generation amounts K1 and K2 (first black generation amount) from the selected one-dimensional K table based on the MIN signal, respectively, and generate the black generation amount. The result is output to the calculation unit 205.

  Here, when it is determined that the region identification signal SEG is a signal representing a halftone dot region or a photographic region, the first access unit 202 and the second access unit 203 are different from the one-dimensional K tables T1 to Tn. Select a one-dimensional K table. At this time, the first access unit 202 selects the one-dimensional K table LUT1 (achromatic color axis black generation amount table) corresponding to the achromatic color region (gray region). On the other hand, the second access unit 203 selects the one-dimensional K table LUT2 (high saturation axis black generation amount table) taking the saturation component into consideration. Then, the first access unit 202 reads the black generation amount K1 from the selected one-dimensional K table LUT1 based on the MIN signal. Further, the second access unit 203 reads the black generation amount K2 from the selected one-dimensional K table LUT2 based on the MIN signal value. Therefore, in this case, the black generation amount K1 and the black generation amount K2 are the black generation amounts read from the one-dimensional K tables having different characteristics.

On the other hand, when it is determined that the region identification signal SEG is a signal representing a character region or a color blur region, the first access unit 202 and the second access unit 203 are both out of the one-dimensional K tables T1 to Tn. Select the same one-dimensional K table. At this time, both the first access unit 202 and the second access unit 203 select the same one-dimensional K table LUT1 (achromatic color axis black generation amount table) corresponding to the achromatic color region (gray region). Then, both the first access unit 202 and the second access unit 203 read the black generation amount K1 and the black generation amount K2 from the same selected one-dimensional K table LUT1 based on the MIN signal value. As a result, the black generation amount K1 and the black generation amount K2 have the same value.
[Black generation amount calculation unit 205]
The black generation amount calculation unit 205 receives the black generation amount K1, the black generation amount K2, the MIN signal, and the MAX signal. Then, the black generation amount calculation unit 205 performs an interpolation calculation shown in Expression (4) based on the input black generation amounts K1 and K2 based on the MIN signal and the MAX signal. Accordingly, the black generation amount calculation unit 205 calculates a black generation amount K ′ (second black generation amount) for the image data, and outputs the black generation amount K ′ (second black generation amount) to the spatial filter processing unit 27.

  As shown in this equation, when it is determined that the region identification signal SEG is a signal representing a halftone dot region or a photographic region, the black generation amount K ′ calculated by the black generation amount calculation unit 205 is a one-dimensional K table. Information on the black generation amount having two different characteristics, that is, the black generation amount K1 read from the LUT 1 and the black generation amount K2 read from the one-dimensional K table LUT2 is reflected. As a result, the calculated black generation amount K ′ is obtained from a so-called two-dimensional black generation table in which the relationship between the MIN signal and the MAX signal and the black generation amount is stored in a two-to-one correspondence. Is substantially equivalent. Therefore, the black generation amount calculation unit 205 performs a process comparable to the two-dimensional black generation process on the area determined as the halftone dot area or the photographic area. As a result, in a region determined to be a halftone dot region or a photographic region, an appropriate black generation process corresponding to the saturation is performed, so that the image quality is improved.

  On the other hand, when it is determined that the region identification signal SEG is a signal representing a character region or a color blur region, the black generation amount K1 and the black generation amount K2 are equal. Therefore, in this case, the expression (4) is substantially equivalent to the following expression (5).

  As described above, when it is determined that the black generation amount K1 is equal to the black generation amount K2, that is, the region identification signal SEG is a signal representing a character region or a color blur region, the black generation amount K ′ and the black generation amount K1. (Black generation amount K2) is equivalent. Therefore, the black generation amount calculation unit 205 does not substantially perform the interpolation calculation. In other words, when the black generation amount calculation unit 205 performs the interpolation calculation shown in Expression (4), if the black generation amounts K1 and K2 read by the K table memory access unit 201 have the same value, the black generation amount K ′ Is equal to the black generation amount K1. Here, the black generation amount K1 is the black generation amount read from the one-dimensional K table LUT1. Therefore, the black generation amount K ′ is equal to the black generation amount read from the one-dimensional K table LUT1. That is, the black generation amount calculation unit 205 eventually performs a one-dimensional black generation process on the area determined to be a character area or a color blur area.

  The actions and effects of the black generation amount calculation unit 200 are summarized below. When determining that the area identification signal SEG is a signal representing a character area or a color blur area, the second access unit 203 reads the black generation amount K1 from the one-dimensional K table LUT1. As described above, when the second access unit 203 reads the black generation amount K1 from the one-dimensional K table LUT1, the black generation amount calculation unit 205 performs a one-dimensional black generation process and generates black suitable for the achromatic region. Determine the amount. Therefore, the black generation amount calculation unit 205 calculates a black generation amount suitable for an achromatic color region for a character region that is an achromatic color or a color blur region that is determined to be a chromatic color but should be originally an achromatic color. decide. Thereby, the reproducibility of gray in these areas can be improved, and the amount of color material used can be reduced.

  On the other hand, when it is determined that the region identification signal SEG is a signal representing a halftone dot region or a photographic region, the second access unit 203 reads the black generation amount K2 from the one-dimensional K table LUT2. As described above, when the second access unit 203 reads the black generation amount K2 from the one-dimensional K table LUT2, the black generation amount calculation unit 205 performs a two-dimensional black generation process and takes the saturation component into consideration. Determine the amount of black produced. Therefore, the black generation amount calculation unit 205 determines the black generation amount in consideration of the saturation component for the halftone area and the photograph area. Thereby, the color reproducibility in these regions can be improved, so that the image quality can be improved.

  Further, as a result, the black generation amount calculation unit 200 selectively performs either one-dimensional or two-dimensional black generation processing based on the region identification signal SEG. That is, the black generation amount calculation unit 200 can perform either one-dimensional or two-dimensional black generation processing based on the region identification signal SEG, in other words, depending on the type of region (image characteristics). .

Accordingly, the color image processing apparatus 20 including the black generation amount calculation unit 200 can perform one-dimensional and two-dimensional black generation processing using the same hardware. Therefore, the color image processing apparatus 20 does not need to include a number of dedicated hardware for performing black generation processing of a specific dimension, can simplify the configuration of the apparatus, and can reduce the cost of the apparatus. Furthermore, since the color image processing apparatus 20 uses a one-dimensional K table, the amount of memory for storing the K table can be significantly reduced as compared with the case where a two-dimensional K table is used.
[Black generation amount calculation unit 300]
As shown in FIG. 16, the object of the present invention is to perform a process of reading the black generation amount from one one-dimensional K table in parallel with the process of the configuration of FIG. This may be achieved by the black generation amount calculation unit 300 that selectively outputs one of the two black generation amounts.

In this case, the black generation amount calculation unit 300 is roughly configured by a two-dimensional black generation amount calculation unit 301, a one-dimensional black generation amount calculation unit 302, a K table memory 307, and an output selection unit 309. Here, the K table memory access unit 303, the black generation amount calculation unit 308, and the K table memory 307, which are included in the two-dimensional black generation amount calculation unit 301 and include the first access unit 304 and the second access unit 305, are illustrated in FIG. 15 is the same as the K table memory access unit 201, the black generation amount calculation unit 205, and the K table memory 204 including the first access unit 202 and the second access unit 203 shown in FIG. In FIG. 16, the calculation result of the black generation amount calculation unit 308 is K3.
[One-dimensional black generation amount calculation unit 302]
The one-dimensional black generation amount calculation unit 302 performs one-dimensional black generation processing, and the third access unit 306 accesses the K table memory 307 to obtain a one-dimensional K table LUT1 corresponding to the achromatic color characteristic. select. Then, the third access unit 306 reads the black generation amount K4 from the one-dimensional K table LUT1 based on the MIN signal, and outputs it to the output selection unit 309. As described above, the black generation amount K4 calculated by the one-dimensional black generation amount calculation unit 302 is a black generation amount read based on the MIN signal from the one-dimensional K table LUT1, and thus is obtained by one-dimensional black generation processing. It is.
[Output Selection Unit 309]
The output selection unit 309 receives the black generation amount K3, the black generation amount K4, and the region identification signal SEG. The output selection unit 309 selects one of the input black generation amounts K3 and K4 based on the region identification signal SEG, and sets this as the black generation amount K ′ for the image data to the spatial filter processing unit 27. Output.

For example, when it is determined that the region identification signal SEG is a signal representing a character region or a color blur region, the output selection unit 309 selects the black generation amount K4 as the black generation amount K ′, while the region identification signal SEG represents When it is determined that the area is a halftone dot area or a photograph area, the output selection unit 309 selects and outputs the black generation amount K3 as the black generation amount K ′.
[Hue determination signal]
The black generation amount calculation unit (under color removal amount calculation unit) that uses the one-dimensional K table described above uses an optimal one-dimensional K table based on a hue determination signal that represents the hue of image data. May be. This example will be described below.

  In this case, the K table memory stores, as a one-dimensional K table, one gray-axis one-dimensional K table corresponding to the gray area and a plurality of high-saturation axis one-dimensional K tables corresponding to each hue. . The color image processing apparatus 20 further includes a hue determination unit that determines the hue of the image data.

  A CMY signal of each pixel is input to the hue determination unit. Then, the hue determination unit compares the sizes of the input CMY and selects two hues that are close to the previously divided hues. Then, the hue determination unit outputs a hue determination signal representing the selected hue. Here, as a hue dividing method, there are three methods of selecting two from among CMY and a method of dividing into three, and two methods of selecting two from among CMYRGB.

  Next, based on the hue determination signal, the black generation amount calculation unit firstly reads the black generation amount read from the high saturation axis K table of the two selected hues, the black generation amount read from the gray axis K table, and the MIN signal. And the MAX signal, a black generation amount for each hue is obtained by some interpolation calculation. Then, the black generation amount calculation unit uses the positional relationship between the two selected hues and the image data and the black generation amount for each hue calculated by the interpolation calculation to perform black interpolation on the image data by another interpolation calculation. Find the amount of production.

In this way, when calculating the black generation amount of each hue, the one-dimensional K table can be switched based on the hue determination signal.
[Black generation amount calculation unit 400]
The object of the present invention is to use a so-called two-dimensional black generation table in which the relationship between the MIN signal and the MAX signal and the black generation amount is stored in a two-to-one correspondence as shown in FIG. This can also be achieved by the generation amount calculation unit 400. Therefore, the configuration and processing of the black generation amount calculation unit 400 will be described in detail below with reference to FIGS.

FIG. 17 is a block diagram illustrating the configuration of the black generation amount calculation unit 400 according to another embodiment of the present invention. According to this figure, the black generation amount calculation unit 400 includes a signal selection unit 401 (parameter selection unit), a K table memory 402 (function data storage unit), and a K table memory access unit 403 (black characteristic amount acquisition unit). It is the structure provided with.
[Signal Selection Unit 401]
The signal selection unit 401 receives the MAX signal, the MIN signal, and the region identification signal SEG. Here, the signal selection unit 401 selects either the input MIN signal (first parameter) or the MAX signal. Specifically, the signal selection unit 401 outputs either the MAX signal or the MIN signal to the K table memory access unit 403 as the selection signal SIG based on the region identification signal SEG. For example, when the region identification signal SEG is determined to be a signal representing a character region or a color blur region, the signal selection unit 401 outputs a MIN signal to the K table memory access unit 403 as the selection signal SIG. On the other hand, when it is determined that the region identification signal SEG is a region representing a halftone dot region or a photograph region, the signal selection unit 401 outputs a MAX signal to the K table memory access unit 403 as the selection signal SIG.
[K table memory 402]
The K table memory 402 stores n (n is a positive integer) number of two-dimensional K tables D1 to Dn. These two-dimensional K tables D1 to Dn are all optimized in advance corresponding to the region identification signal SEG. More specifically, each of the two-dimensional K tables D1 to Dn stores a plurality of black generation amounts corresponding to the two-dimensional grid points having the MIN signal and the selection signal SIG as coordinates. In each of the two-dimensional K tables D1 to Dn, the black generation amount suitable for the achromatic color region is stored at the lattice point where the MIN signal and the selection signal SIG are equal.
[K table memory access unit 403]
The K table memory access unit 403 receives the region identification signal SEG, the MIN signal, and the selection signal SIG. Here, the K table memory access unit 403 accesses the K table memory 402 and reads one black generation amount. More specifically, the K table memory access unit 403 first accesses the K table memory 402 and selects one optimum two-dimensional K table based on the region identification signal SEG.

  At this time, when the selection signal SIG is a MAX signal, the K table memory access unit 403 uses a lattice corresponding to the coordinates of the MIN signal and the MAX signal (SIG) from the selected two-dimensional K table as shown in FIG. One black generation amount K ′ stored at the position of the point is read, and this is output as a black generation amount for the image data to the spatial filter processing unit 27. Here, as described above, when the region identification signal SEG is a signal representing a halftone dot region or a photographic region, the selection signal SIG is a MAX signal. As a result, the K table memory access unit 403 performs a two-dimensional black generation process on the halftone dot area or the photographic area. Therefore, the black generation amount calculation unit 400 determines a black generation amount that takes the saturation component into consideration for the halftone dot region and the photographic region. Thereby, the color reproducibility in these regions can be improved, so that the image quality can be improved.

  On the other hand, as described above, when the region identification signal SEG is a signal representing a character region or a color blur region, the selection signal SIG is a MIN signal. As a result, the K table memory access unit 403 performs a one-dimensional black generation process on the character area or the color blur area. Therefore, the black generation amount calculation unit 400 determines a black generation amount suitable for an achromatic color region for a character region that is an achromatic color or a color blur region that is a chromatic color but should be originally an achromatic color. . Thereby, the reproducibility of gray in these areas can be improved.

As described above, the K table memory access unit 403 can use the two-dimensional K table as a one-dimensional or two-dimensional K table based on the region identification signal SEG. Therefore, the black generation amount calculation unit 400 can switch between one-dimensional and two-dimensional black generation processing based on the region identification signal SEG, in other words, according to the type of region (image characteristics). Thereby, the color image processing apparatus 20 performs both the determination of the black generation amount suitable for the achromatic color region and the determination of the black generation amount taking the saturation component into consideration, that is, one-dimensional and two-dimensional black generation processing. You can do both. In the color image processing apparatus, it is not necessary to separately store the one-dimensional K table for the achromatic color region and the two-dimensional K table taking the saturation component into memory or the like. Further, in the color image processing apparatus 20, it is not necessary to provide the black generation amount calculation unit 400 separately for the achromatic color region and the case where the saturation component is taken into consideration. Therefore, the color image processing apparatus also has the effect of reducing memory resources and simplifying the apparatus configuration.
[Other examples of characteristic signals]
Note that the black generation amount calculation units 44 to 400 described above may perform black generation processing based on characteristic signals representing other characteristics of the input image instead of the region identification signal SEG. For example, instead of the area identification signal SEG, a characteristic signal indicating the document type or the image mode may be input to the black generation amount calculation units 44 to 400. In this case, the black generation amount calculation units 44 to 400 generate one-dimensional and two-dimensional blacks according to the type of input document and the image mode (character document mode, character / photo mode, etc.) input from the operation panel. Processing can be performed selectively. More specifically, according to the document type or the image mode, for example, the signal selection unit switches the signal to be selected as the selection signal SIG, or the K table memory access unit 104 switches the type of the K table. Can do.
[Parameter generation means]
In the present embodiment, the maximum value / minimum value calculation unit 41 has been described as an example of parameter generation means. However, the parameter generation means is not limited to the maximum value / minimum value calculation unit 41. That is, the parameter generation unit may be any unit that generates the first and second parameters from the pixel values included in the image data. For example, when the pixel included in the image represented by the image data is composed of three types of color components C (cyan), M (magenta), and Y (yellow), the parameter generation unit may determine the amount of these color components included in the image data. Based on the above, the first and second parameters may be generated.

Further, as described above, the image represented by the image data processed by the color image processing apparatus is composed of a plurality of color components. The lightness, hue, and saturation of the image represented by the image data change according to the density ratio of these color components. Therefore, the parameter generation means does not simply generate the first and second parameters, but generates these parameters as variables reflecting the achromatic color characteristic and the chromatic color characteristic of the image data, respectively. That is, the parameter generation unit generates different first and second parameters according to the color characteristics of the image represented by the image data. For example, the parameter generation means may obtain an average value or median value of the input CMY signals and output this as the first parameter instead of the MIN signal.
[Function data]
In the present embodiment, an example in which the K table is included in the K table memories 104 to 402 has been described. However, the K table memory 103 may store “function data” in which the relationship between the first parameter generated by the parameter generation unit and the black characteristic amount is determined in advance. This function data is data representing a function for specifying and outputting a black characteristic amount corresponding to the input first parameter by some method. This function data can be, for example, a black characteristic amount table in which the first parameter and the black characteristic amount are stored in a one-to-one relationship. The function data can also be mathematical formula data that returns a black characteristic amount by performing a predetermined calculation based on the input first parameter.

  Further, the K table memory 402 stores “binary function data” in which the relationship between the first and second parameters generated by the parameter generation unit and the black characteristic amount taking the saturation component into consideration is predetermined. May be. The binary function data is data representing a function for specifying and outputting a black characteristic amount corresponding to the input first and second parameters by some method. Further, in this binary function data, a portion where the first parameter and the second parameter are equal is determined in advance with a black characteristic amount suitable for the achromatic region based on the relationship between the first parameter and the black characteristic amount. The determined one-way function data may be used.

The binary function data is, for example, a two-dimensional black characteristic amount table in which the first and second parameters and the black characteristic amount taking the saturation component into account are stored in a two-to-one relationship. be able to. In this case, a part of the binary function data is used as a one-dimensional black characteristic amount table in which the first parameter and the black characteristic amount suitable for the achromatic region are stored in a one-to-one relationship. become. Further, the binary function data returns a black characteristic amount taking the saturation component into consideration by performing a predetermined calculation based on the first and second parameters, while the first and second parameters are In the case of equality, it is also possible to use mathematical formula data such that the returned value is a black characteristic amount suitable for the achromatic region.
[Other possible configurations]
The image processing apparatus of the present invention is an image processing apparatus that performs black generation and undercolor removal processing on image data composed of a plurality of color components, and is based on a characteristic signal that represents characteristics of the image data composed of a plurality of color components. A signal selection unit that selects any one parameter from a plurality of parameters obtained from the image data, and a black generation amount storage unit (K table memory) that stores a black generation amount group corresponding to the characteristics of the image data. A black generation amount selection unit (K memory access unit) that selects a corresponding black generation amount group based on the characteristic signal, and a predetermined value obtained from the image data from the selected plurality of black generation amount groups. A plurality of first black generation amounts (black generation amount K1 and black generation amount K2) read based on the received parameters (MIN signal), and the parameter (M) selected by the signal selection unit (X signal or MIN signal) and a predetermined parameter (MIN signal) obtained from the image data, a black generation amount calculation unit that calculates a second black generation amount (K) for image data composed of a plurality of color components It can also be configured as an image processing apparatus characterized by comprising

  In the image processing apparatus of the present invention, when the characteristic signal is an area identification signal and the area identification signal is a character area or a blur area, the signal selection unit selects a MIN signal which is a parameter obtained from image data. In the case where the area identification signal is a halftone dot area or a photographic area, the signal selection unit can select a MAX signal that is a parameter obtained from the image data.

  The image processing apparatus of the present invention is an image processing apparatus that performs black generation and undercolor removal processing on image data consisting of a plurality of color components, and is based on a characteristic signal that represents the characteristics of the image data consisting of a plurality of color components. A signal selection unit that selects any one parameter from a plurality of parameters obtained from the image data, and a black generation amount storage unit (K table memory) that stores a black generation amount group corresponding to the characteristics of the image data. And a characteristic signal of the image data, one parameter (MIN signal) among a plurality of parameters obtained from the image data, and a parameter (MAX signal or MIN signal) selected by the signal selection unit. And a black generation amount selection unit for determining a black generation amount for image data composed of a plurality of color components. Rukoto can also.

  The image processing apparatus of the present invention is an image processing apparatus that performs black generation and undercolor removal processing on image data consisting of a plurality of color components, and is based on a characteristic signal that represents the characteristics of the image data consisting of a plurality of color components. A signal selection unit that selects any one of a plurality of parameters obtained from the image data, a lower color removal amount storage unit that stores a lower color removal amount group according to the characteristics of the image data, One of a plurality of parameters obtained from the image data from the undercolor removal amount selection unit that selects a corresponding undercolor removal amount group based on the characteristic signal, and the plurality of selected undercolor removal amount groups. A lower color for calculating a second lower color removal amount for image data composed of a plurality of color components using a plurality of first under color removal amounts read based on the image and a parameter selected by the signal selection unit Providing the removed by amount calculation unit may be configured as an image processing apparatus according to claim.

  The image processing apparatus of the present invention is an image processing apparatus that performs black generation and undercolor removal processing on image data consisting of a plurality of color components, and is based on a characteristic signal that represents the characteristics of the image data consisting of a plurality of color components. A signal selection unit that selects any one parameter from a plurality of parameters obtained from the image data, an under color removal amount storage unit that stores a black generation amount group corresponding to the characteristics of the image data, and the image Using the characteristic signal of data, one parameter among a plurality of parameters obtained from the image data, and the parameter selected by the signal selection unit, the under color removal amount for the image data composed of a plurality of color components It is also possible to configure as an image processing apparatus including a lower color removal amount selection unit for obtaining the above.

  The image processing method of the present invention is an image processing method for performing black generation and undercolor removal processing on image data composed of a plurality of color components, and is based on a characteristic signal representing the characteristics of the image data composed of a plurality of color components. A signal selection step of selecting any one parameter from a plurality of parameters obtained from the image data, and a black generation amount storage unit (K table memory) for storing a black generation amount group corresponding to the characteristics of the image data Thus, a black generation amount selection step for selecting a corresponding black generation amount group based on the characteristic signal, and a predetermined parameter (MIN signal) obtained from the image data from the selected plurality of black generation amount groups. ) And a plurality of first black generation amounts (black generation amount K1 and black generation amount K2) read based on the parameter selection parameter (MAX signal or M And a black generation amount calculation step of calculating a second black generation amount (K) for image data composed of a plurality of color components using a predetermined parameter (MIN signal) obtained from the N data) and image data. The image processing method can also be characterized.

  In the image processing method of the present invention, when the characteristic signal is an area identification signal and the area identification signal is a character area or a blur area, a MIN signal which is a parameter obtained from image data by the signal selection unit is selected. When the area identification signal is a halftone area or a photographic area, it is preferable to select a MAX signal that is a parameter obtained from image data by the signal selection unit.

  The image processing method of the present invention is an image processing method for performing black generation and undercolor removal processing on image data composed of a plurality of color components, and is based on a characteristic signal representing the characteristics of the image data composed of a plurality of color components. A signal selection step of selecting any one parameter from a plurality of parameters obtained from the image data, and a black generation amount storage unit (K table memory) for storing a black generation amount group corresponding to the characteristics of the image data Accordingly, the characteristic signal of the image data, one parameter (MIN signal) among a plurality of parameters obtained from the image data, and the parameter (MAX signal or MIN signal) selected by the signal selection step are used. And a black generation amount selection step for obtaining a black generation amount for image data composed of a plurality of color components. It may be.

  The image processing method of the present invention is an image processing method for performing black generation and undercolor removal processing on image data composed of a plurality of color components, and is based on a characteristic signal representing the characteristics of the image data composed of a plurality of color components. The signal selection step of selecting any one parameter from a plurality of parameters obtained from the image data, and the under color removal amount storage unit for storing the under color removal amount group corresponding to the characteristics of the image data, One of a plurality of parameters obtained from the image data from the undercolor removal amount selection step of selecting a corresponding undercolor removal amount group based on the characteristic signal and the selected plurality of undercolor removal amount groups. The second undercolor removal amount for the image data composed of a plurality of color components is calculated using the plurality of first undercolor removal amounts read based on the image and the parameters selected by the signal selection unit. It can be configured as an image processing method characterized by comprising the under color removal amount calculation step.

  The image processing method of the present invention is an image processing method for performing black generation and undercolor removal processing on image data composed of a plurality of color components, and is based on a characteristic signal representing the characteristics of the image data composed of a plurality of color components. The signal selection step of selecting any one parameter from a plurality of parameters obtained from the image data, and the under color removal amount storage unit for storing the under color removal amount group corresponding to the characteristics of the image data, Using the characteristic signal of the image data, one parameter among a plurality of parameters obtained from the image data, and the parameter selected by the signal selection step, the under color removal for the image data composed of a plurality of color components The image processing method can also be configured to include an under color removal amount selection step for obtaining the amount.

  The image processing apparatus according to the present invention is an image processing apparatus that performs black generation and lower color removal processing on image data including a plurality of color components, and generates a black amount corresponding to characteristics of the image data including the plurality of color components. A black generation amount storage unit (K table memory) for storing a group, and a black generation amount selection unit (K memory) for selecting a corresponding black generation amount group based on a characteristic signal representing characteristics of image data composed of a plurality of color components A plurality of first black generation amounts (black generation amount K1 · black generation amount) read based on the first parameter (MIN signal) obtained from the image data from the selected plurality of black generation amount groups. A black generation amount calculation unit that calculates a second black generation amount (K) for image data including a plurality of color components using K2) and a second parameter (MAX signal) obtained from the image data. It can be configured as an image processing apparatus according to claim.

  In the image processing apparatus according to the aspect of the invention, it is preferable that the black generation amount selection unit selects the same black generation amount group according to the characteristic signal.

  The image processing apparatus according to the present invention is an image processing apparatus that performs black generation and under color removal processing on image data composed of a plurality of color components, and removes the under color corresponding to the characteristics of the image data composed of the plurality of color components. Under color removal amount storage unit (UCR table memory) for storing amount groups, and under color removal amount selection for selecting a corresponding under color removal amount group based on a characteristic signal representing the characteristics of image data composed of a plurality of color components Section (UCR memory access section) and a plurality of first under color removal amounts (UCR1...) Read out based on the first parameter (MIN signal) obtained from the image data from the selected plurality of under color removal amount groups. UCR2) and a second parameter (MAX signal) obtained from the image data, undercolor removal for calculating a second undercolor removal amount (UCR) for image data composed of a plurality of color components. Providing the calculation unit may be configured as characterized.

  In the image processing apparatus according to the aspect of the invention, it is preferable that the under color amount selection unit selects the same under color removal amount group according to the characteristic signal.

  Further, the image processing method of the present invention is a black generation amount corresponding to characteristics of image data consisting of a plurality of color components in an image processing method for performing black generation and under color removal processing on image data consisting of a plurality of color components. A black generation amount selection step of selecting a corresponding black generation amount group based on a characteristic signal representing characteristics of image data composed of a plurality of color components from a black generation amount storage unit (K table memory) for storing the group; A plurality of first black generation amounts (black generation amount K1 and black generation amount K2) read out based on a first parameter (MIN signal) obtained from the image data from a plurality of selected black generation amount groups, and the image An image comprising a black generation amount calculation step of calculating a second black generation amount (K) for image data composed of a plurality of color components using a second parameter (MAX signal) obtained from the data. It can be configured as a physical method.

  In the image processing method of the present invention, it is preferable that the black generation amount selection step selects the same black generation amount group according to the characteristic signal.

  Also, the image processing method of the present invention is an image processing method for performing black generation and under color removal processing on image data consisting of a plurality of color components, and under color removal corresponding to the characteristics of the image data consisting of a plurality of color components. Under color removal amount selection unit that selects a corresponding under color removal amount group based on a characteristic signal representing the characteristics of image data composed of a plurality of color components from a under color removal amount storage unit (UCR table memory) that stores the amount group. A plurality of first under color removal amounts (UCR1, UCR2) read out from the selected plurality of under color removal amount groups based on a first parameter (MIN signal) obtained from the image data, and the image A lower color removal amount calculation step of calculating a second lower color removal amount (UCR) for image data including a plurality of color components using a second parameter (MAX signal) obtained from the data; It can be configured as an image processing method characterized.

  In the image processing method of the invention, it is preferable that the under color amount selection step selects the same under color removal amount group according to the characteristic signal.

  The image processing method of the present invention can be realized as software (application program). In this case, a printer driver incorporating software for realizing the black generation and under color removal process can be provided in the computer.

  As shown in FIG. 20, a printer 100, a communication port driver 120, and a communication port 130 are incorporated in a computer 100 according to the present invention. The printer driver 110 includes a color correction unit 111, a black generation and under color removal unit 112, a gradation reproduction processing unit 113, and a printer language translation unit 114. The color correction unit 111 and the gradation reproduction processing unit 113 perform the same processing as the color correction unit 25 and the gradation reproduction processing unit 29 shown in FIG. The black generation and under color removal unit 112 performs the same processing as the black generation and under color removal unit described with reference to FIGS. 1 and 4 to 14 and the like.

  The computer 100 is connected to a printer (image output device) 150, and the printer 150 outputs an image in accordance with image data output from the computer 100.

  Image data generated by executing various application programs in the computer 100 is subjected to the above-described processing by the color correction unit 111, the black generation and under color removal unit 112, and the gradation reproduction processing unit 113. The image data subjected to the above processing is converted into a printer language by the printer language translation unit 114 and input to the printer 150 via the communication port driver 120 and the communication port 130 (for example, RS232C / LAN). The printer 150 may be a digital complex machine having a copy function and a fax function in addition to the printer function.

  The present invention also records a one-dimensional K (UCR) table and an image processing method for performing black generation and undercolor removal processing by interpolation calculation on a computer-readable recording medium on which a program to be executed by a computer is recorded. Can also be provided. As a result, a recording medium on which a one-dimensional K (UCR) table and a program for performing an image processing method for performing black generation / undercolor removal processing by interpolation calculation can be provided in a portable manner. Alternatively, the recording medium can be provided as a recording of a two-dimensional K (UCR) table and an image processing method for performing black generation and undercolor removal processing. As a result, a recording medium on which a two-dimensional K (UCR) table and an image processing method for performing black generation and undercolor removal processing are recorded can be provided in a portable manner.

  Here, the recording medium for recording the program or the like may be a program medium such as a memory (not shown) such as a ROM because processing is performed by the microcomputer. Alternatively, the recording medium may be a program medium provided with a program reading device as an external storage device (not shown) and readable by inserting the recording medium therein.

  In any case, the stored program may be configured to be accessed and executed by the microprocessor. Alternatively, the stored program may be a system in which the read program is downloaded to a program storage area (not shown) of the microcomputer and the program is executed by reading the program. In this case, it is assumed that the download program is stored in the main device in advance.

  Here, the above-described program medium is a recording medium configured to be separable from the main body. That is, the program medium includes a tape system such as a magnetic tape and a cassette tape, a magnetic disk such as a floppy (registered trademark) disk and a hard disk, and an optical disk such as a CD-ROM / MO / MD / DVD, an IC card (memory card). / A card system such as an optical card, or a mask ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), and a fixed program including a semiconductor memory such as a flash ROM It may be a medium.

  In this case, the recording medium may be a medium that can be connected to a communication network including the Internet and that carries the program in a fluid manner so as to download the program from the communication network. When downloading the program from the communication network in this way, the download program may be stored in the main device in advance or installed from another recording medium.

  The above-described image processing method is executed by reading the recording medium described above by a program reading device provided in a digital color image forming apparatus or a computer system.

  The above-described computer system includes an image input device such as a flatbed scanner, a film scanner, and a digital camera, a computer that performs various processes such as the image processing method by loading a predetermined program, and computer processing results. An image display device such as a CRT display or liquid crystal display for display and a printer for outputting the processing results of the computer to paper are included. Furthermore, the computer system is provided with a network card, a modem, and the like as communication means for connecting to a server or the like via a network.

  In addition, this invention is not limited to embodiment mentioned above, A various change is possible in the range shown to the claim. That is, embodiments obtained by combining technical means appropriately modified within the scope of the claims are also included in the technical scope of the present invention.

  The image processing apparatus according to the present invention performs appropriate black generation processing (under color removal processing) according to the type of document on input image data, particularly one-dimensional and two-dimensional black using the same hardware and memory. Since any one of the generation processes (under color removal processes) can be selectively performed, the present invention can be applied to uses such as a color copying machine and a color printer that perform image output using a K (black) color material.

1 is a block diagram illustrating a main configuration of a black generation amount calculation unit according to an embodiment of the present invention. 1 is a block diagram illustrating a configuration of an image forming apparatus to which a color image processing apparatus is applied. It is a block diagram which shows the structure of an area | region separation process part. It is a block diagram which shows the structure of a black production | generation undercolor removal part. It is a block diagram which shows an example of a structure of a blurring process part. It is a figure which shows an example of a structure of K table memory. Concept of a method in which a black generation amount calculation unit calculates a black generation amount K ′ for image data by performing two-dimensional black generation processing by interpolation calculation from two black generation amounts read from two one-dimensional K tables. FIG. Concept of a method in which a black generation amount calculation unit calculates a black generation amount K ′ for image data by performing two-dimensional black generation processing by interpolation calculation from two black generation amounts read from two one-dimensional K tables. FIG. When the MIN signal is the selection signal SIG, the black generation amount calculation unit uses the two-dimensional black generation processing by interpolation calculation from the black generation amounts read from the two one-dimensional K tables. FIG. 6 is a diagram illustrating a concept of a method for calculating a black generation amount K ′ for image data by obtaining a result equivalent to the above. When the MIN signal is the selection signal SIG, the black generation amount calculation unit uses the two-dimensional black generation processing by interpolation calculation from the black generation amounts read from the two one-dimensional K tables. FIG. 6 is a diagram illustrating a concept of a method for calculating a black generation amount K ′ for image data by obtaining a result equivalent to the above. It is a flowchart which shows the flow of the whole process in a black generation amount calculation part. It is a flowchart which shows the flow of a color blurring process. It is a flowchart which shows an example of the flow of a black generation amount calculation process. It is a flowchart which shows an example of the flow of an under color removal amount calculation process. It is a block diagram which shows other embodiment of this invention and shows the structure of a black generation amount calculation part. It is a block diagram which shows other embodiment of this invention and shows the structure of a black generation amount calculation part. It is a block diagram which shows other embodiment of this invention and shows the structure of a black generation amount calculation part. It is a figure showing the concept of the method of calculating a black generation amount from a two-dimensional K table in a black generation amount calculation part. It is a figure showing the concept of the method of using a part of 2D K table as a 1D K table in a black generation amount calculation part. FIG. 3 is a block diagram illustrating a configuration of an image forming apparatus of an example different from FIG. 2 to which a color image processing apparatus according to the present invention is applied.

Explanation of symbols

24 region separation processing unit 31 region separation unit 32 color blur determination unit 33 chromatic color determination unit 34 edge extraction processing unit 35 neighborhood pixel determination unit 41 maximum value / minimum value calculation unit (parameter generation means)
42 Blur processing unit 43 Under color removal amount calculation unit 44 Black generation amount calculation unit (black characteristic amount determination means)
45 Under color removal processing unit 51 Average value calculation unit 52 Bleed signal selection unit 60, 82, 84 Straight line 80 Graph 101 Signal selection unit (parameter selection means)
102 Black generation unit 103 K table memory (function data storage unit)
104 K table memory access unit (black characteristic amount acquisition means)
105 Black generation amount calculation unit 201 K table memory access unit (black characteristic amount acquisition means)
202 1st access part (1st black characteristic amount acquisition means)
203 2nd access part (2nd black characteristic quantity acquisition means)
204 K table memory (function data storage)
205 Black generation amount calculation unit 301 Two-dimensional black generation amount calculation unit 302 One-dimensional black generation amount calculation unit 303 K table memory access unit (black characteristic amount acquisition unit)
304 first access unit 305 second access unit 306 third access unit 307 K table memory (function data storage unit)
308 Black generation amount calculation unit 309 Output selection unit 401 Signal selection unit (parameter selection means)
402 K table memory (function data storage)
403 K table memory access unit (black characteristic amount acquisition means)

Claims (13)

In an image processing apparatus that performs black generation processing or undercolor removal processing by using a black characteristic amount for image data representing an image composed of a plurality of color components,
Parameter generation means for generating, from pixel values included in the image data, a first parameter reflecting the achromatic characteristic of the image and a second parameter reflecting the chromatic characteristic of the image;
Parameter selection means for selecting the first or second parameter based on a predetermined criterion and outputting it as a selection parameter;
Based on the first parameter and the selection parameter, the black characteristic amount to be applied to the image data is determined from binary function data that defines the relationship between the first and second parameters and the black characteristic amount. A characteristic amount determining means,
The parameter selection means uses the characteristic of the image as the predetermined reference, selects either the first parameter or the second parameter based on a characteristic signal representing the characteristic,
The binary function data takes into account the first function data in which the relationship between the first parameter and the black characteristic amount suitable for the achromatic region is predetermined, the first parameter, and the saturation component. It consists of second function data that has a predetermined relationship with the black characteristic amount,
Based on the first parameter, the first black characteristic amount suitable for the achromatic region is acquired from the first function data, and the first black characteristic amount based on the first parameter is obtained from the second function data. A black characteristic amount acquisition means for acquiring a second black characteristic amount taking into account the degree component;
The black characteristic amount determining means performs an interpolation operation based on the first parameter and the selection parameter selected by the parameter selecting means from the acquired first and second black characteristic amounts. An image processing apparatus for obtaining a black characteristic amount to be applied to the image data. In an image processing apparatus that performs black generation processing or undercolor removal processing by using a black characteristic amount for image data representing an image composed of a plurality of color components,
Parameter generation means for generating, from pixel values included in the image data, a first parameter reflecting the achromatic characteristic of the image and a second parameter reflecting the chromatic characteristic of the image;
Parameter selection means for selecting the first or second parameter based on a predetermined criterion and outputting it as a selection parameter;
Based on the first parameter and the selection parameter, the black characteristic amount to be applied to the image data is determined from binary function data that defines the relationship between the first and second parameters and the black characteristic amount. A characteristic amount determining means ,
The parameter selection means uses the characteristic of the image as the predetermined reference, selects either the first parameter or the second parameter based on a characteristic signal representing the characteristic,
The binary function data is a two-dimensional lookup table associating black characteristic quantities with the first and second parameters.
The black characteristic amount determining unit obtains a black characteristic amount to be applied to image data from the two-dimensional lookup table based on the first parameter and the selection parameter selected by the parameter selecting unit. A featured image processing apparatus. In an image processing apparatus that performs black generation processing or undercolor removal processing by using a black characteristic amount for image data representing an image composed of a plurality of color components,
Parameter generation means for generating, from pixel values included in the image data, a first parameter reflecting the achromatic characteristic of the image and a second parameter reflecting the chromatic characteristic of the image;
Based on the first function data, the first black characteristic amount suitable for the achromatic region is obtained from the first function data in which the relationship between the first parameter and the black characteristic amount suitable for the achromatic region is determined in advance. First black characteristic amount acquisition means for acquiring;
The function data is selected based on a predetermined criterion from the second function data in which the relationship between the first parameter and the black characteristic amount considering the saturation component is determined in advance, or the first function data, Second black characteristic quantity acquisition means for acquiring a second black characteristic quantity from the selected function data based on the first parameter;
A black characteristic for obtaining a black characteristic amount to be applied to the image data by performing an interpolation operation based on the first parameter and the second parameter from the acquired first and second black characteristic amounts. A quantity determining means ,
The second black characteristic amount acquisition means uses the characteristic of the image as the predetermined reference, and based on the characteristic signal representing the characteristic, the second black characteristic amount acquisition means calculates the second black characteristic amount from the first or second function data. An image processing apparatus characterized by acquiring a characteristic amount. Each of the binary function data includes a plurality of different function data corresponding to the characteristics of the image,
A function data storage unit that stores the plurality of function data in association with a characteristic signal representing the characteristic;
2. The black characteristic amount acquisition unit acquires the black characteristic amount from the binary function data corresponding to the characteristic signal in the function data storage unit based on the characteristic signal. Image processing apparatus. Each of the first and second function data is composed of a plurality of different function data corresponding to the characteristics of the image, and the function data stores the plurality of function data in association with a characteristic signal representing the characteristics. A storage unit,
The first black characteristic amount acquisition means acquires the first black characteristic amount from function data corresponding to the characteristic signal in the first function data based on the characteristic signal, and the second black characteristic amount acquisition means. Based on the characteristic signal, the black characteristic amount obtaining means obtains the second data from the function data corresponding to the characteristic signal in the second function data or the function data corresponding to the characteristic signal in the first function data. The image processing apparatus according to claim 3 , wherein a black characteristic amount is acquired. The characteristic signal is an area identification signal representing a type of an area including at least one of a character area, a color blur area, a halftone dot area, and a photographic area to which each pixel or pixel group included in the image belongs.
The parameter selection means is
If it is determined that the region identification signal is a signal representing a character region or a color blur region, the first parameter is selected as the selection parameter,
If it is determined that the region identification signal is a signal representing a halftone region or a photograph region, according to claim 1, 2 or 4, selects the second parameter, characterized in that the said selection parameters Image processing apparatus. The characteristic signal is an area identification signal representing a type of an area including at least one of a character area, a color blur area, a halftone dot area, and a photographic area to which each pixel or pixel group included in the image belongs.
The second black characteristic amount acquisition means includes:
When it is determined that the region identification signal is a signal representing a character region or a color blur region, the second black characteristic amount is acquired from the first function data,
If it is determined that the region identification signal is a signal representing a halftone region or a photograph region, according to claim 3 or 5, characterized in that to obtain the second black characteristic quantity from said second function data Image processing apparatus. An image processing method for generating a black characteristic amount in an image processing apparatus that performs black generation processing or undercolor removal processing using black characteristic amount for image data representing an image composed of a plurality of color components,
A parameter generation step for generating a first parameter reflecting the achromatic color characteristic of the image and a second parameter reflecting the chromatic color characteristic of the image from pixel values included in the image data;
A parameter selection step of selecting the first or second parameter based on a predetermined criterion and outputting it as a selection parameter;
Based on the first parameter and the selection parameter, the black characteristic amount to be applied to the image data is determined from binary function data that defines the relationship between the first and second parameters and the black characteristic amount. A characteristic amount determination step,
In the parameter selection step, the characteristic of the image is used as the predetermined reference, and either the first parameter or the second parameter is selected based on a characteristic signal representing the characteristic,
The binary function data takes into account the first function data in which the relationship between the first parameter and the black characteristic amount suitable for the achromatic region is predetermined, the first parameter, and the saturation component. It consists of second function data that has a predetermined relationship with the black characteristic amount,
Based on the first parameter, the first black characteristic amount suitable for the achromatic region is acquired from the first function data, and the first black characteristic amount based on the first parameter is obtained from the second function data. A black characteristic amount acquisition step of acquiring a second black characteristic amount taking into account the degree component;
In the black characteristic amount determination step, by performing an interpolation operation based on the first parameter and the selection parameter selected in the parameter selection step from the acquired first and second black characteristic amounts. An image processing method characterized by obtaining a black characteristic amount to be applied to the image data. An image processing method for generating a black characteristic amount in an image processing apparatus that performs black generation processing or undercolor removal processing using black characteristic amount for image data representing an image composed of a plurality of color components,
A parameter generation step for generating a first parameter reflecting the achromatic color characteristic of the image and a second parameter reflecting the chromatic color characteristic of the image from pixel values included in the image data;
A parameter selection step of selecting the first or second parameter based on a predetermined criterion and outputting it as a selection parameter;
Based on the first parameter and the selection parameter, the black characteristic amount to be applied to the image data is determined from binary function data that defines the relationship between the first and second parameters and the black characteristic amount. A characteristic amount determination step,
In the parameter selection step, the characteristic of the image is used as the predetermined reference, and either the first parameter or the second parameter is selected based on a characteristic signal representing the characteristic,
The binary function data is a two-dimensional lookup table associating black characteristic quantities with first and second parameters,
In the black characteristic amount determination step, obtaining a black characteristic amount to be applied to the image data from the two-dimensional lookup table based on the first parameter and the selection parameter selected in the parameter selection step. A featured image processing method. An image processing method for generating a black characteristic amount in an image processing apparatus that performs black generation processing or undercolor removal processing using black characteristic amount for image data representing an image composed of a plurality of color components,
A parameter generation step for generating a first parameter reflecting the achromatic color characteristic of the image and a second parameter reflecting the chromatic color characteristic of the image from pixel values included in the image data;
Based on the first function data, the first black characteristic amount suitable for the achromatic region is obtained from the first function data in which the relationship between the first parameter and the black characteristic amount suitable for the achromatic region is determined in advance. A first black characteristic amount acquisition step to be acquired;
The function data is selected based on a predetermined criterion from the second function data in which the relationship between the first parameter and the black characteristic amount taking the saturation component into consideration is predetermined or from the first function data A second black characteristic amount acquisition step for acquiring a second black characteristic amount from the selected function data based on the first parameter;
A black characteristic for obtaining a black characteristic amount to be applied to the image data by performing an interpolation operation based on the first parameter and the second parameter from the acquired first and second black characteristic amounts. and the amount determined step seen including,
In the second black characteristic amount acquisition step, the characteristic of the image is used as the predetermined reference, and the second black characteristic is obtained from the first or second function data based on a characteristic signal representing the characteristic. An image processing method characterized by acquiring a characteristic amount . An image forming apparatus comprising the image processing apparatus according to any one of claims 1-7. An image processing program for operating an image processing apparatus according to any one of claims 1 to 7, an image processing program for causing a computer to function as each means described above. A computer-readable recording medium an image processing program according to claim 1 2.

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