JP3736632B2 - Image processing apparatus, image processing method, and medium on which image processing program is recorded - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
  The present invention relates to an image processing apparatus, an image processing method, and a medium on which an image processing program is recorded, and more particularly, to an image processing apparatus, an image processing method, and a medium on which an image processing program is recorded that enhances contrast and saturation of image data.
[0002]
[Prior art]
  When a photograph is read with a scanner or the like and converted into electronic image data, it may be desirable to emphasize the contrast and vividness of the image. Conventionally, photo retouching software or the like is known as means for converting this type of image data.
[0003]
  As a method for enlarging the contrast of image data, one disclosed in Japanese Patent Publication No. 7-66318 is known, and the relationship between the luminance y ′ after conversion and the luminance y ′ after conversion is expressed by equation (1). Thus, the brightness of the image data is converted based on the parameter a or the parameter b selected by the operator. As a result, an image in which the contrast is enhanced for image data having a low contrast is obtained.
[0004]
  y ′ = ay + b (1)
  On the other hand, for enhancing so-called saturation in order to enhance vividness, for example, color components of image data are represented by gradation data of red (= R), green (= G), and blue (= B). It is known to increase the value of the desired color component when it is present.
[0005]
  That is, when the gradation data is in the range of “0 to 255”, in order to make the red color more vivid, “20” is uniformly added to the red gradation data, or the blue color is more vivid. For this purpose, “20” is uniformly added to the blue gradation data.
[0006]
[Problems to be solved by the invention]
  By the way, there is a tendency to increase the value of image data in both the process of enlarging the contrast and the process of enhancing the saturation. Therefore, it is not preferable to enhance the saturation after enhancing the contrast, resulting in a flashy image.
[0007]
  However, in the above-described conventional image processing apparatus, there is a problem that if one is adjusted to an appropriate state and then the other is adjusted, the result of the previous adjustment is out of order.
[0008]
  SUMMARY An advantage of some aspects of the invention is that it provides an image processing apparatus, an image processing method, and a medium on which an image processing program is recorded, which can easily obtain a desired image.
[0009]
[Means for Solving the Problems]
  In order to achieve the above object, the invention according to claim 1 comprises a contrast enlarging means for enlarging a luminance distribution in image data, a saturation emphasizing means for enhancing the saturation of each pixel in the image data, and the contrast enlarging means. One of the parameter representing the degree of expansion of the luminance distribution and the parameter representing the degree of saturation enhancement in the saturation enhancement means is a temporary parameter, and the temporary parameter is automatically calculated from the other parameter and the temporary parameter. Enhancement processing suppression means for converting the parameter into a parameter that suppresses the operation, and the contrast enlarging means and the saturation enhancement means use the converted parameter and the other parameter, respectively. The image data is converted so as to perform processing.
[0010]
  In the invention according to claim 1 configured as described above, the contrast enlarging means expands the luminance distribution in the image data, while the saturation emphasizing means emphasizes the saturation of each pixel in the image data. Emphasis processing suppression means by the brightness distribution expansion operation and saturation enhancement operationEach other or oneTry to suppress each other.
[0011]
  Therefore, if the contrast is enlarged by the contrast enlargement means and the saturation is emphasized by the saturation enhancement means, the enhancement processing suppression means isBoth or oneSuppresses the highlighting operation and prevents it from becoming synergistic.
[0012]
  Emphasis processing suppression means is about the brightness distribution expansion operation and saturation enhancement operation.Anything that relates the other in a suppressive manner may be used.Here, the process of enlarging the luminance distribution varies, and the same applies to the saturation enhancement process. Accordingly, the specific method may be appropriately changed according to the contrast enlarging means and the saturation emphasizing means. Also,In repressively relating the other,It does not necessarily suppress each other, but the suppression process may be performed from one to the other, but the reverse process may not be performed. In this way, it is possible to select a case where synergistic emphasis is prevented and a case where such emphasis is approved.
  In this sense, according to a second aspect of the present invention, in the image processing apparatus according to the first aspect, the enhancement processing suppression unit is configured to perform saturation when attempting to perform the luminance distribution expansion operation and the saturation enhancement operation. The invention according to claim 3 is the image processing apparatus according to claim 1, wherein the enhancement processing suppression unit performs a luminance distribution expansion operation and a saturation enhancement operation. According to the invention according to claim 4, in the image processing apparatus according to claim 1, the enhancement processing suppression unit is configured to suppress the luminance distribution expansion operation. In this configuration, the enlargement operation and the saturation enhancement operation are mutually suppressed.
[0013]
  Of course, as a result, the luminance distribution expansion operation and saturation enhancement operationIt only needs to be able to relate the other in a suppressive way,For example, when it is necessary to suppress the enlargement operation in the contrast enlargement means, a further conversion process that denies the enlargement result for the enlarged image data is performed instead of suppressing the enlargement operation of the contrast enlargement means itself. Alternatively, it may be applied, or it may be different from the increase in contrast, but the same result may be obtained by darkening the image as a whole. This also applies to the saturation enhancement operation.
[0014]
  on the other hand,More to suppressively relate the otherClaims for specific methods5The present invention relates to the above-mentioned claim.1 to 4In the image processing device according to any one of the above, the enhancement processing suppression unit includes one of a parameter that represents the degree of expansion of the luminance distribution in the contrast enlarging unit and a parameter that represents the degree of saturation enhancement in the saturation enhancement unit. When the value of becomes larger, the other becomes smaller.
[0015]
  Configured as aboveClaim 5In the invention according to the invention, the contrast enlarging means converts the image data using a parameter representing the degree of expansion of the luminance distribution, and the saturation emphasizing means also uses the parameter representing the degree of enhancement of the saturation to convert the image data. As a result, the enhancement processing suppression means associates so that when one is large, the other is small, and as a result, the luminance distribution expansion operation and the saturation enhancement operation are performed. And act to suppress each other.
[0016]
  Various methods can be used to associate the parameters of the two. For example, if one parameter is multiplied by a coefficient having the other parameter as the denominator, the same parameter becomes smaller as the other parameter becomes larger.
In this case, the other parameter is not affected by the same parameter, but can be easily realized by another method if it is desired to influence each other. Of course, a conversion table referred to by mutual parameters may be prepared, and conversion values that suppress each other may be read out.
[0017]
  There are various methods of image data conversion performed by the contrast enlarging means and the saturation emphasizing means.,The contrast enlarging means and the saturation emphasizing means are configured to perform a conversion operation on image data for each pixel.Also good.
[0018]
  If image data conversion for contrast enhancement or image data conversion for saturation enhancement is not performed for each pixel, the causal relationship between this enlargement processing and saturation enhancement processing becomes complicated. Depending on the situation, complicated processing may be required to suppress both of them, and a separate work area may be required. However, if the conversion operation is performed on the image data for each pixel, the influence of the process such as increase / decrease of the image data on the contrast and saturation becomes simple, and the process of suppressing each other becomes simple.
[0019]
  When the contrast enlargement means and the saturation enhancement means convert the image data,Claim 6The invention according to claim 1 to claim 1 above.Claim 5In the image processing apparatus according to any one of the above, one or both of the contrast enlarging unit and the saturation emphasizing unit analyze image data and set the degree of enhancement.
[0020]
  That is, the contrast enlarging means and the saturation emphasizing means automatically set the degree of emphasis, and the emphasis processing suppression means performs the above-described suppression operation in this automation process. Accordingly, when the contrast enlarging means sets the degree of enhancement, if the degree of enhancement is reduced or the processing is changed by referring to parameters in the saturation enhancement means, such processing is the enhancement processing suppression means. Will be composed. Of course, when the saturation enhancement means sets the degree of enhancement, this processing constitutes the enhancement processing suppression means when the degree of enhancement is reduced or the process is changed with reference to parameters in the contrast enlargement means. Will do.
[0021]
  As a specific configuration of the contrast enlargement means for analyzing the image data and setting the enlargement degree,Claim 7The invention according to the aboveClaim 6In the image processing apparatus according to claim 1, the contrast enlarging unit includes a luminance distribution detecting unit that detects a luminance distribution of image data in units of pixels, and the same luminance within a reproducible range based on the detected luminance distribution. Contrast data conversion means for determining the degree to which the distribution can be expanded and converting the image data is provided.
[0022]
  In order to obtain the luminance distribution in handling the image data, the luminance distribution detecting means detects the luminance distribution of the image data in units of pixels. Then, using the detected luminance distribution, the contrast data converting means determines the amount of expansion of the luminance distribution within a reproducible range, and converts the image data.
[0023]
  That is, the so-called contrast width from the brightest brightness to the darkest brightness can be determined by obtaining the brightness distribution of the image data in pixel units, and the contrast magnification can be determined by comparing with the reproducible brightness width range. Therefore, after that, it is sufficient to enlarge the luminance distribution so that the enlargement ratio is obtained. For example, after the luminance distribution as a whole is aggregated based on the luminance at each pixel, the luminance distribution is the same when the aggregated luminance distribution is not widely dispersed in the effective luminance range that the image data can take. The luminance information of each pixel in the image data is converted so as to be widely distributed in the luminance range.
[0024]
  In addition, as a specific configuration of the saturation enhancement means for analyzing the image data and setting the enhancement degree,Claim 8The invention according to the aboveClaim 6OrClaim 7In the image processing apparatus according to any one of the above, the saturation enhancement means includes a saturation distribution counting means for counting the saturation distribution of each pixel in the image data, and the saturation calculated by the saturation distribution counting means. Saturation enhancement degree determination means for determining the degree of enhancement of the saturation of the image data from the distribution state of the degree, and new image data by correcting the information representing the saturation in the image data based on the determined degree of conversion Saturation data conversion means for converting to the above.
[0025]
  Configured as aboveClaim 8In the invention according to this aspect, when the saturation distribution totalizing unit totals the saturation distribution of each pixel in the image data, the saturation enhancement determination unit determines from the saturation distribution state totaled by the saturation distribution totaling unit. The degree of enhancement of the saturation of the image data is determined, and the saturation data conversion means corrects information representing the saturation in the image data based on the determined degree of conversion and converts the information to new image data. That is, for each image, the optimum enhancement degree is determined from the saturation distribution of the image data and converted. Note that the saturation enhancement means is not necessarily limited to the enhancement process, and may be a process that weakens the image.
  As a more specific configuration, the invention according to claim 9 is the image processing apparatus according to any one of claims 1 to 7, wherein the contrast enlarging means is an effective value that the image data can take. The luminance range is y range The luminance y before conversion and the maximum value y of the luminance distribution range max And the minimum value y min Therefore, the luminance Y of the conversion destination is obtained based on the following equation.
  Y = ay + b
However,
  a = y range / (Y max -Y min )
  b = −a · y min Or y range -A ・ y max
If Y <0 in the above conversion formula, then Y = 0 and Y> y range Then Y = y range And
  Furthermore, the invention according to claim 10 is the image processing apparatus according to any one of claims 1 to 8, wherein the saturation emphasizing unit is configured such that the image data includes component values of a plurality of substantially equal hue components. In this case, a saturation conversion is performed by adding a value obtained by multiplying a difference value between each hue component and luminance by a predetermined enhancement coefficient to the same hue component.
[0026]
  As described above, the method of processing in association with the luminance distribution expansion operation and the saturation enhancement operation so as to suppress each other is not necessarily limited to a substantial device, and also functions as the method. That is easy to understand. For this reason, the invention according to claim 11 includes a contrast enlargement process for enlarging the luminance distribution in the image data and a saturation enhancement process for enhancing the saturation of each pixel in the image data. When one of the parameter that represents the degree of expansion of the luminance distribution and the parameter that represents the degree of saturation enhancement in the above saturation enhancement processing is a temporary parameter, and an attempt is made to perform an operation of expanding the luminance distribution and an operation of enhancing the saturation. In addition, the temporary parameter is automatically converted from the other parameter and the temporary parameter into a parameter that suppresses the operation, and each process is performed using the converted parameter and the other parameter. As described above, the image data is converted.
[0027]
  That is, it is not necessarily limited to a substantial apparatus, and there is no difference that the method is also effective.
[0028]
  By the way, such an image processing apparatus may exist alone, or may be used in a state of being incorporated in a certain device. The idea of the invention is not limited to this, and includes various aspects. . Therefore, it can be changed as appropriate, such as software or hardware.
[0029]
  As an example, even in a printer driver that converts image data corresponding to printing ink based on input image data and prints it on a predetermined color printer, contrast enlargement processing for expanding the luminance distribution in the image data, and image data When executing the saturation enhancement processing for enhancing the saturation of each pixel in the image, the image data is converted and printed so that the expansion operation of the luminance distribution and the enhancement operation of the saturation are associated with each other so as to suppress each other. Can be configured.
[0030]
  That is, the printer driver converts the image data input corresponding to the printing ink, and at this time, contrast enhancement processing for expanding the luminance distribution in the image data and saturation enhancement for enhancing the saturation of each pixel in the image data. Processing, and when this processing is executed, the brightness distribution expansion operation and the saturation enhancement operation are performed.TogaBy associating them so as to suppress each other, the two processes act synergistically so that they do not become flashy and are printed.
[0031]
  In the case of software for an image processing apparatus as an embodiment of the idea of the invention, it naturally exists on a recording medium on which such software is recorded and must be used. As an example of the invention, the invention according to claim 12 includes a contrast enlargement process for inputting image data by a computer and expanding a luminance distribution in the image data, and a saturation enhancement for enhancing the saturation of each pixel in the image data. A medium on which an image processing program for executing the processing is recorded, and when executing the contrast enlargement process and the saturation enhancement process, a parameter representing a degree of expansion of the luminance distribution in the contrast enlargement process and the saturation enhancement One of the parameters representing the degree of saturation enhancement in the processing is set as a temporary parameter, and when trying to perform the luminance distribution expansion operation and the saturation enhancement operation, the other parameter and the temporary parameter are used. The temporary parameter is automatically converted to a parameter that suppresses the operation, and To implement the respective processing using the other parameters is a configuration for converting the image data.
[0032]
  Of course, the recording medium may be a magnetic recording medium, a magneto-optical recording medium, or any recording medium that will be developed in the future. In addition, the duplication stage of the primary duplication product, secondary duplication product, etc. is the same without any question..
[0033]
  Further, even when a part is software and a part is realized by hardware, there is nothing completely different in the idea of the invention, and a part is stored on a recording medium, and it is appropriately changed as necessary. It may be in the form of being read. Furthermore, it goes without saying that the present invention can also be applied to an image processing apparatus built in a color facsimile machine, a color copier, a color scanner, a digital camera, a digital video, or the like.
[0034]
【The invention's effect】
  As described above, the present invention performs the contrast enlargement process and the saturation enhancement process.,Since they are associated so as to suppress each other, it is possible to provide an image processing apparatus that can act synergistically to prevent being too flashy. Moreover, even if the other is adjusted after one adjustment, the previous adjustment can be utilized.
[0035]
  Also,Claim 5According to the invention, processing is facilitated by associating with parameters representing the degree of contrast enhancement and the degree of saturation enhancement.
[0036]
  further,Assuming conversion of image data for each pixel,Conversion is simple and association is easy.
[0037]
  further,Claim 6According to the invention, since the degree of enhancement of contrast and saturation is determined by analysis of image data, it is easy to realize enhancement processing in combination with this.
[0038]
  further,Claim 7According to the invention, the contrast distribution can be quantitatively handled by obtaining the luminance distribution, and the degree of enlargement within the reproducible range can be obtained, so that contrast enhancement is automated. be able to.
[0039]
  further,Claim 8According to the invention, it is possible to quantify the saturation index of an image by summing up the distribution of saturations, and to perform optimum saturation enhancement according to each image.
[0040]
  further,Claim 11According to the invention, the contrast enlargement process and the saturation enhancement process are performed.DepressImage processing that can synchronize and prevent being overly flashy, and can make use of the previous adjustment even if the other is adjusted after one adjustment. Can provide a way,Claim 12According to the invention, a medium on which an image processing program capable of preventing the contrast enlargement process and the saturation enhancement process from acting too synergistically to be too flashy is provided. be able to.
[0041]
DETAILED DESCRIPTION OF THE INVENTION
  Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[0042]
  FIG. 1 is a block diagram illustrating an image processing system according to an embodiment of the present invention, and FIG. 2 is a block diagram illustrating a specific hardware configuration example.
[0043]
  In the figure, an image input apparatus 10 captures an image and outputs image data to the image processing apparatus 20, and the image processing apparatus 20 performs contrast enlargement processing and saturation enhancement processing while correlating and suppressing each other. Are output to the image output device 30, and the image output device 30 displays an image in which contrast and saturation are appropriately corrected.
[0044]
  Here, a specific example of the image input device 10 corresponds to the scanner 11, the digital still camera 12, or the video camera 14, and a specific example of the image processing device 20 corresponds to a computer system including the computer 21 and the hard disk 22. Specific examples of the output device 30 include a printer 31, a display 32, and the like.
[0045]
  In the present image processing system, the contrast and saturation of the image data are to be enhanced. Therefore, the image processing system captures a photograph with a scanner 11 as the image input apparatus 10 or a digital still camera 12. In the case of the processed image data or the like, the case where the contrast width is narrow or the vividness has faded due to the flare of the light beam or the like becomes the object of processing and is input to the computer system as the image processing apparatus 20. The image processing apparatus 20 performs a contrast enlargement process and a saturation enhancement process as will be described later, and further suppresses the enhancement so as not to synergize too much. Of course, the image processing apparatus 20 may also be a color conversion unit that corrects a color difference for each model, or a resolution conversion unit that converts a resolution corresponding to each model. .
[0046]
  In this example, the computer 21 executes each image processing program stored in the internal ROM or the hard disk 22 while using a RAM or the like. Such an image processing program is supplied via various recording media such as a CD-ROM, floppy disk, and MO, and connected to an external network via a public communication line by a modem or the like. And downloading and installing data.
[0047]
  The execution result of this image processing program is obtained as image data with increased contrast and enhanced saturation, and is printed by the printer 31 that is the image output device 30 based on the obtained image data, or the same image output device. 30 is displayed on the display 32. More specifically, the image data is RGB (green, blue, red) gradation data, and the image has a grid of pixels in the vertical direction (height) and the horizontal direction (width). It is configured as lined dot matrix data. That is, the image data represents information of each pixel by decomposing the image into pixels in a dot matrix.
[0048]
  In this embodiment, a computer system is incorporated between image input / output devices to perform image processing. However, such a computer system is not necessarily required. For example, the digital still camera 12a shown in FIG. 3 incorporates an image processing device in the sense of correcting contrast and saturation. That is, the digital still camera 12a includes an image pickup unit including an optical system 12a1 and a photoelectric conversion unit 12a2 including a CCD. The digital still camera 12a converts an optical image into a digital image under the control of the control unit 12a3. Although it can be recorded in the memory 12a4, the image correction unit 12a5 is provided here to correct the contrast and saturation of the captured image data while suppressing emphasis on each other. In such a case, the image correction unit 12a5 may be configured by hardware such as an LSI or may be configured by software processing.
[0049]
  It is also possible to adopt a configuration in which contrast and saturation are emphasized at the output stage without specifying an input device. For example, the printer driver shown in FIG. 4 has a rasterizer 21a1 that cuts out the scanning range of the print head in the printer from the image data output by the printing application, and an RGB gradation table with reference to the color conversion table for each pixel in the scanning range. Ordinary printer driver in that it includes a color conversion unit 21a2 that converts color data into CMY gradation color data and a gradation conversion unit 21a3 that converts CMY gradation data into binary data. And in common. However, it differs from a normal printer driver in that it includes an image correct module 21b that corrects image data before it is input to the rasterizer 21a1. The image correct module 21b performs contrast enlargement, saturation enhancement, and suppression of these enhancement processes. By configuring in this way, whatever image data is input, At the time of printing, the contrast and saturation are moderately emphasized, and printing becomes possible.
[0050]
  Returning to the present embodiment, FIG. 5 shows a flowchart corresponding to image processing executed by the computer 21 as the image processing apparatus 20. In order to set parameters in the contrast enlarging process and the saturation emphasizing process, a predetermined aggregation process is executed in step S110, and in step S120, a contrast expansion coefficient is determined based on the luminance distribution as the aggregation result, and step S130. Then, a temporary saturation emphasis coefficient is determined based on the saturation distribution that is the total result. In step S140, a formal saturation enhancement coefficient for suppressing the enhancement is determined from the contrast expansion coefficient and the temporary saturation enhancement coefficient. In the last step S150, the same contrast enhancement coefficient and the formal saturation enhancement are determined. The image data is converted based on the coefficients.
[0051]
  These will be described in detail below.
[0052]
  Before explaining the first aggregation process, the thinning process used at the time of aggregation will be described. As will be described later, the luminance distribution necessary for the contrast enlargement processing and the saturation distribution necessary for the saturation enhancement processing are only to know a rough tendency, so an exact numerical value affects the result. Do not mean. Therefore, the totalization is not performed for all the pixels, but the totalization is performed by thinning out the error so as to be within the allowable range.
[0053]
  As shown in FIG. 6, in the case of a bitmap image, it is formed as a two-dimensional dot matrix consisting of predetermined dots in the vertical direction and predetermined dots in the horizontal direction. When thinning out based on statistical errors, The error with respect to the number N can be generally expressed as 1 / (N ** (1/2)). However, ** represents a power. Therefore, in order to perform processing with an error of about 1%, N = 10000.
[0054]
  Here, the bitmap screen shown in FIG. 6 has the number of pixels of (width) × (height), and the sampling period ratio is
  ratio = min (width, height) / A + 1 (2)
And Note that min (width, height) is the smaller of width and height, and A is a constant. Further, the sampling period ratio here indicates how many pixels are sampled, and the pixels marked with ◯ in FIG. 7 indicate the case where the sampling period ratio = 2. That is, one pixel is sampled every two pixels in the vertical and horizontal directions, and every other pixel is sampled. The number of sampling pixels in one line when A = 200 is as shown in FIG.
[0055]
  As can be seen from the figure, except for the case where the sampling period ratio = 1 in which sampling is not performed, when there is a width of 200 pixels or more, the number of samples is at least 100 pixels. Therefore, in the case of 200 pixels or more in the vertical direction and the horizontal direction, (100 pixels) × (100 pixels) = (10000 pixels) is secured, and the error can be reduced to 1% or less.
[0056]
  Here, the reason for using min (width, height) as a reference is as follows. For example, as shown in FIG. 9A, when width >> height is determined with the longer width as shown in FIG. 9A, the sampling period ratio is determined as shown in FIG. 9B. In addition, in the vertical direction, only two lines of the upper end and the lower end may be extracted.
However, if the sampling period ratio is determined based on the smaller one as min (width, height), thinning is performed so as to include the intermediate portion in the smaller vertical direction as shown in FIG. Will be able to.
[0057]
  In this example, thinning is performed with an accurate sampling period for pixels in the vertical and horizontal directions. This is suitable for processing while thinning out pixels that are sequentially input. However, when all the pixels have been input, the pixels may be selected by randomly specifying coordinates in the vertical direction or the horizontal direction. In this way, when the necessary minimum number of pixels, such as 10,000 pixels, is determined, the extraction process is repeated at random until the number of pixels reaches 10,000, and the extraction is stopped when the number of pixels reaches 10,000.
[0058]
  The luminance and saturation distributions are totaled while performing the thinning process in this way. The brightness distribution is required for the contrast enlargement process. Next, the contrast enlargement process will be described.
[0059]
  A basic flow of the contrast enlargement process is shown in the flowchart of FIG. 10, and FIG. 11 shows a specific result of the contrast enlargement process. In FIG. 10, an image conversion process is performed in which the contrast expansion coefficient is determined in the process of the first step S120 surrounded by the one-dot chain line, the enhancement suppression process is performed in the next step S140, and the contrast is actually expanded in the process of the last step S150. Is shown. Further, as shown in FIG. 11, when the luminance distribution over the entire image data is smaller than the original reproducible range, a process of expanding the luminance distribution range is performed, and the extent that can be expanded in this sense is obtained. Therefore, the luminance distribution range of the image data is used.
[0060]
  If the pixel data for the pixel selected in the thinning process has luminance as its component element, the distribution can be obtained using the luminance value, but the luminance as a direct component element can be obtained with RGB gradation data I don't have a value. In such a case, the luminance value can be obtained by performing conversion from the color space where the luminance value is not a direct component value to the color space where the luminance value is a direct component value. A size color conversion table is required and the amount of calculation processing is enormous. In view of such a situation, in the present embodiment, as used in the case of a television or the like, the following conversion formula for obtaining luminance from the three primary colors of RGB is adopted. That is, for the luminance yp at the point P, from the RGB component values (Rp, Gp, Bp),
  yp = 0.30Rp + 0.59Gp + 0.11Bp (3)
And In this way, the luminance value can be obtained by only three multiplications and two additions.
[0061]
  By the way, when the reproducible luminance range is “0” to “255”, in the luminance conversion, the luminance y before conversion from the luminance y before conversion, the maximum value ymax and the minimum value ymin of the luminance distribution range. Is obtained based on the following equation.
[0062]
  Y = ay + b (4)
However,
  a = 255 / (ymax−ymin) (5)
  b = −a · ymin or 255−a · ymax (6)
In the above conversion equation, if Y <0, Y = 0, and if Y> 255, Y = 255. Here, a is an inclination and b can be said to be an offset. According to this conversion formula, a luminance distribution having a narrow width can be expanded to a reproducible range.
[0063]
  Here, returning to the flowchart shown in FIG. 10, both ends of the luminance distribution are obtained in step S202. The luminance distribution in the natural image appears approximately in a mountain shape as shown by the solid line in FIG. Of course, there are various positions and shapes. The width of the luminance distribution is determined by where the two ends are determined. However, the point where the base extends and the number of distributions is “0” cannot be the both ends, and the smallest luminance side is the smallest in the distribution range. The part that is closer to the inside by a certain distribution ratio from the side is defined as both ends of the distribution. In the present embodiment, this distribution ratio is set to 0.5%. In this way, by cutting the upper end and the lower end by a certain distribution ratio, it is possible to ignore white spots and black spots caused by noise or the like.
[0064]
  In actual processing, 0.5% of the number of pixels to be processed (the total number of pixels selected in the thinning-out processing) is calculated, and inward from the luminance value at the upper end and the luminance value at the lower end in the reproducible luminance distribution. Then, the number of distributions is accumulated to obtain a luminance value of 0.5%. The upper end side is ymax, and the lower end side is ymin.
[0065]
  In the present embodiment, the upper end and the lower end are obtained through such processing on the luminance distribution, but it is also possible to obtain both ends under statistical processing. For example, it is also possible to adopt a method in which the portion where the percentage of the average value of the luminance values is less than or equal to the edge is used.
[0066]
  By the way, since the range that the luminance y can take is only “0” to “255”, it is efficient to obtain the luminance Y after conversion corresponding to all the values that the luminance y can take in advance. Yes, the correspondence is calculated and stored as a table in step S204.
[0067]
  Thus, the preparation for enlarging the contrast is completed, but the degree of enlargement corresponds to the parameter a in the equation (4). Hereinafter, the parameter a will be referred to as a contrast enlarging coefficient. Due to its nature, the contrast expansion coefficient a is a value of “1” or more.
[0068]
  The conversion of the image data for increasing the contrast is thereafter performed with reference to the table calculated in step S204 for each pixel. By the way, the correspondence relationship for converting the luminance has been obtained so far, and for example, it is not the conversion relationship for the component values (Rp, Gp, Bp) on the RGB coordinate axes. However, the conversion formula (4) can also be applied in correspondence with the RGB component values (Rp, Gp, Bp). That is, the component values (R ′, G ′, B ′) after conversion with respect to the component values (R, G, B) before conversion are
  R ′ = a · R + b (7)
  G ′ = a · G + b (8)
  B ′ = a · B + b (9)
Can be obtained as This is clear from the fact that both the equations (4) and (3) show a linear correspondence. Also, the RGB component values (R, G, B), (R ′, G ′, B ′) are the same corresponding to the luminance y, Y ranging from “0” to “255”. It can be said that the luminance y and Y conversion tables described above may be used as they are.
[0069]
  Accordingly, in step S206, the image data (R, G, B) of all the pixels is converted into image data (R ′, G ′, B ′) by referring to the conversion table corresponding to the equations (7) to (9). . In step S208, the converted pixels are sequentially moved as shown in FIG. 12, and the process is repeated until the final pixel is determined in step S210.
[0070]
  In the present embodiment, the degree of emphasis that increases the contrast is automatically obtained, but it is also possible for the operator to manually set the parameters a and b.
[0071]
  On the other hand, it is the saturation enhancement processing that requires the saturation distribution to be totalized in the above-described thinning-out processing. Next, saturation enhancement will be described.
[0072]
  The basic flow of saturation enhancement processing is shown in the flowchart of FIG. 13, FIG. 14 shows the saturation distribution, and FIG. 15 shows the saturation enhancement coefficient derived from the saturation distribution. Also in FIG. 13, the saturation enhancement coefficient is determined in the process of the first step S130 surrounded by the one-dot chain line, the enhancement suppression process is performed in the next step S140, and the saturation is actually enhanced in the process of the last step S150. An image conversion process is shown. In this process, as shown in FIG. 14, the saturation A representing the saturation of the entire image is obtained from the saturation distribution over the entire image data, and the saturation enhancement coefficient S is obtained from the saturation A. In order to obtain the saturation A, the saturation distribution of the image data is used. As will be described later, since the processing for weakening the saturation enhancement coefficient S is performed based on the contrast expansion coefficient a in the subsequent enhancement suppression processing, it can be said to be a temporary value here.
[0073]
  The saturation distribution is also totalized for the pixels thinned out in step S110. If the image data has saturation as its component element, the distribution can be obtained using the saturation value, and even in the case of image data where saturation is not a direct component element Specifically, it has component values representing saturation. Therefore, a saturation value can be obtained by performing conversion from a color space where saturation is not a direct component element to a color space where the saturation value is a direct component value. For example, in the Luv space as a standard color system, the L axis represents luminance (brightness), and the U axis and V axis represent hue. Here, in the U axis and the V axis, the distance from the intersection of both axes represents the saturation, so that (U ** 2 + V ** 2) ** (1/2) is substantially the saturation. However, the amount of calculation processing required for such conversion becomes enormous.
[0074]
  Therefore, in this embodiment, standard RGB gradation data is directly used as image data, and an alternative value X of saturation is obtained as follows.
[0075]
  X = | G + B−2 × R | (10)
  Originally, the saturation is “0” when R = G = B, and becomes the maximum value when mixing with a predetermined ratio of one or two colors of RGB. Although it is possible to express the saturation appropriately from this property, it is possible to obtain the maximum saturation if it is cyan, which is a single color of red and a mixed color of green and blue, according to the simple equation (10). It is “0” when the components are uniform. In addition, green and blue single colors reach about half of the maximum value.
[0076]
  In a situation where each component represents a component of each color independently as in the RGB color space, in other words, in a situation where the component values of the hue components are roughly equivalent,
  X ′ = | R + B−2 × G | (11)
  X ″ = | G + R−2 × B | (12)
However, as a result, the one according to the equation (10) was the best.
[0077]
  When the saturation distribution is obtained from the RGB image data on the basis of the expression (10) for the pixels thinned out in step S110, the saturation is distributed in the range of the minimum value “0” to the maximum value “511”. The distribution is as shown in FIG.
[0078]
  Based on the aggregated saturation distribution, a saturation enhancement coefficient for this image is determined in step S302. Assuming that the aggregated saturation distribution is as shown in FIG. 14, in the present embodiment, the range occupied by the upper “16%” is obtained as the distribution number within the range of effective pixels. Then, the saturation enhancement coefficient S is determined based on the following equation, assuming that the lowest saturation “A” in this range represents the saturation of this image.
[0079]
  That is,
  If A <92
    S = −A × (10/92) +50 (13)
  If 92 ≦ A <184
    S = −A × (10/46) +60 (14)
  If 184 ≤ A <230
    S = −A × (10/23) +100 (15)
  If 230 ≦ A
    S = 0 (16)
  And FIG. 15 shows the relationship between the saturation “A” and the saturation enhancement coefficient S. As shown in the figure, the saturation enhancement coefficient S is large when the saturation “A” is small in the range from the maximum value “50” to the minimum value “0”, and small when the saturation “A” is large. Will gradually change.
[0080]
  In this embodiment, the saturation occupied by a certain ratio in the upper part of the total saturation distribution range is used. However, the present invention is not limited to this. For example, an average value is obtained or a median is obtained to enhance saturation. It may be a basis for calculating the coefficient S. However, when a certain proportion of the upper level in the saturation distribution is taken, the influence of the sudden error is weakened, and thus a good result as a whole can be obtained.
[0081]
  When the saturation enhancement coefficient S is obtained, the saturation enhancement processing is performed on the image data of each pixel as shown in the subsequent stage of FIG. In order to enhance the saturation based on the saturation enhancement coefficient S, if the image data has a saturation parameter as described above, the same parameter may be converted. Adopting space. Therefore, a method for enhancing the saturation by using the RGB gradation data as it is will be described below.
[0082]
  When each component is a component value of a hue component in which the respective components are roughly equivalent as in the RGB color space, if R = G = B, the color is gray and achromatic. Therefore, assuming that the component having the minimum value in each component of RGB is merely reducing the saturation without affecting the hue of each pixel, the minimum value in each component is determined from all the component values. It can be said that the saturation can be enhanced by subtracting and enlarging the difference value.
[0083]
  First, a saturation enhancement parameter Sratio that is advantageous for calculation from the saturation enhancement coefficient S described above,
  Sratio = (S + 100) / 100 (17)
  Asking. In this case, when the saturation enhancement coefficient S = 0, the saturation enhancement parameter Sratio = 1 and the saturation is not enhanced. Next, assuming that the component value of blue (B) in each component (R, G, B) of the RGB gradation data is the minimum value, conversion is performed as follows using this saturation enhancement parameter Sratio.
[0084]
  R ′ = B + (R−B) × Sratio (18)
  G ′ = B + (GB) × Sratio (19)
  B '= B (20)
  This eliminates the need for color conversion between at least the RGB color space and the Luv space, but in this case, even if the saturation is emphasized independently, the luminance also increases. There is a tendency to become bright overall. Therefore, the conversion is performed on the difference value obtained by subtracting the luminance equivalent value from each component value.
[0085]
  For luminance, the conversion formula obtained directly from RGB as described above is used.
[0086]
  On the other hand, saturation enhancement
  R ′ = R + ΔR (21)
  G ′ = G + ΔG (22)
  B ′ = B + ΔB (23)
And These addition / subtraction values ΔR, ΔG, ΔB are obtained by the following equation based on the difference value from the luminance. That is,
  ΔR = (R−Y) × Sratio (24)
  ΔG = (G−Y) × Sratio (25)
  ΔB = (BY) × Sratio (26)
And as a result,
  R ′ = R + (R−Y) × Sratio (27)
  G ′ = G + (G−Y) × Sratio (28)
  B ′ = B + (BY) × Sratio (29)
Can be converted as In addition, the preservation | save of a brightness | luminance is clear from following Formula.
[0087]
  Y ′ = Y + ΔY (30)
  ΔY = 0.30ΔR + 0.59ΔG + 0.11ΔB
      = Sratio {(0.30R + 0.59G + 0.11B) -Y}
      = 0 (31)
Further, when the input is gray (R = G = B), the luminance Y = R = G = B, so the addition / subtraction value ΔR = ΔG = ΔB = 0, and the achromatic color is not colored. . When the image data is converted in step S304, the converted pixel is moved in the same manner as shown in FIG. 12 in step S306, and the process is repeated until it is determined as the final pixel in step S308.
[0088]
  In this embodiment, the degree of enhancement for enhancing the saturation is automatically obtained in this way. However, when the operator manually increases or decreases the component value uniformly, such an increase / decrease value is used. Is a saturation enhancement parameter.
[0089]
  When the contrast expansion coefficient a and the saturation enhancement coefficient S are obtained in the preceding stage of each process described above, the enhancement suppression process is executed in step S140 corresponding to the middle part to obtain the formal saturation enhancement coefficient S ′. Ask. If the expressions (27) to (29) are used in the saturation enhancement process, the luminance is preserved, and even if the saturation is enhanced, the overall brightness does not increase. However, there is no problem when only the saturation is emphasized in this way, and when the process of enlarging the contrast and the saturation enhancement process are performed at the same time, they act synergistically and the image becomes flashy. Become. In order to avoid this, it is necessary to associate each other with emphasis processing. This association is performed based on the following equation.
[0090]
  S ′ = S × (1 / a) (32)
  As described above, the contrast enlargement coefficient a is “1” or more, and if the enlargement tendency becomes strong, (1 / a) becomes less than “1”. Therefore, the formal saturation enhancement coefficient S ′ is as described above. It becomes smaller than the calculated temporary saturation enhancement coefficient S. That is, the parameter used in the saturation enhancement process is reduced by the parameter used in the contrast enlargement process, and the enhancement process is suppressed.
[0091]
  In this embodiment, as shown in FIG. 16, association is performed such that the saturation enhancement coefficient S is weakened by the contrast expansion coefficient a, and in this sense, it can be said that an enhancement processing suppression filter is provided. However, as shown in FIG. 17, it is possible to perform association that weakens the contrast enhancement coefficient a with the saturation enhancement coefficient S, and as shown in FIG. 18, association that weakens each other is performed. Also good. Also, instead of a unique filter, as shown in FIGS. 19A and 19B, a conversion table to be referred to according to specific values of the contrast expansion coefficient a and the saturation enhancement coefficient S is prepared. Also good. If such a conversion table is prepared, more detailed settings can be made.
[0092]
  On the other hand, it may not be necessary to weaken each other. For example, when the contrast enlargement coefficient a and the saturation enhancement coefficient S are small, there are cases where they act individually and have no synergistic adverse effects. Therefore, as shown in FIG. 20, a non-interference area may be prepared so as to be affected by weakening when a certain threshold value is reached. Similarly, it is also possible to act to weaken the other party only when a certain threshold value is exceeded.
[0093]
  In this way, if the arithmetic expression (32) is used or the enhancement processing is suppressed using the conversion table, the image data is finally converted using the enhancement processing coefficient in step S150. That is, data conversion is performed on a pixel-by-pixel basis for the image data of the pixel of interest corresponding to the subsequent stage of each process described above.
[0094]
  As for the contrast enlargement process, as described above, the component values (R ′, G ′, B ′) after conversion with respect to the component values (R, G, B) before conversion for the pixel of interest are (7) to ( 9) Convert based on the equation.
[0095]
  On the other hand, for the saturation enhancement process, the saturation enhancement parameter S′ratio is obtained from the equation (17) based on the newly obtained saturation enhancement coefficient S ′, and the component values (R ′, G ′, B ′) are converted based on the equations (27) to (29) to obtain final image data of component values (R ″, G ″, B ″).
[0096]
  Next, the operation of the present embodiment having the above configuration will be described step by step.
[0097]
If a photograph is taken with the scanner 11 or the like, image data representing the photograph in RGB gradation data is taken into the computer 21, and the CPU executes the image processing program shown in FIG. The contrast enlargement process and the saturation enhancement process are executed so that the contrast and the vividness are obtained.
[0098]
  First, in step S110, a pixel is selected by thinning processing so as to be within an allowable error range, and the luminance of the same pixel is obtained from equation (3) and the saturation is obtained from equation (10). Then, the distributions of these luminance and saturation are totaled.
[0099]
  In the next step S120, the maximum value ymax and the minimum value ymin, which are the distribution range, are determined from the luminance distribution, parameters a and b are obtained from the equations (5) and (6), A conversion table is calculated in which the conversion relation for the gradations is calculated.
[0100]
  On the other hand, in step S130, a saturation A representing the saturation of the image is obtained from the saturation distribution, and a temporary saturation enhancement coefficient S is obtained from the relationship between the saturation A and the expressions (13) to (16).
[0101]
  Since the saturation enhancement coefficient S is a provisional value, in the next step S140, the contrast enhancement coefficient a is used to convert the equation (32) into the formal saturation enhancement coefficient S '.
With this process, the enhancement process can be suppressed. At this time, the saturation enhancement parameter S'ratio is obtained from the saturation enhancement coefficient S '.
[0102]
  Thereafter, in step S150, specific image data conversion is performed while sequentially moving the target pixel as shown in FIG.
[0103]
  That is, from the component values (R, G, B)
  R ′ = a · R + b (7)
  G ′ = a · G + b (8)
  B ′ = a · B + b (9)
The component values (R ′, G ′, B ′) are obtained through the following arithmetic expression, and from the component values (R ′, G ′, B ′) using the saturation enhancement parameter S ′ ratio described above.
  R ″ = R + (R′−Y) × S′ratio (27) ′
  G ″ = G + (G′−Y) × S′ratio (28) ′
  B ″ = B + (B′−Y) × S′ratio (29) ′
The final component values (R ″, G ″, B ″) are obtained through the following arithmetic expression.
[0104]
  The image data obtained in this way is the best image without synergistic action while the contrast is enlarged and the saturation is enhanced.
[0105]
  As described above, the contrast enhancement coefficient a is determined in step S120 and the saturation emphasis coefficient S is determined in step S130 based on the luminance distribution and the saturation distribution that are tabulated in the thinning-out aggregation in step S110. In S140, a new saturation enhancement coefficient S ′ is obtained by performing an association based on the contrast enhancement coefficient a so that the saturation enhancement coefficient S decreases as the contrast enhancement coefficient a increases, and the same in step S150. Since the image data is converted by using the saturation enhancement coefficient S ′ and the contrast enlargement coefficient a, it is possible to prevent the image data from being flashy due to a synergistic enhancement process when each is set. And the best image data can be easily obtained.
[0106]
  Note that the calculation speed of the input image of the video camera 14 may not be in time. Therefore, in such a case, brightness and saturation are detected for each shooting scene, and the degree of contrast expansion and saturation enhancement are determined on the assumption that the scene has the same tendency. In addition, it is only necessary to expand the luminance distribution and enhance the saturation for each frame based on the same degree of enhancement. Of course, if there is a sufficient calculation speed, conversion may be performed for each frame, or similar conversion can be performed on the receiver side.
[Brief description of the drawings]
FIG. 1 is a block diagram of an image processing system to which an image processing apparatus according to an embodiment of the present invention is applied.
FIG. 2 is a block diagram illustrating a specific hardware configuration example of the image processing apparatus.
FIG. 3 is a block diagram of a digital still camera showing another application example of the image processing apparatus of the present invention.
FIG. 4 is a configuration diagram of a printer driver showing another application example of the image processing apparatus of the present invention.
FIG. 5 is a flowchart showing image processing in the present invention.
FIG. 6 is a diagram illustrating a conversion source image.
FIG. 7 is a diagram showing a sampling period.
FIG. 8 is a diagram illustrating the number of sampling pixels.
FIG. 9 is a diagram illustrating a relationship between a conversion source image and pixels to be sampled.
FIG. 10 is a flowchart illustrating an outline of contrast enlargement processing.
FIG. 11 is a diagram showing the aggregated luminance distribution and the enlarged luminance distribution.
FIG. 12 is a diagram illustrating a moving direction of a target pixel.
FIG. 13 is a flowchart illustrating an outline of saturation enhancement processing.
FIG. 14 is a schematic diagram of a total state of saturation distribution.
FIG. 15 is a diagram showing the relationship between saturation A and saturation enhancement index S.
FIG. 16 is a diagram showing a concept to which enhancement suppression processing according to the present embodiment is applied.
FIG. 17 is a diagram illustrating a concept to which enhancement suppression processing according to a modification is applied.
FIG. 18 is a diagram illustrating a concept to which enhancement suppression processing according to another modification is applied.
FIG. 19 is a diagram illustrating a concept to which enhancement suppression processing is applied using a conversion table in another modified example.
FIG. 20 is a diagram illustrating a concept to which enhancement suppression processing is applied by setting a non-interference area.
[Explanation of symbols]
10. Image input device
11 ... Scanner
12 ... Digital still camera
12a ... Digital still camera
12a1 ... Optical system
12a2 ... Photoelectric conversion unit
12a3 ... control unit
12a4 ... Image memory
12a5 ... Image correction unit
14 ... Video camera
20 Image processing apparatus
21 ... Computer
21a1 ... Rasterizer
21a2 ... Color converter
21a3 ... gradation conversion section
21b ... Image correct module
22 ... Hard disk
30. Image output device
31 ... Printer
32 ... Display

Claims (12)

Contrast expansion means for expanding the luminance distribution in the image data;
Saturation enhancement means for enhancing the saturation of each pixel in the image data;
One of the parameter representing the degree of expansion of the luminance distribution in the contrast enlarging means and the parameter representing the degree of saturation enhancement in the saturation enhancing means is a temporary parameter, and the other parameter and the temporary parameter are automatically used. And an emphasis processing suppression means for converting the temporary parameter into a parameter for suppressing the operation,
The image processing apparatus characterized in that the contrast enlarging means and the saturation emphasizing means convert the image data so as to perform respective processing using the converted parameter and the other parameter. .   The image processing apparatus according to claim 1, wherein the enhancement processing suppression unit suppresses the saturation enhancement operation when attempting to perform a luminance distribution expansion operation and a saturation enhancement operation. An image processing apparatus.   The image processing apparatus according to claim 1, wherein the enhancement processing suppression unit suppresses the luminance distribution expansion operation when attempting to perform the luminance distribution expansion operation and the saturation enhancement operation. An image processing apparatus.   The image processing apparatus according to claim 1, wherein the enhancement processing suppression unit suppresses the luminance distribution enlargement operation and the saturation enhancement operation to be performed each other. .   5. The image processing apparatus according to claim 1, wherein the enhancement processing suppression unit includes a parameter representing a degree of expansion of a luminance distribution in the contrast enlarging unit and saturation enhancement in the saturation enhancement unit. An image processing apparatus characterized in that, based on a parameter representing a degree, an association is performed such that when one is large, the other is small.   6. The image processing apparatus according to claim 1, wherein one or both of the contrast enlarging unit and the saturation emphasizing unit analyze image data and set the degree of enhancement. An image processing apparatus.   7. The image processing apparatus according to claim 6, wherein the contrast enlarging unit includes a luminance distribution detecting unit that detects a luminance distribution of the image data in units of pixels, and a reproducible range based on the detected luminance distribution. An image processing apparatus comprising: contrast data conversion means for determining the degree of expansion of the same luminance distribution in the image and converting image data.   8. The image processing apparatus according to claim 6, wherein the saturation enhancement unit includes a saturation distribution totaling unit that totalizes the distribution of the saturation of each pixel in the image data, and the saturation distribution. Saturation emphasis degree judging means for judging the degree of emphasizing the saturation of the image data from the distribution state of the chroma summed by the summing means, and information representing the saturation in the image data based on the judged degree of conversion An image processing apparatus comprising: saturation data conversion means for correcting the image and converting it into new image data. The image processing apparatus according to any one of claims 1 to 7, wherein the contrast enlarging means calculates the luminance y and luminance before conversion when the effective luminance range that the image data can take is yrange. An image processing apparatus characterized in that a conversion destination luminance Y is obtained from a maximum value ymax and a minimum value ymin of a distribution range based on the following equation.
Y = ay + b
However, a = yrange / (ymax−ymin)
b = -a.ymin or yrange-a.ymax
In the above conversion equation, if Y <0, Y = 0, and if Y> range, Y = yrange. The image processing apparatus according to any one of claims 1 to 8, wherein the saturation enhancement unit includes:
When the image data is indicated by component values of a plurality of roughly equivalent hue components, the value obtained by multiplying the difference value between each hue component and luminance by a predetermined enhancement coefficient is added to the same hue component, thereby converting the saturation. An image processing apparatus characterized by   In executing the contrast enlargement process for enlarging the luminance distribution in the image data and the saturation enhancement process for enhancing the saturation of each pixel in the image data, the parameter indicating the degree of expansion of the luminance distribution in the contrast enlargement process and the saturation One of the parameters representing the degree of saturation enhancement in the degree enhancement processing is set as a temporary parameter, and the other parameter and the temporary parameter are used when performing the luminance distribution expansion operation and the saturation enhancement operation. And automatically converting the temporary parameter to a parameter that suppresses the operation, and converting the image data so that each process is performed using the converted parameter and the other parameter. An image processing method characterized by the above. A medium on which image data is input by a computer and recorded with an image processing program for executing contrast expansion processing for expanding the luminance distribution in the image data and saturation enhancement processing for enhancing the saturation of each pixel in the image data Because
In executing the contrast enlargement process and the saturation enhancement process, one of a parameter representing the degree of expansion of the luminance distribution in the contrast enhancement process and a parameter representing the degree of saturation enhancement in the saturation enhancement process is assumed temporarily. As a parameter, when trying to carry out a brightness distribution expansion operation and a saturation enhancement operation, the temporary parameter is automatically changed from the other parameter and the temporary parameter to a parameter that suppresses the operation. A medium on which an image processing program is recorded, wherein the image data is converted so that each process is performed using the converted parameter and the other parameter.

Images