JP6500638B2 - Image processing apparatus and computer program - Google Patents

Description

  The present specification relates to image processing for performing unsharp mask processing on image data.

  2. Description of the Related Art Conventionally, unsharp mask processing for sharpening an image has been performed as image processing for improving the quality of an image to be printed. The unsharp mask processing can improve the image quality of an image including, for example, a photograph and the like by enhancing the sharpness of the image. For example, Patent Document 1 discloses that unsharp mask processing is used as edge enhancement processing on an image determined to be a natural image such as a photograph.

Japanese Patent Application Laid-Open No. 10-200778

  However, in the unsharp mask processing, processing time tends to be long because it is necessary to generate mask data using the values of pixels in the peripheral region of the target pixel. In the above-mentioned technology, since the device for reducing the processing time is not sufficiently devised, the processing time for generating mask data of the unsharp mask processing may be excessively long.

  The present specification discloses a new technique that can reduce processing time for generating mask data of unsharp mask processing.

  The technology disclosed in the present specification can be implemented as the following application example.

[Example 1 of application] (M × N) (M, N) in the peripheral range including the pixel for each of a plurality of pixels included in the acquisition unit for acquiring the original image data representing the original image and the plurality of pixels included in the original image N is a mask generation unit that calculates an average value of pixel values of 2 or more) as mask data corresponding to the pixel, and the peripheral range has M pixels in the first direction The mask generation unit and the plurality of pixels included in the original image, each of which is a rectangular range in which the number of pixels in the second direction intersecting the first direction is N. And an unsharp mask processing unit configured to generate processed image data by executing unsharp mask processing using mask data, wherein the mask generation unit is configured to generate a first range which is the peripheral range of the first pixel. Values of (M × N) pixels in First mask data corresponding to the first pixel is calculated using a first value which is the sum of the first and second values, and the (M.times.N) pixels in the first range are opposite to the first direction. A second value, which is located at the end of the direction and is the sum of the values of N pixels aligned along the second direction, and is adjacent to the first range in the first direction; The third value is calculated as a sum of the values of N pixels lined up in a direction, the second value is subtracted from the first value, and the third value is added to the third value. A fourth value which is a sum of values of (M × N) pixels in a second range which is the peripheral range of the second pixel adjacent to the first direction of one pixel is calculated, and the fourth value is calculated. An image processing apparatus that calculates second mask data corresponding to the second pixel using the second image data.

According to the above configuration, the fourth value is calculated by subtracting the second value from the first value and adding the third value. As a result, by adding the values of (M × N) pixels in the second range one by one, it is possible to reduce the calculation time compared to calculating the fourth value. Therefore, processing time for generating mask data of unsharp mask processing can be reduced.
Application Example 2
The image processing apparatus according to Application Example 1 is,
The mask generation unit
A fifth one of the (M × N) pixels in the first range is a sum of values of M pixels located at an end in the opposite direction of the second direction and aligned along the first direction. Calculate the value,
A sixth value is calculated, which is a sum of values of M pixels adjacent to the first range in the second direction and aligned along the first direction,
A third range which is the peripheral range of the third pixel adjacent to the second direction of the first pixel by subtracting the fifth value from the first value and adding the sixth value. Calculate a seventh value which is the sum of the values of (M × N) pixels within
The image processing device which calculates the 3rd mask data corresponding to the 3rd pixel using the 7th value.
Application Example 3
The image processing apparatus according to Application Example 1 or Application Example 2, wherein
An image processing apparatus, wherein M is an integer of 3 or more and N is an integer of 3 or more.
Application Example 4
The image processing apparatus according to any one of application examples 1 to 3;
The mask generation unit
L pixel groups each including L (where L is an integer of M or more) pixels aligned in the first direction including the first pixel and the second pixel, wherein L pixels are included; A total value of N pixels included in each pixel group for each of the L pixel groups including N pixels aligned in the second direction included in any of the peripheral range of pixels Calculate
The image processing apparatus calculates L mask data corresponding to the L pixels by addition processing and subtraction processing using L total values of the L pixel groups.
Application Example 5
The image processing apparatus according to any one of application examples 1 to 3;
The mask generation unit
After calculating the first mask data using the first value, the first value is erased from the memory,
The image processing apparatus, wherein the first value is calculated by multiplying the first mask data by (M × N) when calculating the fourth value after erasing the first value.
Application Example 6
The image processing apparatus according to any one of application examples 1 to 5, wherein
The unsharp mask processing unit is configured to determine whether the difference between the maximum luminance value and the minimum luminance value of the plurality of pixels in the peripheral range is within a specific range among the plurality of pixels in the original image. Image processing device that does not change the value of.
Application Example 7
The image processing apparatus according to Application Example 6, which is
The mask generation unit
When calculating the mask data for each of a plurality of pixels included in the original image, it is determined whether the difference is within the specific range for the pixel corresponding to the mask data,
The mask data corresponding to a pixel whose difference is not within the specific range is determined as an average value of pixel values within the peripheral range of the pixel,
The image processing apparatus, wherein the mask data corresponding to a pixel whose difference is within the specific range is determined as a value of the pixel.
Application Example 8
The image processing apparatus according to Application Example 6 or Application Example 7;
The mask generation unit
M maximum luminance values and M specified for each of the M pixel groups including the N pixels aligned in the second direction, which are M pixel groups in the first range Identifying the maximum brightness value and the minimum brightness value within the first range using the minimum brightness values
Using the maximum luminance value and the minimum luminance value within the specified first range, it is determined whether or not the difference is within the specific range for the first pixel,
Identifying a maximum luminance value and a minimum luminance value of one pixel group including N pixels adjacent to the first range in the first direction and arranged along the second direction;
Of the M maximum luminance values and the M minimum luminance values that have been identified, the value of one pixel group located at the opposite end of the first direction within the first range is excluded (M− 1) Maximum luminance values and minimum luminance values specified for one pixel group adjacent to the first range in the first direction with respect to the maximum luminance values and the (M-1) minimum luminance values And identifying the maximum luminance value and the minimum luminance value within the second range,
An image processing apparatus that determines whether the difference is within the specific range for the second pixel, using a maximum luminance value and a minimum luminance value within the specified second range.
Application Example 9
The image processing apparatus according to Application Example 8 is,
The image processing apparatus, wherein the specified range of the difference is at least one of a range in which the difference is smaller than a first reference and a range in which the difference is larger than a second reference.

  The technology disclosed in the present specification can be realized in various forms, for example, a printing apparatus, a control apparatus for the printing apparatus, an image processing method, and a computer program for realizing functions of these apparatuses and methods. The present invention can be realized in the form of a recording medium recording the computer program, and the like.

FIG. 2 is a block diagram showing the configuration of a computer 200 and a multifunction peripheral 100. 5 is a flowchart of print processing. It is a figure which shows an example of the original image OI represented by original image data. It is a flow chart of mask data generation processing of the 1st example. It is an enlarged view of the upper left vertex vicinity of the original image OI. It is an enlarged view of the vicinity of pixel P (0, b). It is a flowchart of sharpening processing. It is a flow chart of mask data generation processing of the 2nd example. It is a figure showing a part of object Ob2 containing character TX in original picture OI.

A. First embodiment:
A-1: Configuration of Image Processing Apparatus Next, an embodiment will be described based on an example. FIG. 1 is a block diagram showing the configuration of a computer 200 as an image processing apparatus and a multifunction peripheral 100 in the embodiment.

  The computer 200 is, for example, a personal computer and is a processor as a controller of the computer 200, a non-volatile storage device 220 such as a hard disk drive, a volatile storage device 230 such as a RAM, and operations such as a mouse and a keyboard. And a display unit 270 such as a liquid crystal display, and a communication unit 280. The computer 200 is communicably connected to an external device such as the MFP 100 via the communication unit 280.

  The volatile storage device 230 provides a buffer area 231 for temporarily storing various intermediate data generated when the CPU 210 performs processing. The non-volatile storage device 220 stores a computer program CP. In the present embodiment, the computer program CP is a printer driver program for controlling a printer unit 130, which will be described later, of the MFP 100, and is provided in the form of being downloaded from a server. Alternatively, the computer program CP may be provided in the form of being stored on a DVD-ROM or the like. The CPU 210 executes a printing process described later by executing the computer program CP.

  The multifunction peripheral 100 generates a scan data by optically reading a document using an image sensor, and a printer that prints an image on a printing medium such as paper by a predetermined method (for example, ink jet, laser). The control unit 110 includes a unit 130, a CPU that controls the scanner unit 120 and the printer unit 130, and a memory.

A-2: Printing Process FIG. 2 is a flowchart of the printing process. The printing process is started based on the user's start instruction when, for example, the computer program CP is executed in the computer 200 and the printer driver is activated.

  In S10 and S20, the CPU 210 acquires original image data. First, in S10, image data representing an image to be printed is acquired. The image data is, for example, one piece of image data selected from among a plurality of image data stored in the non-volatile storage device 220 based on user's designation. In S20, the CPU 210 executes rasterization processing on the acquired image data to generate original image data. The original image data is bitmap data including a plurality of pixels, and more specifically, is RGB image data representing a color for each pixel by RGB values. The RGB values are tone values of three color components (hereinafter also referred to as component values), that is, color values of an RGB color system including R value, G value, and B value. The R value, the G value, and the B value are, for example, gradation values of 256 gradations.

  FIG. 3 is a diagram showing an example of the original image OI represented by the original image data. The original image OI in FIG. 3 includes three objects Ob1 to Ob3 and a background BG. An object Ob1 represents a picture including a person HN. The object Ob2 represents a table including the character TX. The object Ob3 represents a drawing, specifically, a pie chart.

  In S30, the CPU 210 executes mask data generation processing for generating mask data used in the unsharp mask processing in S40. In the mask data generation process, corresponding mask data is generated for each of the plurality of pixels included in the original image OI. The mask data is an average value of values of (M × N) (M and N are integers of 2 or more) pixels in a peripheral range CA described later of the corresponding pixel in the original image OI. Details of the mask data generation process will be described later.

  At S40, the CPU 210 executes a sharpening process. The sharpening process is a process of generating processed image data by performing an unsharp mask process on each of a plurality of pixels included in the original image OI using corresponding mask data. The processed image represented by the processed image data has high sharpness compared to the original image OI, and in particular, the image quality of the object Ob1 indicating a picture in the original image OI is improved. The processed image data is RGB image data in the same manner as the original image data. Details of the sharpening process will be described later.

  At S50, the CPU 210 executes color conversion processing on the processed image data. Thus, the RGB values of each pixel of the processed image data are converted into color values including a plurality of component values corresponding to a plurality of printing materials. In this embodiment, RGB values are converted to CMYK values including four component values of C (cyan), M (magenta), Y (yellow), and K (black). The color conversion process is performed with reference to a color conversion profile (not shown) stored in advance in the non-volatile storage device 220. The color conversion profile is information defining the correspondence between RGB values and CMYK values, and more specifically, is a look-up table.

  In S60, the CPU 210 executes halftone processing on the processed image data after the color conversion processing, and generates dot data representing the dot formation state for each pixel and for each color material. The value of each pixel included in the dot data indicates, for example, any of the formation states of four dots of “large dot”, “medium dot”, “small dot”, and “no dot”. Instead of this, the value of each pixel included in the dot data may indicate either of the formation state of two dots of “dot present” and “dot absent”.

  In S70, the CPU 210 generates a print job using dot data. For example, the CPU 210 executes a process of rearranging dot data in the order used when printing is performed using the printer unit 130, and a process of adding a printer control code and a data identification code to the dot data. As a result, a print job interpretable by the multifunction peripheral 100 is generated. In S80, the CPU 210 outputs the generated print job to the multifunction peripheral 100. The printer unit 130 of the multifunction machine 100 prints an image based on the print job output from the computer 200.

A-3: Mask Data Generation Process The mask data generation process of S30 of FIG. 2 will be described. As described above, the mask data generation process is a process of generating mask data for each of the plurality of pixels in the original image OI using the values of the plurality of pixels in the peripheral range CA of the pixel.

  FIG. 5 is an enlarged view of the vicinity of the top left corner of the original image OI. Each of the plurality of rectangles arranged in a grid in FIG. 5 indicates a pixel in the original image OI. As shown in FIG. 5, the direction from the left to the right of the original image OI is called the + X direction, and the opposite direction to the + X direction is called the −X direction. Further, the direction from the upper side to the lower side of the original image OI is referred to as the + Y direction, and the opposite direction to the + Y direction is referred to as the −Y direction. From the end of the original image OI in the −X direction (left end in FIG. 5) to the + X direction, an X coordinate is attached to each pixel. In addition, a Y coordinate is added to each pixel in the + Y direction from the end in the −Y direction (upper end in FIG. 5). A pixel whose X coordinate is “a” and whose Y coordinate is “b” is represented as P (a, b) (a and b are integers of 0 or more). For example, the pixel at the top left vertex of the original image OI is represented as P (0, 0). Similarly, a target pixel which is one pixel set from a plurality of pixels of the original image OI is represented as a target pixel TP (a, b) using the coordinates (a, b) of the target pixel.

  Here, the peripheral range CA (a, b) of the pixel P (a, b) will be described. As shown in FIG. 5, the peripheral range CA (a, b) of one pixel P (a, b) is a range of a predetermined size including the pixel P (a, b). Specifically, the peripheral range CA (a, b) of the pixel P (a, b) is a rectangle including (11 × 11), ie, 121 pixels centered on the pixel P (a, b) Range. The number of pixels in the + X direction of the peripheral range CA in the present embodiment is 11, and the number of pixels in the Y direction of the peripheral range CA is 11. The total value of the values of 121 pixels in the peripheral range CA (a, b) of the pixel P (a, b) is referred to as the peripheral total value TM (a, b) of the pixel P (a, b).

  As shown in FIG. 5, the peripheral range CA (a, b) includes 11 columns C (a-5) to C (a + 5) whose X coordinates are (a-5) to (a + 5). . Each of the eleven columns C (a-5) to C (a + 5) includes eleven pixels arranged along the + Y direction. The total value of the values of the eleven pixels included in each of the eleven columns C (a-5) to C (a + 5) is TV (a-5) to TV (a + 5).

  FIG. 4 is a flowchart of mask data generation processing according to the first embodiment. This flowchart shows mask data generation processing for one component value of RGB values. In practice, mask data generation processing is executed for each component of the RBG value to generate mask data MDr, MDg, and MDb of each component of RGB for each pixel. Hereinafter, among the RGB values of the pixel, the component value to be processed is also simply referred to as the pixel value. The mask data of the component to be processed is also simply referred to as mask data MD.

  In S105, the CPU 210 sets the pixel of interest TP (a, b) to the pixel P (0, 0) at the upper left of the original image OI.

  In S110, the CPU 210 adds the total value TV (-5) of each column for the eleven columns C (-5) to C (+5) in the peripheral range CA (0, 0) of the pixel of interest TP (0, 0). ) To calculate TV (+5). Here, since the pixel of interest TP (0, 0) is the upper left pixel of the original image OI, in the peripheral range CA (0, 0), the pixel of interest TP (0, 0) is in the −X direction from FIG. There is no pixel in the -Y direction (upper side in FIG. 5) of the pixel on the left side of FIG. As described above, when an area where no pixel is present is included in the peripheral range CA, the process proceeds on the assumption that there is a pixel having a specific value in the area. The calculation of the sum values TV (-5) to TV (+5) of each column of this step is also performed under this assumption. In the present embodiment, "255" is used as the specific value. That is, assuming that there is a white pixel around the original image OI, mask data generation processing is performed. Alternatively, a value indicating the background of the original image OI, for example, an average value of a plurality of pixels along the outer edge of the original image OI may be used as the specific value.

  In S115, the CPU 210 calculates the peripheral total value TM (0, 0) of the pixel of interest TP (0, 0) by adding the total values TV (-5) to TV (+5) of each column. The total values TV (-5) to TV (+5) of the respective columns are held without being erased from the buffer area 231 even after the peripheral total value TM (0, 0) is calculated. These ten values are acquired from the buffer area 231 in S135 described later, and calculation of the peripheral total value TM (a, b) of the second and subsequent target pixels TP (a, b) in S145 described later Because it is used for

  The processes of S120 to S145 described below are repeatedly executed while changing the pixel of interest TP, and therefore, the process for the pixel of interest TP (a, b) will be generally described. In the initial processing of S120 to S145, the target pixel TP (a, b) is the pixel P (0, 0).

  In S120, the mask data MD (a, b) of the pixel of interest TP (a, b) is calculated using the peripheral total value TM (a, b). Specifically, the CPU 210 divides the peripheral sum value TM (a, b) by the number PN of pixels included in the peripheral range (a, b) (121 in the present embodiment) to obtain mask data. Calculate MD (a, b) (MD (a, b) = TM (a, b) / PN). The surrounding total value TM (a, b) used in the initial S120, that is, the surrounding total value TM (0, 0) is a value calculated in S115. The peripheral total value TM (a, b) used in the second and subsequent S120 is a value calculated in S145 or S175 described later. Note that the peripheral sum value TM (a, b) used for calculating the mask data MD (a, b) is the peripheral sum value TM (a + 1) of the next target pixel TP (a + 1, b) in S145 described later. And b) are stored in the buffer area 231.

  In S125, the CPU 210 determines that the pixel of interest TP (a, b) is the final pixel in the + X direction, that is, a pixel located at the end of the line along the + X direction (hereinafter also simply referred to as line) in the process It is determined whether or not If the pixel of interest TP (a, b) is not the final pixel in the + X direction (S125: NO), the process proceeds to S130, and the pixel of interest TP (a, b) is the final pixel in the + X direction If not (S125: YES), the process proceeds to S150.

  In S130, the CPU 210 moves the pixel of interest TP (a, b) by one in the + X direction. That is, the pixel P (a + 1, b) adjacent to the target pixel TP (a, b) in the + X direction is set as a new target pixel TP (a, b) (a = a + 1).

  In S135, the CPU 210 selects 11 pieces from the column C (a-6) located at the end of the −X direction of the peripheral range CA (a−1, b) of the previous target pixel TP (a−1, b) The total value TV (a-6) of the values of the pixels of is acquired. Hereinafter, the total value of the values of the eleven pixels included in one column in the peripheral range CA will be simply expressed as “the total value of the corresponding column”. Column C (a-6) is a portion hatched in FIG. 5 by single hatching. The total value TV (a-6) is calculated to calculate the peripheral total value TM of the target pixel TP that has been processed up to this point. Specifically, it is calculated in S140 (described later) which has been executed up to this point or S115 described above, and is stored in the buffer area 231. For example, when the current target pixel TP (a, b) is the pixel P (1, 0), the obtained total value TV (a-6) is calculated in S115 and the total value TV (-5) ). When the current target pixel TP (a, b) is the pixel P (30, 0), the obtained total value TV (a-6) is the target pixel (a, b) being the pixel P (a, b). When it is 19, 0), it is the total value TV (24) calculated in S140.

  Note that as a modification, in this step, the CPU 210 calculates the total value TV (a-6) using the values of the eleven pixels in the column C (a-6) to obtain the total value TV. (A-6) may be acquired. In this case, although the amount of calculation increases more than in the present embodiment, it is not necessary to hold the total value TV calculated in S115 and S140 until it is acquired in this step, so the necessary memory amount ( For example, the capacity of the buffer area 231 can be reduced.

  In S140, the CPU 210 calculates the total value TV (a + 5) of the column C (a + 5) of the end in the + X direction of the peripheral range CA (a, b) of the current pixel of interest TP (a, b). This column C (a + 5) is a portion that is double hatched in FIG. The column C (a + 5) can also be referred to as a column adjacent to the end of the peripheral range CA (a-1, b) of the previous target pixel TP (a-1, b) in the + X direction.

In S145, the CPU 210 calculates the peripheral total value TM (a, b) of the current target pixel TP (a, b). Specifically, the total value TV (a-6) acquired in S135 is subtracted from the peripheral total value TM (a-1, b) of the previous target pixel TP (a-1, b), By adding the total value TV (a + 5) calculated in S140, the peripheral total value TM (a, b) is calculated. That is, the calculation formula of the marginal sum value TM (a, b) is represented by the following formula (1).
TM (a, b) = TM (a-1, b) -TV (a-6) + TV (a + 5) (1)

  In addition, after the calculation of the peripheral total value TM (a, b), the peripheral total value TM (a-1, b) of the previous target pixel TP (a-1, b) and the total value TV acquired in S135 Since (a-6) becomes unnecessary, it is erased from the buffer area 231.

  When the peripheral total value TM (a, b) is calculated in S145, the CPU 210 returns the process to S120.

  If the pixel of interest TP (a, b) is the final pixel in the + X direction (S125: YES), the CPU 210 proceeds to S150 to select the current pixel of interest TP (a, b) as the final pixel in the + Y direction. That is, it is determined whether it is the last pixel to be processed. If the current target pixel TP (a, b) is the final pixel in the + Y direction (S150: YES), the CPU 210 ends the mask data generation process.

  If the pixel of interest TP (a, b) is not the final pixel in the + Y direction (S150: NO), the CPU 210 shifts the pixel of interest TP (a, b) by one in the + Y direction in S155. And move to the first pixel in the X direction (the end in the −X direction) (a = 0, b = b + 1). That is, the pixel P at the end of the −X direction of the line adjacent to the + Y direction of the line in which the target pixel TP (a, b) is located is set as a new target pixel TP. The newly set target pixel TP located at the beginning of the line (that is, a = 0) is expressed as a target pixel TP (0, b).

  FIG. 6 is an enlarged view of the vicinity of the pixel of interest TP (0, b), that is, the pixel P (0, b). In S160, the CPU 210 sets the eleven pixels included in the row R (b-6) positioned at the end of the -Y direction of the peripheral range CA (0, b-1) of the pixel P (0, b-1). The total value TH (b-6) of the values is calculated. The total value of the values of 11 pixels included in one row in the peripheral range CA is simply expressed as “the total value of the corresponding row”.

  The pixel P (0, b-1) is a pixel adjacent to the target pixel TP (0, b) (that is, the pixel P (0, b) in FIG. 6) in the -Y direction, as shown in FIG. . The pixel P (0, b-1) is one of the pixels already processed as the target pixel TP. Row R (b-6) is a portion hatched in FIG.

  In S165, in S140, the CPU 210 calculates a total value TH (b + 5) of the row R (a + 5) of the end in the + Y direction of the peripheral range CA (0, b) of the current pixel of interest TP (0, b). This row R (b + 5) is a portion that is double hatched in FIG. The row R (b + 5) can also be referred to as a row adjacent to the end of the peripheral range CA (0, b-1) of the pixel P (0, b-1) in the + Y direction.

  In S170, the CPU 210 uses the calculated mask data MD (0, b-1) for the pixel P (0, b-1) adjacent to the pixel of interest TP (0, b) in the -Y direction to The peripheral sum value TM (0, b-1) of (0, b-1) is calculated again. The peripheral total value TM (0, b-1) has already been calculated in S175 when the pixel of interest TP is the pixel P (0, b-1), but in S120 immediately after that This is because the mask data MD (0, b-1) is calculated using the peripheral total value TM (0, b-1) and then erased from the buffer area 231. Specifically, the mask data MD (0, b-1) is multiplied by the number PN (121 in this embodiment) of pixels included in the peripheral range (0, b-1) to obtain a mask. Data MD (0, b-1) is calculated.

  As a modification, the peripheral total value TM of the pixel at the head of the line (the pixel where a = 0) is stored in the buffer area 231 until the mask data MD is calculated for the pixel P adjacent to the + Y direction. It may be held. In this case, the process of calculating the surrounding total value TM (0, b-1) again in S170 can be omitted.

In S175, the CPU 210 calculates the peripheral total value TM (0, b) of the current target pixel TP (0, b). Specifically, the sum TH (b-6) calculated in S160 is subtracted from the peripheral sum TM (0, b-1) calculated in S170, and the sum calculated in S165 By adding TH (b + 5), the peripheral sum value TM (0, b) is calculated. That is, a calculation formula of the marginal sum value TM (0, b) is represented by the following formula (2).
TM (0, b) = TM (0, b-1)-TH (b-6) + TH (b + 5) (2)

  When the peripheral total value TM (0, b) of the current pixel of interest TP (0, b) is calculated at S175, the CPU 210 returns the process to S120.

  When the mask data generation process described above is executed for each of the three components of RGB, a plurality of mask data MDr, MDg, and MDb corresponding to the three components of RGB are included in the original image OI. It is generated for each of the number of pixels.

A-4: Sharpening Process The sharpening process of S40 of FIG. 2 will be described. In the sharpening process, as described above, the processed image data is generated by performing the unsharp mask process on each of the plurality of pixels included in the original image OI using the corresponding mask data. It is a process.

  FIG. 7 is a flowchart of the sharpening process. In S180, the CPU 210 selects one target pixel from the plurality of pixels included in the original image OI.

  In S185, the CPU 210 executes unsharp mask processing on the pixel of interest using mask data corresponding to the pixel of interest among the plurality of mask data generated in the mask data generation process of FIG.

Specifically, assuming that the RGB value before processing the pixel of interest is (Rin, Gin, Bin) and the mask data corresponding to the pixel of interest is (MDr, MDg, MDb), the RGB values after processing (Rout, Gout) , Bout) are represented by the following formulas (3) to (5).
Rout = Rin + (Rin−MDr) × K (3)
Gout = Gin + (Gin-MDg) x K (4)
Bout = Bin + (Bin−MDb) × K (5)
Here, K is a predetermined coefficient indicating a level for emphasizing sharpness, and in the present embodiment, K = 1.

  In S190, the CPU 210 determines whether all the pixels in the original image OI have been processed as the pixel of interest. If there is an unprocessed pixel (S190: NO), the CPU 210 returns to S180 to select an unprocessed pixel as a target pixel. If all the pixels have been processed (S190: YES), the CPU 210 ends the sharpening process. At this point, processed image data representing the processed image is generated.

  According to the first embodiment described above, the periphery which is the sum of the values of (11 × 11) pixels in the peripheral range (a−1, b) of the pixel P (a−1, b) in FIG. 5 The mask data MD (a-1, b) corresponding to the pixel P (a-1, b) is calculated using the total value TM (a-1, b) (S120 in FIG. 4). At this point, among the (11 × 11) pixels in the peripheral range (a−1, b), 11 pixels located at the end in the −X direction and aligned along the + Y direction (ie, FIG. The total value TV (a-6) of the values of 11 pixels in the column C (a-6) of the image data is calculated and held in the buffer area 231. Then, 11 pixels adjacent to the peripheral range CA (a-1, b) in the + X direction and aligned along the Y direction (that is, 11 pixels in the column C (a + 5) in FIG. 5) A total value TV (a + 5) of values is calculated (S140). Then, the total value TV (a-6) is subtracted from the calculated peripheral total value TM (a-1, b), and the total value TV (a + 5) is added to the pixel P in FIG. Peripheral total value TM (sum of values of (11 × 11) pixels in peripheral range CA (a, b) of pixel P (a, b) adjacent to + a direction of (a−1, b) a, b) are calculated (S 145). Then, mask data MD (a, b) corresponding to the pixel P (a, b) is calculated using the peripheral total value TM (a, b) (S 120). As a result, the calculation time can be reduced compared to calculating the peripheral sum value TM (a, b) by adding the values of (11 × 11) pixels in the peripheral range CA (a, b) one by one. . Therefore, the processing time for generating mask data can be reduced.

  Furthermore, among the (11 × 11) pixels in the peripheral range CA (0, b−1) of the pixel P (0, b−1) in FIG. A total value TH (b-6) of the values of the 11 pixels (that is, the row R (b-6) in FIG. 6) aligned along the line is calculated (S160). Then, 11 pixels adjacent to the peripheral range CA (0, b-1) in the + Y direction and arranged along the + X direction (that is, 11 pixels in the row R (b + 5) in FIG. 6) The total value TH (b + 5) of the values of is calculated (S165). Then, the total value TH (b-6) is subtracted from the peripheral total value TM (0, b-1) of the pixel P (0, b-1) calculated in S170, and the total value TH (b + 5) is calculated. Value of (11 × 11) pixels in the peripheral range CA (0, b) of the pixel P (0, b) adjacent to the pixel P (0, b−1) in the + Y direction. The peripheral total value TM (0, b) which is the sum of the above is calculated (S175). Then, mask data MD (0, b) corresponding to the pixel P (0, b) is calculated using the peripheral sum value TM (0, b) (S 120). As a result, the calculation time can be reduced compared to calculating the peripheral total value TM (0, b) by adding the values of (11 × 11) pixels in the peripheral range CA (0, b) one by one. . Therefore, therefore, the processing time for generating mask data can be further reduced.

  More specifically, the processing time for generating mask data according to the present embodiment is the case where peripheral total value TM is calculated by adding the values of all pixels in peripheral range CA one by one for each pixel. This is approximately 1 / 9.3 as compared with the processing time of

  Here, as the number L of pixels in the + X direction (L is an integer greater than or equal to M) of the original image OI, attention is focused on a specific raster line along the + X direction, that is, L pixels aligned along the + X direction. As understood from S110 and S140 in FIG. 4, the total values TV (0) to TV (L) of L columns C (0) to C (L) including one each of these L pixels are obtained. Each has been calculated. And, as understood from S115 and S145, the addition processing and the subtraction processing using these L total values TV (0) to TV (L) correspond to these L pixels. L mask data MD are calculated. As a result, mask data can be efficiently calculated using L total values TV (0) to TV (L). Note that L columns C (0) to C (L) are L pixel groups included in any one of L peripheral ranges CA of L pixels, and 11 pixels are arranged along + Y. It can be said that it is L pixel groups each including the pixel of.

  Furthermore, after the mask data MD (1, b-1) of the pixel P (1, b-1) is calculated in S145, the peripheral total value TM of the pixel P (0, b-1) used for the calculation is calculated. (0, b-1) are erased from the memory (specifically, the volatile storage device 230). Then, when the mask data MD (0, b) of the pixel P (0, b) is subsequently calculated, the peripheral total value TM (0, b-1) used for the calculation is the mask data MD (0). , B-1) by (11 × 11) times, ie, 121 times (S170). As a result, since it is not necessary to hold the peripheral sum value TM (0, b-1) in the buffer area 231 until the mask data MD (0, b) is calculated, the usage amount of the volatile storage device 230 It can be reduced.

  As understood from the above description, an example of the correspondence relationship will be described. The + X direction is an example of a first direction, and the + Y direction is an example of a second direction.

  Further, in the example of FIG. 5, the pixel P (a−1, b) is an example of a first pixel, and the pixel P (a, b) is an example of a second pixel. 1 and b) are examples of the first range, and the peripheral range CA (a, b) is an example of the second range. The mask data MD (a-1, b) is an example of first mask data, and the mask data MD (a, b) is an example of second mask data. The marginal total value TM (a-1, b) is an example of a first value, the total value TV (a-6) is an example of a second value, and the total value TV (a + 5) is a third value. The peripheral sum value TM (a, b) is an example of the fourth value.

  Further, in the example of FIG. 6, the pixel P (0, b-1) is an example of the first pixel, and the pixel P (0, b) is an example of the third pixel, and the peripheral range CA (0, b) is b-1) is an example of the first range, and the peripheral range CA (0, b) is an example of the third range. The mask data MD (0, b-1) is an example of first mask data, and the mask data MD (0, b) is an example of third mask data. The marginal sum value TM (0, b-1) is an example of a first value, the sum value TH (b-6) is an example of a fifth value, and the sum value TH (b + 5) is a sixth value The peripheral sum value TM (0, b) is an example of the seventh value.

B. Second Embodiment In the second embodiment, the mask data generation process is different from the mask data generation process of the first embodiment of FIG. The other processes are the same as in the first embodiment.

  FIG. 8 is a flowchart of mask data generation processing according to the second embodiment. In S205, the CPU 210 sets the pixel of interest TP (a, b) to the pixel P (0, 0) at the upper left of the original image OI.

  Since S210 to S220 are processing executed when the pixel at the head (end of the -X direction) of each raster line along the + X direction (pixel of a = 0) is the pixel of interest TP, the pixel of interest TP The process for (0, b) will be described. In the initial processing of S210 to S220, the target pixel TP (0, b) is the pixel P (0, 0).

  In S210, the CPU 210 sums TV (-5) to TV (+5) of 11 columns C (-5) to C (+5) of the peripheral range CA (0, b) of the pixel of interest TP (0, b). Calculate).

  In S215, the CPU 210 calculates the peripheral total value TM (0, b) in the peripheral range CA (0, b) by adding the 11 total values TV (-5) to TV (+5). As in the first embodiment, the total values TV (-5) to TV (+5) of each column are not erased from the buffer area 231 even after the peripheral total value TM (0, b) is calculated. , Is held.

  In S220, the CPU 210 calculates, for each of the eleven columns C (a-5) to C (a + 5), the luminance values of the eleven pixels using the RGB values of the eleven pixels included in each column. Then, the maximum luminance value and the minimum luminance value among the 11 luminance values calculated are specified in the buffer area 231. The specified maximum luminance value and minimum luminance value are held in the buffer area 231. The maximum luminance values of 11 columns C (-5) to C (+5) are YVmx (-5) to YVmx (+5), and the minimum luminance values of 11 columns C (-5) to C (+5) are It is set as YVmn (-5)-YVmn (+5).

  The processes of S225 to S260 are repeatedly executed while changing the pixel of interest TP, and therefore, the process for the pixel of interest TP (a, b) will be generally described.

  In S225, the CPU 210 specifies the maximum luminance value Ymx and the minimum luminance value Ymn among the luminance values of 121 pixels in the peripheral range CA (a, b) of the pixel of interest TP (a, b). At this point, the maximum luminance values YVmx (a-5) to YVmx (a + 5) of the eleven columns C (a-5) to C (a + 5) in the peripheral range CA (a, b) are the above-described S220 or It is specified in S255 described later and held in the buffer area 231. The CPU 210 specifies the maximum value of the eleven maximum luminance values YVmx (a-5) to YVmx (a + 5) as the maximum luminance value Ymx of the peripheral range CA (a, b). Similarly, at this time, the minimum luminance values YVmn (a-5) to YVmn (a + 5) of the eleven columns C (a-5) to C (a + 5) in the peripheral range CA (a, b) are specified. And is held in the buffer area 231. The CPU 210 specifies the minimum value of the eleven minimum luminance values YVmn (a-5) to YVmn (a + 5) as the minimum luminance value Ymn of the peripheral range CA (a, b).

  In S230, the CPU 210 calculates a difference ΔY between the maximum luminance value Ymx and the minimum luminance value YVmn specified in S225 (ΔY = Ymx−Ymn). Since the difference ΔY of the luminance values is a value indicating the height of the contrast of the image in the peripheral range CA, it is also referred to as the contrast ΔY.

  In S235, the CPU 210 determines whether the contrast ΔY is within the specific range SR. The specific range SR is a range that satisfies either the contrast ΔY being less than the lower threshold TH1 or the contrast ΔY being greater than the upper threshold TH2 (ΔY <TH1 or ΔY> TH2, , TH1 <TH2)). For example, the lower threshold TH1 is set to a value of 15% from the lower limit of the range that the contrast ΔY can take, and the upper threshold TH2 is set to a value from the lower limit of the range that the contrast ΔY can take to 70%. For example, when the luminance value of a pixel is represented by a value of 0 to 255, the range that the contrast ΔY can take is 0 to 255. In this case, for example, TH1 = 38 and TH2 = 192 are set.

  If the contrast ΔY is within the specific range SR (S235: YES), the CPU 210 determines the value of the pixel of interest TP (a, b) as the mask data MD as it is at S240. Then, if the contrast ΔY is not within the specific range SR (S235: NO), the CPU 210 uses the peripheral total value TM (a, b) at S245 in the same manner as S120 of FIG. The mask data MD (a, b) of (a, b) is calculated. Specifically, the CPU 210 divides the peripheral sum value TM (a, b) by the number PN of pixels included in the peripheral range (a, b) (121 in the present embodiment) to obtain mask data. Calculate MD (a, b) (MD (a, b) = TM (a, b) / PN).

  In S250, the CPU 210 determines whether the pixel of interest TP (a, b) is the final pixel in the + X direction. If the pixel of interest TP (a, b) is not the final pixel in the + X direction (S250: NO), the process proceeds to S255, and the pixel of interest TP (a, b) is the final pixel in the + X direction If not (S250: YES), the process proceeds to S270.

  In S255, the CPU 210 moves the pixel of interest TP (a, b) by one in the + X direction. That is, the pixel P (a + 1, b) adjacent to the target pixel TP (a, b) in the + X direction is set as a new target pixel TP (a, b) (a = a + 1).

  In S260, the CPU 210 calculates the luminance values of the eleven pixels included in the column C (a + 5) located at the end of the new target pixel TP (a, b) in the + X direction, and calculates these eleven pixels. Among the luminance values, the maximum luminance value YVmx (a + 5) and the minimum luminance value YVmn (a + 5) are specified.

  At S265, the CPU 210 executes the processing of S135 to S145 of FIG. 4 described above. After S265, the CPU 210 returns the process to S225.

  If the pixel of interest TP (a, b) is the final pixel in the + X direction (S250: YES), the CPU 210 checks the current pixel of interest TP (a, b) as the final pixel in the + Y direction at S270. That is, it is determined whether it is the last pixel to be processed. If the current target pixel TP (a, b) is not the final pixel in the + Y direction (S270: NO), the CPU 210 moves the target pixel TP (a, b) by one in the + Y direction at S275. The pixel is moved to the top pixel in the X direction (the end in the −X direction) (a = 0, b = b + 1). After S275, the CPU 210 returns the process to S210. If the current target pixel TP (a, b) is the final pixel in the + Y direction (S270: YES), the CPU 210 ends the mask data generation process.

  When the mask data MD (a, b) is determined to be the value of the corresponding pixel P (a, b) in S245, the unsharp mask processing for the pixel P (a, b) (FIG. 7) In S185), the value of the pixel P (a, b) is not changed. Explain the reason. It is assumed that the value of the pixel of the processed image is calculated in S185 of FIG. 7 according to the above formulas (3) to (5). In this case, the values (Rin, Gin, Bin) of the original pixel and the values (MDr, MDg, MDb) of the mask data are the same. The term becomes 0, and the original pixel value is maintained at the same value. As a result, when the mask data MD is determined to be the value of the corresponding pixel P in S245, the unsharp mask processing is not substantially performed on the pixel P.

  According to the second embodiment described above, among the plurality of pixels P (a, b) in the original image OI, for pixels in which the contrast ΔY of the peripheral range CA (a, b) is within the specific range SR, In the sharpening process, the pixel value is not changed. As a result, it is possible to reduce the disadvantage that the image quality is degraded by the unsharp mask processing.

  It will be described in more detail. FIG. 9 is a diagram showing a part of the object Ob2 including the character TX in the original image OI. When the unsharp mask processing is performed, the sharpness of an image such as a photograph is particularly enhanced, and the image quality is improved. On the other hand, if the unsharp mask processing is performed on all the pixels, in the processed image, a portion having a relatively high contrast, specifically, a region having a relatively light ground color, within the region. It is easy to generate the problem that the near area of the dark-colored character arranged in is brightened excessively. For example, it is assumed that the neighborhood area SA of the black character TX in FIG. 9 and the outside area OA of the neighborhood area SA have the same color in the original image OI. If unsharp mask processing is performed on all pixels, in the processed image, the neighborhood area SA is changed to a whitish color by being excessively brightened, and a color different from that of the outside area OA is generated. Occur.

  The reason is explained. The peripheral range CA of the pixels in the near area SA includes dark pixels that form characters, but the peripheral range CA of the pixels in the outer area OA does not include dark colors. For this reason, each value of mask data of pixels in the adjacent area SA (that is, average color values (MDr, MDg, MDb) of the peripheral range CA of the pixel) is each of mask data of pixels in the outer area OA. It is a value that indicates a color darker than the value (that is, a small value). As a result, when performing the unsharp mask processing, in the pixels in the near area SA, (Rin−MDr), (Gin−MDg), and (Gin−MDg) of the second term of the right side of the equations (3) The value of Bin−MDb) is larger than the pixels in the outer area OA. Therefore, if the unsharp mask processing is performed on the pixels in the vicinity area SA as usual, the component values of the processed RGB values (Rout, Gout, Bout) are changed to excessively large values. As a result, the color of the pixels in the neighboring area SA becomes excessively bright and whitish.

  In the second embodiment, when the contrast ΔY in the peripheral range CA (a, b) of the pixel P (a, b) is excessively high (that is, when ΔV> TH2), the contrast ΔY is Since it is determined that the pixel P (a, b) is within the specific range SR, the unsharp mask process is not substantially performed on the pixel P (a, b). Therefore, the unsharp mask process is not substantially executed on the pixels in the vicinity area SA of FIG. 9, so that the occurrence of the above-mentioned problems can be suppressed. As a result, it is possible to suppress the deterioration of the image quality caused by the unsharp mask processing, specifically, the problem that the periphery of the dark-colored character is excessively brightened, while enhancing the sharpness of the image.

  Furthermore, for example, the skin portion of the person HN in the original image OI of FIG. 2 has a relatively low contrast ΔY. When the unsharp mask processing is performed on such a part, for example, a disadvantage such as an increase in wrinkles present on the skin may occur, and the image quality of the original image OI may be degraded. In the second embodiment, when the contrast ΔY in the peripheral range CA (a, b) of the pixel P (a, b) is excessively low (that is, when ΔV <TH1), the contrast ΔY is Since it is determined that the pixel P (a, b) is within the specific range SR, the unsharp mask process is not substantially performed on the pixel P (a, b). Therefore, the unsharp mask process is not substantially executed on the skin portion of the person HN, so that the occurrence of the above-mentioned problems can be suppressed. As a result, it is possible to suppress the deterioration of the image quality caused by the unsharp mask processing, specifically, the defect in which the wrinkles of the skin of the person HN are emphasized while enhancing the sharpness of the image.

  Furthermore, in the second embodiment, when the mask data MD is calculated for each of the plurality of pixels P included in the original image OI, the contrast ΔY is within the specific range SR for the pixel corresponding to the mask data MD. It is determined whether there is any (S235). Then, the mask data MD corresponding to the pixel whose contrast ΔY is not within the specific range SR is determined to be the average value of the values of the pixels within the peripheral range of the pixel (S245). Then, the mask data MD corresponding to the pixel whose contrast ΔY is within the specific range SR is determined as the value of that pixel (S240). In this way, even if the unsharp mask processing is performed on the pixel in S185 of FIG. 7 by determining the mask data MD of the pixel whose contrast ΔY is within the specific range SR as the value of the pixel, The value of the pixel can be prevented from being changed by unsharp masking.

  Furthermore, in the second embodiment, the eleven maximum luminances specified for each of the eleven columns C (a-6) to (a + 4) in the peripheral range CA (a-1, b) of FIG. Using the values YVmx (a-6) to YVmx (a + 4) and the 11 minimum luminance values YVmn (a-6) to YVmn (a + 4), the maximum in the peripheral range CA (a-1, b) The luminance value Ymx and the minimum luminance value Ymn are identified (S225). Then, using the maximum luminance value Ymx and the minimum luminance value Ymn in the peripheral range CA (a-1, b), whether or not the contrast ΔY is within the specific range SR for the pixel P (a-1, b) Is determined (S235). Then, the maximum luminance value YVmx (a + 5) of a column C (a + 5) including 11 pixels adjacent to the peripheral range CA (a-1, b) in FIG. 5 along the + Y direction and adjacent to the peripheral range CA (a-1, b) The minimum luminance value YVmn (a + 5) is specified (S260). Eleven maximum luminance values YVmx (a-5) to YVmx (a + 5) specified for each of the eleven columns C (a-5) to (a + 5) in the peripheral range CA (a, b) of FIG. 5 And the 11 minimum luminance values YVmn (a-5) to YVmn (a + 5), the maximum luminance value Ymx and the minimum luminance value Ymn in the peripheral range CA (a, b) are identified. (S225). The eleven maximum luminance values YVmx (a-5) to YVmx (a + 5) are the peripheral range CA (of the eleven maximum luminance values YVmx (a-6) to YVmx (a + 4) used in the previous S225). Ten maximum luminance values YVmx (a-5) to YVmx (a + 4) excluding the values of one column C (a-6) located at the end in the -X direction in a-1, b); This is one maximum luminance value YVmx (a + 5) specified in S260 thereafter. The eleven minimum luminance values YVmn (a-5) to YVmn (a + 5) are the peripheral range CA of the eleven minimum luminance values YVmn (a-6) to YVmn (a + 4) used in the previous S225. Ten minimum luminance values YVmn (a-5) to YVmn (a + 4) excluding the values of one column C (a-6) located at the end in the -X direction in a-1, b), This is one minimum luminance value YVmn (a + 5) specified in the subsequent S260. Then, using these values YVmn (a-5) to YVmn (a + 5) and YVmn (a-5) to YVmn (a + 5), the maximum luminance value Ymx and the minimum luminance value in the peripheral range CA (a, b) Ymn is identified (S225). Then, using the maximum luminance value Ymx and the minimum luminance value Ymn in the specified peripheral range CA (a, b), whether or not the contrast ΔY is within the specific range SR for the pixel P (a, b) It is determined (S235). As a result, when mask data is generated, the processing time for determining whether the contrast ΔY is within the specific range SR can be shortened for each of the plurality of pixels in the original image OI.

  Furthermore, as described above, the specific range SR is a range in which the contrast ΔY is smaller than the lower threshold TH1 (ΔY <TH1) and a range in which the contrast ΔY is larger than the upper threshold TH2 (ΔY> TH2). As a result, it is possible to suppress the deterioration of the image quality caused by the unsharp mask processing described above. As a modification, the specific range SR may be only in the range of ΔY <TH1, or may be only in the range of ΔY> TH2. In other words, the specific range SR is preferably at least one of the range of ΔY <TH1 and the range of ΔY> TH2.

C. Modification:
(1) In the above embodiments, the peripheral range CA (a, b) is a square range including (11 × 11) pixels, but is not limited to this. In general, the peripheral range CA (a, b) is a rectangular range including (M × N) (M and N are integers of 2 or more) pixels, and the number of pixels in the + X direction is M It is preferable that it is a rectangular range in which the number of pixels is N and the number of pixels in the + Y direction is N. For example, the peripheral range CA may be a square range including (9 × 9) pixels, or may be a rectangular range including (5 × 7) pixels.

  Here, the processing time for generating mask data according to the present embodiment is compared with the comparative example in which the peripheral total value TM is calculated by adding the values of all the pixels within the peripheral range CA one by one for each pixel. Show the results. As a result of investigating processing time about a case where peripheral range CA (a, b) is (Q x Q) pieces of squares (Q is an integer of 2 or more and 12 or less), processing time of this example relative to the comparative example Is approximately 1, 1 / 1.8, 1 / 2.7, 1 / 3.6, 1 / 4.5, 1 / 5.4, 1/6 when Q = 2 to 12, respectively. It was .4, 1 / 7.4, 1 / 8.3, 1 / 9.3, 1 / 10.3. From this result, it is preferable that M is an integer of 3 or more and N is an integer of 3 or more for the size (M × N) of the peripheral range CA (a, b). In this case, the processing time can be effectively shortened. Also, it was found that as M and N become larger, the degree to which the processing time can be shortened becomes larger.

(2) In the mask data generation process of each of the above embodiments, the target pixel TP (a, b) is sequentially selected from the end in the −X direction toward the + X direction for one line along the + X direction, After the processing of the final pixel in the + X direction of the raster line is completed, the processing is performed on the pixels on the line adjacent to the + Y direction of the line. Instead of this, for one line along the + Y direction, the pixel of interest TP (a, b) is sequentially selected from the end in the −Y direction toward the + Y direction, and the final pixel in the + Y direction of the line After the processing is completed, processing may be performed on pixels on the line adjacent to the + X direction of the line.

(3) In the second embodiment, whether or not the contrast ΔY is within the specific range SR is determined when generating mask data in the mask data generation process for each pixel in the original image OI. There is. Instead of this, in the sharpening process of FIG. 7, for each pixel, it is determined whether or not the contrast ΔY is within the specific range SR, and the pixel determined that the contrast ΔY is within the specific range SR On the other hand, the unsharp mask processing may be performed on the pixels for which the contrast ΔY is determined not to be within the specific range SR without performing the unsharp mask processing.

(4) In the above embodiments, the output of the processed image data generated in S40 of FIG. 2 is controlled by using the processed image data to control the MFP 100 (ie, generate a print job). The print job is transmitted to the multifunction peripheral 100), and the processed image is printed on the multifunction peripheral 100. Alternatively, the processed image data generated at S40 may be output to the non-volatile storage device 220 and the processed image data may be stored in the non-volatile storage device 220. Alternatively, the processed image data may be transmitted to another device such as a storage server or another terminal device.

(5) As the color components adjusted by the unsharp mask processing, other various color components can be adopted instead of the three color components of RGB. For example, a luminance component may be employed. The CPU 210 generates, for example, image data representing color values in the YCbCr color space as original image data, and generates mask data for the color value (that is, luminance value) of the Y component of each pixel of the image data. good. Then, the CPU 210 may adjust the color value (that is, the luminance value) of the Y component of the image data by unsharp mask processing.

(6) The computer 200 as an image processing apparatus that executes the printing process of FIG. 2 may be an apparatus of a type different from that of a personal computer, such as the multifunction peripheral 100, a digital camera, a scanner, or a smartphone. When the MFP 100 executes the printing process of FIG. 2, printing using processed image data is performed using, for example, the printer unit 130 of the MFP 100. Further, the image processing apparatus that executes the printing process of FIG. 2 may be, for example, a server that acquires original image data from a user terminal or the multifunction peripheral 100 and executes image processing. In such a server, a plurality of computers that can communicate with each other via a network may share the function of the image processing apparatus one by one to realize one image processing function as a whole. In this case, the plurality of computers that can communicate with each other via the network correspond to the image processing apparatus.

(7) In each of the above embodiments, a part of the configuration realized by hardware may be replaced by software, and conversely, a part or all of the configuration implemented by software is replaced by hardware You may do so. For example, part of the processing executed by the CPU 210 of the computer 200 of FIG. 1 may be realized by a dedicated hardware circuit.

  Although the present invention has been described above based on the examples and modifications, the above-described embodiment of the present invention is for the purpose of facilitating the understanding of the present invention, and does not limit the present invention. The present invention can be modified and improved without departing from the spirit and the scope of the claims, and the present invention includes the equivalents thereof.

  100: MFP, 110: control unit, 110: CPU, 120: scanner unit, 130: printer unit, 200: computer, 210: CPU, 220: Nonvolatile storage device 230 Volatile storage device 231 Buffer area 260 Operation unit 270 Display unit 280 Communication unit YVmx Maximum luminance value YVmn: minimum luminance value, ΔY: contrast, CA: peripheral range, MD: mask data, OI: original image, TM: peripheral total value, CP: computer program, SR ... specific range, CA ... peripheral range

Claims (9)

An acquisition unit for acquiring original image data representing an original image;
For each of the plurality of pixels included in the original image, the average value of (M × N) (M and N are integers of 2 or more) pixels within the peripheral range including the pixel is Mask generation unit that calculates mask data corresponding to the image data, the peripheral range has M pixels in a first direction, and N pixels in a second direction that intersects the first direction. The mask generation unit being a rectangular range;
An unsharp mask processing unit that generates processed image data by performing unsharp mask processing on each of a plurality of pixels included in the original image using the corresponding mask data;
Equipped with
The mask generation unit
Calculating a first mask data corresponding to the first pixel using a first value which is a sum of values of (M × N) pixels in the first range which is the peripheral range of the first pixel; ,
A second one of (M × N) pixels in the first range, which is a sum of values of N pixels located at an end in the opposite direction of the first direction and aligned in the second direction. Calculate the value,
Calculating a third value which is a sum of values of N pixels adjacent to the first range in the first direction and arranged along the second direction;
A second range which is the peripheral range of the second pixel adjacent to the first direction of the first pixel by subtracting the second value from the first value and adding the third value. Calculate the fourth value which is the sum of the values of (M × N) pixels within
Calculating second mask data corresponding to the second pixel using the fourth value ;
The unsharp mask processing unit is configured to determine whether the difference between the maximum luminance value and the minimum luminance value of the plurality of pixels in the peripheral range is within a specific range among the plurality of pixels in the original image. Image processing device that does not change the value of . The image processing apparatus according to claim 1 , wherein
The mask generation unit
When calculating the mask data for each of a plurality of pixels included in the original image, it is determined whether the difference is within the specific range for the pixel corresponding to the mask data,
The mask data corresponding to a pixel whose difference is not within the specific range is determined as an average value of pixel values within the peripheral range of the pixel,
The image processing apparatus, wherein the mask data corresponding to a pixel whose difference is within the specific range is determined as a value of the pixel. An image processing apparatus according to claim 1 or 2 , wherein
The mask generation unit
A M number of pixel groups in the first range, the M of the maximum luminance value of the particular already for each of the second way the M pixel group including N pixels arranged along the direction respectively Identifying the maximum brightness value and the minimum brightness value within the first range using M minimum brightness values;
Using the maximum luminance value and minimum luminance value within the first range specified for the first stroke element, the difference is determined whether or not it is within the specified range,
Identifying a maximum luminance value and a minimum luminance value of one pixel group including N pixels adjacent to the first range in the first direction and arranged along the second direction;
Of the M maximum luminance values and the M minimum luminance values that have been identified, the value of one pixel group located at the opposite end of the first direction within the first range is excluded (M− 1) Maximum luminance values and minimum luminance values specified for one pixel group adjacent to the first range in the first direction with respect to the maximum luminance values and the (M-1) minimum luminance values And identifying the maximum luminance value and the minimum luminance value within the second range,
Using the maximum luminance value and minimum luminance value in the second range specified for the second stroke element, the difference is judged whether it is within the specified range, the image processing apparatus. The image processing apparatus according to claim 3 ,
The image processing apparatus, wherein the specified range of the difference is at least one of a range in which the difference is smaller than a first reference and a range in which the difference is larger than a second reference. The image processing apparatus according to any one of claims 1 to 4 , wherein
The mask generation unit
A fifth one of the (M × N) pixels in the first range is a sum of values of M pixels located at an end in the opposite direction of the second direction and aligned along the first direction. Calculate the value,
A sixth value is calculated, which is a sum of values of M pixels adjacent to the first range in the second direction and aligned along the first direction,
A third range which is the peripheral range of the third pixel adjacent to the second direction of the first pixel by subtracting the fifth value from the first value and adding the sixth value. Calculate a seventh value which is the sum of the values of (M × N) pixels within
The image processing device which calculates the 3rd mask data corresponding to the 3rd pixel using the 7th value. The image processing apparatus according to any one of claims 1 to 5 , wherein
An image processing apparatus, wherein M is an integer of 3 or more and N is an integer of 3 or more. The image processing apparatus according to any one of claims 1 to 6 , wherein
The mask generation unit
L pixel groups each including L (where L is an integer of M or more) pixels aligned in the first direction including the first pixel and the second pixel, wherein L pixels are included; A total value of N pixels included in each pixel group for each of the L pixel groups including N pixels aligned in the second direction included in any of the peripheral range of pixels Calculate
The image processing apparatus calculates L mask data corresponding to the L pixels by addition processing and subtraction processing using L total values of the L pixel groups. The image processing apparatus according to any one of claims 1 to 6 , wherein
The mask generation unit
After calculating the first mask data using the first value, the first value is erased from the memory,
The image processing apparatus, wherein the first value is calculated by multiplying the first mask data by (M × N) when calculating the fourth value after erasing the first value. An acquisition function of acquiring original image data representing an original image;
For each of the plurality of pixels included in the original image, the average value of (M × N) (M and N are integers of 2 or more) pixels within the peripheral range including the pixel is A mask generation function for calculating mask data corresponding to the image data, wherein the peripheral range has M pixels in a first direction and N pixels in a second direction intersecting the first direction. Said mask generation function being a rectangular range;
An unsharp mask processing function of generating processed image data by performing unsharp mask processing on each of a plurality of pixels included in the original image using the corresponding mask data;
On a computer,
The mask generation function is
Calculating a first mask data corresponding to the first pixel using a first value which is a sum of values of (M × N) pixels in the first range which is the peripheral range of the first pixel; ,
A second one of (M × N) pixels in the first range, which is a sum of values of N pixels located at an end in the opposite direction of the first direction and aligned in the second direction. Calculate the value,
Calculating a third value which is a sum of values of N pixels adjacent to the first range in the first direction and arranged along the second direction;
A second range which is the peripheral range of the second pixel adjacent to the first direction of the first pixel by subtracting the second value from the first value and adding the third value. Calculate the fourth value which is the sum of the values of (M × N) pixels within
Calculating second mask data corresponding to the second pixel using the fourth value ;
The unsharp mask processing function is performed on pixels for which the difference between the maximum luminance value and the minimum luminance value of the plurality of pixels in the peripheral range is within the specific range among the plurality of pixels in the original image. A computer program that does not change the value of .

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