JP2006115347A - Image processing apparatus, method, and program, and recording medium recording image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus capable of obtaining a proper black component amount without increasing required memory capacity. <P>SOLUTION: A K table consisting of two one-dimensional tables is stored, and these are used to obtain an optimum black generating amount. Since only the two one-dimensional tables are required as conversion tables, the memory size can be remarkably reduced, compared to a configuration for storing a two-dimensional table. Also, an offset region is set in the vicinity of an LUT 1 (gray axis), and when the maximum value MAX is on the gray axis or within the offset region, one-dimensional image data is considered as a gray image to obtain a black generating amount. In this way, the optimum black generating amount can be set even for a gray image disturbed by a disturbance. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an image processing apparatus that converts primary image data composed of a plurality of color components into secondary image data including a black component.

  In recent years, digitalization of OA equipment has rapidly progressed, and digital color image data is frequently generated by digital cameras, scanners, and personal computers. Accordingly, printing apparatuses (output devices; digital color copying machines, digital color printers, etc.) for printing such image data have been widely spread.

  There are various printing methods for such a printing apparatus (electrophotographic method, ink jet method, thermal transfer method, etc.), but in any method, it is necessary to print (output) an image with stable color reproducibility. is there. For this reason, digital image processing technology, particularly color conversion (color correction) processing is important.

  Here, the color conversion processing refers to color signals (for example, R (red), G (green), B (blue)) used in image data, and color signals (for example, C (cyan)) suitable for the printing apparatus. , M (magenta), Y (yellow)).

In the printing apparatus, not only CMY color materials (toner, ink, etc.) but also K (black) color materials may be used. This is because the use amount of the CMY color material can be reduced by using the K color material, and the gray reproducibility can be improved.
In this case, the printing apparatus generates a signal (black signal) corresponding to K (black) in addition to the CMY color signal by color conversion processing.

  However, the optimum black component amount (black signal amount) differs between printing (reproducing) an image composed of dark and vivid colors and printing an image composed of gray such as black characters (gray image). . For this reason, it is not easy to generate a black signal appropriately.

With regard to this problem, the technique described in Patent Document 1 calculates a difference (MAX−MIN) between the maximum value MAX and the minimum value MIN of the color-corrected CMY signal and the minimum value MIN. An appropriate black component amount corresponding to these values is obtained using a two-dimensional table (black component / undercolor removal two-dimensional LUT).
Thus, with this technology, both a vivid image and a gray image can be printed satisfactorily.
JP 2003-60929 A (publication date: February 28, 2003) JP 2001-223915 A (publication date: August 17, 2001)

  However, the technique disclosed in Patent Document 1 has a problem in that the amount of memory used in the printing apparatus increases because it is necessary to store a two-dimensional table.

  The present invention has been made in view of such conventional problems. An object of the present invention is to provide an image processing apparatus capable of obtaining an appropriate black component amount without increasing a necessary memory capacity.

In order to achieve the above object, a first image processing apparatus (first apparatus) of the present invention includes:
In an image processing apparatus for converting primary image data composed of a plurality of color components into secondary image data including a black component using a first parameter and a second parameter obtained from pixel values of the data,
A gray table in which a plurality of first parameters are associated with “a gray black component amount that is a black component amount corresponding to a gray image” suitable for each first parameter, a plurality of first parameters, A table storage unit for storing a high saturation table associated with “high saturation black component amount that is black component amount considering saturation” suitable for one parameter;
A parameter calculation unit for calculating the first parameter and the second parameter from the pixel value of the primary image data;
The gray black component amount and the high saturation black component amount suitable for the calculated first parameter are read from both the above tables, and are included in the secondary image data using the black component amount, the first parameter, and the second parameter. A black component calculation unit for determining the amount of black component to be generated,
The black component calculation unit is
The apparatus is characterized in that when the difference between the second parameter and the first parameter is within a predetermined offset range, the gray black component amount is set to be a black component amount included in the secondary image data. .

  The first apparatus is provided in an apparatus for processing a multicolor image such as a printing apparatus such as a digital color copying machine. Then, primary image data (for example, CMY data) that does not include a black component is converted into secondary image data (for example, CMYK data) that includes a black component.

In the first device, the amount of black component necessary for such conversion is calculated using two types of parameters (first parameter and second parameter) obtained from the pixel values of the primary image data. It has become.
Here, as these first and second parameters, for example, the maximum pixel value (MAX), the minimum pixel value (MIN), etc. in the primary image data can be used (for other examples, (See [Best Mode for Carrying Out the Invention] described later).

The first device includes a black component calculation unit for obtaining the black component amount to be included in the secondary image data from these two parameters.
The black component calculation unit obtains two reference black component amounts (gray black component amount and high saturation black component amount) from the first parameter obtained from the primary image data. Thereafter, the two black component amounts, the first parameter, and the second parameter are used to determine the black component amount to be included in the secondary image data.

Here, the gray black component amount is an optimal black component amount when the primary image data is assumed to be a gray image (an image in which the first parameter and the second parameter are the same).
On the other hand, the high saturation black component amount is an image in which the primary image data is highly saturated (an image having a large difference between the first parameter and the second parameter (for example, an image in which one of the parameters is 0 and the other is the maximum value). ) Is the optimum black component amount.

  Then, the black component calculation unit obtains a black component amount to be included in the secondary image data by an interpolation calculation using these two reference black component amounts and the first and second parameters ( The details of the interpolation operation will be described later (see [Best Mode for Carrying Out the Invention]).

In particular, in the first device, “a gray table in which a plurality of first parameters and gray-black component amounts suitable for each first parameter are associated”, and “a plurality of first parameters, Two one-dimensional tables called “high saturation tables in which high saturation black component amounts suitable for the first parameter are associated with each other” are stored.
Then, the black component calculation unit obtains a gray black component amount and a high saturation black component amount suitable for the first parameter of the primary image data using these two one-dimensional tables.

As described above, in the first device, only two one-dimensional tables are necessary for the conversion table necessary for obtaining the optimum black component amount.
Therefore, the memory size can be greatly reduced as compared with the configuration storing the two-dimensional table.

In the first device, the black component calculation unit determines whether or not the primary image data is a gray image, and when determining that the primary image data is a gray image, the black component amount read from the gray table is calculated. The amount of black component is set to be included in the secondary image data.
In particular, the black component calculation unit makes the above determination based on “whether or not the difference between the second parameter and the first parameter is within a predetermined offset range”.

That is, in the gray image, since all the color components have the same amount, the first parameter and the second parameter related to the pixel value have the same value.
However, if the primary image data is disturbed (for example, if the original image data is generated by reading an original image with a scanner, it will be subject to disturbances (scanner noise, etc.)) The components may vary, and there may be a difference between the first parameter and the second parameter.
In such a case, the black component amount obtained from the interpolation operation as described above is smaller than the gray black component amount.

Therefore, in the first device, when the difference between the first parameter and the second parameter is small (within a predetermined offset range), the primary image data is regarded as a gray image and the black component amount is obtained. .
As a result, the first device can set an optimal black component amount even for a gray image disturbed by a disturbance.

Further, such black generation processing in the first device can also be applied to undercolor removal processing.
That is, the second image processing apparatus (second apparatus) of the present invention is
With respect to primary image data composed of a plurality of color components, the first parameter and the second parameter obtained from the pixel values of this data are used to add black components and remove undercolor to convert the image data into secondary image data. In the image processing apparatus,
A gray table in which a plurality of first parameters are associated with a “gray undercolor removal amount that is an undercolor removal amount corresponding to a gray image” suitable for each first parameter; and a plurality of first parameters; A table storage unit that stores a high saturation table associated with “high saturation undercolor removal amount that is a lower color removal amount considering saturation” suitable for each first parameter;
A parameter calculation unit for calculating the first parameter and the second parameter from the pixel value of the primary image data;
A gray undercolor removal amount and a high saturation undercolor removal amount suitable for the calculated first parameter are read from both the above tables, and the primary image is read using these undercolor removal amount, the first parameter, and the second parameter. And an under color removal calculating unit for obtaining an under color amount to be removed from the data,
The under color removal calculation unit is
When the difference between the second parameter and the first parameter is within a predetermined offset range, the gray undercolor removal amount is set to be a lower color amount (undercolor removal amount) to be removed from the primary image data. It is the apparatus characterized by this.

Here, the removal of the under color will be described.
The color components of the secondary image data are the color component (previous component) and the black component of the primary image data. Therefore, when the primary image data is converted into the secondary image data, it is necessary to remove (subtract) the pixel value corresponding to the added black component from the previous component, which is the removal of the under color. Also, the amount of pixel value subtracted from the previous component is the under color removal amount.

As described above, the second device uses the two types of parameters (first parameter and second parameter) obtained from the pixel value of the primary image data for the lower color amount to be removed from the previous component. It comes to calculate.
Here, as these first and second parameters, the maximum pixel value (MAX), the minimum pixel value (MIN), etc. in the primary image data can be used, as in the first device.

The second apparatus includes a lower color removal calculation unit for obtaining the lower color amount to be removed from these two parameters.
The under color removal calculating unit obtains two reference removal amounts (a gray under color removal amount and a high saturation under color removal amount) from the first parameter obtained from the primary image data. Thereafter, the under color amount to be removed from the secondary image data is determined using these two reference removal amounts, the first parameter, and the second parameter.

Here, the gray under color removal amount is an optimum under color removal amount when it is assumed that the primary image data is a gray image (an image in which the first parameter and the second parameter are the same).
On the other hand, the high saturation under color removal amount is an optimum under color removal amount when it is assumed that the primary image data is a high saturation image (an image having a large difference between the first parameter and the second parameter).

  Then, the under color removal calculation unit obtains the under color removal amount to be included in the secondary image data by an interpolation operation using these two reference removal amounts and the first and second parameters. (This interpolation calculation is the same as the calculation for obtaining the black component in the first device).

Here, in particular, in the second device, “a gray table in which a plurality of first parameters and an under-gray color removal amount suitable for each first parameter are associated”, and “a plurality of first parameters; Two one-dimensional tables, “high saturation tables in which high saturation undercolor removal amounts suitable for the first parameters are associated with each other”, are stored.
The under color removal calculating unit obtains the gray under color removal amount and the high saturation under color removal amount suitable for the first parameter of the primary image data using these two one-dimensional tables.

As described above, in the second apparatus, only two one-dimensional tables are necessary for the conversion table necessary for obtaining the optimum undercolor removal amount.
Therefore, the memory size can be greatly reduced as compared with the configuration storing the two-dimensional table.

In the second apparatus, the under color removal calculating unit determines whether or not the primary image data is a gray image, and if it is determined that the image is a gray image, the under color removal read from the gray table is performed. The amount is set to be the undercolor removal amount to be included in the secondary image data.
In particular, the undercolor removal calculation unit makes the above determination based on “whether or not the difference between the second parameter and the first parameter is within a predetermined offset range”.

That is, in the gray image, since all the color components have the same amount, the first parameter and the second parameter related to the pixel value have the same value.
However, when the primary image data is disturbed, as described above, in the gray image such as the black character, the color component may vary, and the first parameter and the second parameter may be different.
In such a case, the under color removal amount obtained from the above interpolation calculation is smaller than the gray under color removal amount.

  Therefore, in the second device, when the difference between the first parameter and the second parameter is small (within a predetermined offset range), the primary image data is regarded as a gray image and the undercolor removal amount is obtained. Yes. Thereby, in the second device, it is possible to set an optimum undercolor removal amount even for a gray image disturbed by a disturbance.

Further, in the first device and the second device, the above-described offset range may be changed according to the value of the first parameter (for example, it is narrow when the first parameter is large and wide when it is small). May be)
In such a case, the black component calculation unit and the under color removal calculation unit may indicate that “a two-dimensional region (offset region; offset range of a plurality of first parameters) determined by a plurality of first parameter values and offset ranges thereof. By determining whether or not the second parameter is present in the area (consisting of the set), it is determined whether or not the primary image data is a gray image.

Moreover, it is preferable that the above-described offset range (or offset region) relating to the difference between the first parameter and the second parameter is a range that can be set by a calculation formula.
As described above, when the above range is set by a mathematical expression, it can be determined whether or not the second parameter is within the range without using a table or the like. For this reason, the storage capacity can be saved.

In addition, when the offset range is changed according to the value of the first parameter, the offset area determined from these is a relatively complicated shape (a shape that is not continuous but a shape divided into a plurality of locations, or a straight line. May not be possible).
In such a case, a high-order polynomial is required to accurately define (approximate) the offset region, and the amount of calculation, calculation time, and circuit configuration for calculating this equation will increase. There is also. Moreover, there is a possibility that it cannot be determined by a polynomial.

Therefore, when the offset area has a complicated shape, a value representing the offset area may be included as a table value.
That is, in this case, a table representing the correspondence relationship between the first parameter and the offset range is stored in advance. Then, the black component calculation unit reads the offset range with respect to the first parameter, and determines “whether or not the second parameter is within this range”. Therefore, with this configuration, this determination can be made at high speed.

Further, the first image processing method (first method) of the present invention includes:
In an image processing method for converting primary image data composed of a plurality of color components into secondary image data including a black component using a first parameter and a second parameter obtained from pixel values of the data,
A gray table in which a plurality of first parameters are associated with “a gray black component amount that is a black component amount corresponding to a gray image” suitable for each first parameter, a plurality of first parameters, A storage step of storing a high saturation table associated with “a high saturation black component amount that is a black component amount considering saturation” suitable for one parameter;
A parameter calculating step of calculating the first parameter and the second parameter from the pixel value of the primary image data;
The gray black component amount and the high saturation black component amount suitable for the calculated first parameter are read from both the above tables, and are included in the secondary image data using the black component amount, the first parameter, and the second parameter. A black component calculation step for obtaining a black component amount to be
The above black component calculation step is
The method is characterized in that when the difference between the second parameter and the first parameter is within a predetermined offset range, the gray black component amount is set to be a black component amount included in the secondary image data. is there.

This first method is an image processing method used in the first apparatus described above. Therefore, if the first method is used, the optimum black component amount can be obtained using two one-dimensional tables, so that the memory size can be greatly reduced as compared with the configuration storing two-dimensional tables. Become.
Further, when the difference between the first parameter and the second parameter is small (within a predetermined offset range), the primary image data is regarded as a gray image and the black component amount is obtained. However, it is possible to set an optimal black component amount.

The second image processing method (second method) of the present invention is as follows.
With respect to primary image data composed of a plurality of color components, the first parameter and the second parameter obtained from the pixel values of this data are used to add black components and remove undercolor to convert the image data into secondary image data. In the image processing method,
A gray table in which a plurality of first parameters are associated with a “gray undercolor removal amount that is an undercolor removal amount corresponding to a gray image” suitable for each first parameter; and a plurality of first parameters; A table storage step for storing a high saturation table associated with “high saturation undercolor removal amount that is a lower color removal amount considering saturation” suitable for each first parameter;
A parameter calculating step for calculating the first parameter and the second parameter from the pixel value of the primary image data;
A gray undercolor removal amount and a high saturation undercolor removal amount suitable for the calculated first parameter are read from both the above tables, and the primary image is read using these undercolor removal amount, the first parameter, and the second parameter. An under color removal calculating step for obtaining an under color amount to be removed from the data,
The under color removal calculation process is as follows.
When the difference between the second parameter and the first parameter is within a predetermined offset range, the gray undercolor removal amount is set to be a lower color amount to be removed from the primary image data. It is.

This second method is an image processing method used in the second device described above. Therefore, if the second method is used, the optimum undercolor removal amount can be obtained using two one-dimensional tables, so that the memory size can be greatly reduced as compared with the configuration storing two-dimensional tables. It becomes.
Further, when the difference between the first parameter and the second parameter is small (within a predetermined offset range), the primary image data is regarded as a gray image, and the undercolor removal amount is obtained, so that the gray image disturbed by the disturbance is obtained. Even for this, it is possible to set an optimum undercolor removal amount.

  The image processing program of the present invention is a computer-readable program for causing a computer to execute the steps of the first method or the second method.

By loading this image processing program into a computer capable of inputting (or generating) primary image data, each step of the first method or the second method can be performed by the computer.
Also, by storing this program on a computer-readable recording medium, the program can be easily stored and distributed.

As described above, the first image processing apparatus (first apparatus) of the present invention is
In an image processing apparatus for converting primary image data composed of a plurality of color components into secondary image data including a black component using a first parameter and a second parameter obtained from pixel values of the data,
A gray table in which a plurality of first parameters are associated with “a gray black component amount that is a black component amount corresponding to a gray image” suitable for each first parameter, a plurality of first parameters, A table storage unit for storing a high saturation table associated with “high saturation black component amount that is black component amount considering saturation” suitable for one parameter;
A parameter calculation unit for calculating the first parameter and the second parameter from the pixel value of the primary image data;
The gray black component amount and the high saturation black component amount suitable for the calculated first parameter are read from both the above tables, and are included in the secondary image data using the black component amount, the first parameter, and the second parameter. A black component calculation unit for determining the amount of black component to be generated,
The black component calculation unit is
The apparatus is characterized in that when the difference between the second parameter and the first parameter is within a predetermined offset range, the gray black component amount is set to be a black component amount included in the secondary image data. .

In the first apparatus, “a gray table in which a plurality of first parameters and gray black component amounts suitable for each first parameter are associated” and “a plurality of first parameters and each first parameter are suitable” In addition, two one-dimensional tables called “high saturation tables in which high saturation black component amounts are associated with each other” are stored.
Then, the black component calculation unit obtains a gray black component amount and a high saturation black component amount suitable for the first parameter of the primary image data using these two one-dimensional tables.

As described above, in the first device, only two one-dimensional tables are necessary for the conversion table necessary for obtaining the optimum black component amount.
Therefore, the memory size can be greatly reduced as compared with the configuration storing the two-dimensional table.

In the first device, the black component calculation unit determines whether or not the primary image data is a gray image, and when determining that the primary image data is a gray image, the black component amount read from the gray table is calculated. The amount of black component is set to be included in the secondary image data.
In particular, the black component calculation unit makes the above determination based on “whether or not the difference between the second parameter and the first parameter is within a predetermined offset range”.

That is, in the gray image, since all the color components have the same amount, the first parameter and the second parameter related to the pixel value have the same value.
However, if the primary image data is disturbed (for example, if the original image data is generated by reading an original image with a scanner, it will be subject to disturbances (scanner noise, etc.)) The components may vary, and there may be a difference between the first parameter and the second parameter.
In such a case, the black component amount obtained from the interpolation operation as described above is smaller than the gray black component amount.

  Therefore, in the first device, when the difference between the first parameter and the second parameter is small (within a predetermined offset range), the primary image data is regarded as a gray image and the black component amount is obtained. . As a result, the first device can set an optimal black component amount even for a gray image disturbed by a disturbance.

An embodiment of the present invention will be described.
FIG. 2 is a block diagram showing a schematic configuration of a digital color copying machine (the present copying machine) according to an embodiment of the present invention.
As shown in the figure, the copying machine includes a scanner unit 1, an image processing unit 2, a printing unit 3, an operation unit 4, and a control unit 5.

  The scanner unit (image output device) 1 includes an optical scanning unit, a document table, a CCD (Charge Coupled Device), etc. (all not shown). Then, the reflected light image from the original is read by the CCD, and analog image data (RGB data) of RGB (R: red, G: green, B: blue) is output.

The image processing unit (image processing apparatus) 2 has a function of converting RGB data output from the scanner unit 1 into CMYK digital image data (CMYK data) suitable for printing and outputting the data to the printing unit 3. Yes.
The detailed configuration of the image processing unit 2 will be described later.

  The printing unit (printing apparatus) 3 is an electrophotographic printer, and includes four photosensitive members and a fixing device (both not shown). Then, an electrostatic latent image corresponding to the CMYK data is formed on each photoconductor, and the image is printed by transferring and fixing the image onto a sheet (recording paper).

  The operation unit (operation panel) 4 is a touch panel in which a display screen including a liquid crystal display, setting buttons, ten keys, and the like (all not shown) are integrated. It has a function of accepting user instructions and showing the progress and results of printing processing to the user.

  The control unit 5 is a central part (CPU) of the copying machine that controls all operations of the copying machine. That is, the control unit 5 executes a document image reading process by the scanner unit 1, a CMYK data generation / output process by the image processing unit 2, and a printing process by the printing unit 3 based on an instruction from the user to the operation unit 4. To do.

Next, a detailed configuration of the image processing unit 2 will be described.
FIG. 3 is an explanatory diagram showing a configuration of the image processing unit 2.
As shown in this figure, the image processing unit 2 includes an A / D conversion unit 11, a shading correction unit 12, an input tone correction unit 13, a region separation processing unit 14, a color correction unit 15, and a black generation and under color removal unit 16. , A spatial filter processing unit 17, an output tone correction unit 18, and a tone reproduction processing unit 19.

The A / D (analog / digital) converter 11 converts analog RGB data output from the scanner unit 1 into a digital signal (digital RGB data) having 256 gradations (0 to 255).
The shading correction unit 12 performs processing for removing various distortions (distortion removal processing) caused by the illumination system, imaging system, and imaging system of the scanner unit 1 from the digital RGB data generated by the A / D conversion unit 11. It is something to apply.

The input tone correction unit 13 performs processing for adjusting color balance on the digital RGB data (RGB reflectance signal) that has been subjected to distortion removal processing by the shading correction unit 12.
The input tone correction unit 13 also has a function of converting the digital RGB data into a signal (density signal or the like) that is easy to handle for the image processing method employed in the image processing unit 2.

  The region separation processing unit 14 determines whether each pixel in the image (original image) corresponding to the digital RGB data output from the input tone correction unit 13 belongs to a halftone dot region, a character region, or a photographic region. Region separation processing is performed. Note that the region separation processing by the region separation processing unit 14 will be described later.

The region separation processing unit 14 also outputs a signal (region identification signal) indicating the region to which each pixel belongs based on the result of the region separation processing, as a color correction unit 15, a black generation and under color removal unit 16, and a spatial filter processing unit. 17 and output to the gradation reproduction processing unit 19.
The region separation processing unit 14 outputs the digital RGB data output from the input tone correction unit 13 to the color correction unit 15 as it is.

  In this copying machine, after this digital RGB data is converted into digital data (CMY data) of CMY (C: cyan, M: magenta, Y: yellow) composed of three color components, from this CMY data, CMYK data composed of four color components is generated.

Therefore, in the following, in order to clearly distinguish the data, the three colors of CMY data are referred to as “cmy data” in lower case, while the four colors are expressed as “CMYK data” in upper case.
In addition, the three color components in the cmy data are also expressed in lowercase letters c, m, and y, and the four color components in the CMYK data are expressed in uppercase letters C, M, Y, and K.

  The color correction unit 15 converts digital RGB data into cmy data having 256 gradations (0 to 255).

  The color correction unit 15 performs a process (color correction process; described later) for removing color turbidity based on the spectral characteristics of the toner from the cmy data in order to faithfully reproduce the color. This color turbidity is caused by an unnecessary absorption component contained in the C, M, and Y color materials (toners).

The black generation and under color removal unit 16 generates black (K) data from the cmy data. Further, the black generation and under color removal unit 16 generates new CMY data by subtracting K data from the CMY data, and further generates four-color data (CMYK) composed of CMYK from the new CMY data and K data. Data).
The processing of the black generation and under color removal unit 16 will be described later.

  The spatial filter processing unit 17 performs a spatial filter process using a digital filter on the CMYK data based on the region identification signal. That is, the spatial filter processing unit 17 has a function of correcting the spatial frequency characteristics of the CMYK data and preventing blurring of the output image and deterioration of graininess.

The output tone correction unit 18 performs output tone correction processing for converting a part of CMYK data (density data or the like) into a halftone dot area ratio that is a characteristic value of the printing unit 3.
The gradation reproduction processing unit 19 performs gradation reproduction processing (halftone generation processing) for separating the CMYK data output from the output gradation correction unit 18 for each pixel and processing so as to reproduce the gradation of each pixel. It is something to execute.

  In particular, in the character region, in order to improve the reproducibility of the character, the enhancement amount of the high-frequency component can be increased by the sharp enhancement process (one of the spatial filter processes) of the spatial filter processing unit 17. At the same time, the character area is binarized or multi-valued by the output tone correction unit 18 on a high-resolution screen suitable for reproducing high-frequency components.

For the halftone dot region, the spatial filter processing unit 17 performs low-pass filter processing for removing the input halftone dot component. Then, the output gradation correction unit 18 performs binarization or multi-value processing using a screen that emphasizes gradation.
Further, regarding the photographic area, the gradation reproduction processing unit 18 performs binarization or multi-value processing using a screen that emphasizes gradation reproducibility.

Hereinafter, the region separation processing by the region separation processing unit 14 will be described.
FIG. 4 is an explanatory diagram showing the configuration of the region separation processing unit 14.
As shown in this figure, the region separation processing unit 14 includes a character / halftone dot / photograph region separation unit 21.

  The character / halftone dot / photo area separating unit 21 includes a pixel, a halftone dot, a photo area (or other area including a photo area) in which each pixel in the image corresponding to the digital RGB data output from the input tone correcting unit 13 Area).

  As described above, for example, a method described in Patent Document 2 can be used as a method of separating each pixel of digital RGB data into a character, a halftone dot, and a photographic region.

A method for separating pixels into character / halftone dot / photograph areas by the character / halftone dot / photograph area separating unit 21 will be described below.
The character / halftone dot / photograph region separation unit 21 sets an M × N (M and N are natural numbers) pixel block centered on one pixel of interest in the digital RGB data.

Thereafter, the character / halftone dot / photograph region separation unit 21 calculates an average value (D _ave ) of the signal level for the central nine pixels in the block. Then, using the obtained average value, binarized pixel data is generated by binarizing (0 or 1) all the pixels in the block.
The character / halftone dot / photograph region separating unit 21 simultaneously obtains the maximum pixel signal level (D _max ) and the minimum pixel signal level (D _min ) in the block.

Next, the character / halftone dot / photograph region separation unit 21 determines whether the pixel belongs to the halftone dot region.
In the halftone dot area, the fluctuation of the image signal in the small area is large, and the pixel density is higher than the background.

Therefore, the character / halftone dot / photo area separating unit 21 changes the number of change points (K _H ) from 0 to 1 in the main scanning and sub-scanning directions (K _H ) and the number of change points from 1 to 0 (binary pixel data). determine the K _V).
Thereafter, the character / halftone dot / photograph region separating unit 21 compares these K _H and K _V with predetermined thresholds T _H and T _V. If K _H and K _V both exceed the thresholds T _H and T _V , it is determined that “the above-mentioned target pixel belongs to the halftone dot region”.

In addition, the character / halftone dot / photo area separation unit 21 compares the above-described D _max , D _min , D _ave with predetermined threshold values B ₁ , B ₂ . This is to prevent erroneous determination with the background.

That is, the character / halftone dot / photograph region separation unit 21 classifies the pixel of interest into a halftone dot region when the following condition (A) is satisfied.
(A) D _max −D _ave > B ₁ , D _ave −D _min > B ₂ , K _H > _TH , and K _V > T _V
If the condition (A) is not satisfied, the character / halftone dot / photo area separating unit 21 determines whether the target pixel belongs to the character area.
In the character area, the difference between the maximum pixel signal level (D _max ) and the minimum pixel signal level (D _min ) is large, and the density is also high.

Therefore, the character / halftone dot / photo area separating unit 21 uses the maximum pixel signal level (D _max ), the minimum pixel signal level (D _min ), and their difference (D _sub ) as predetermined thresholds P _A , P _B , compared with the P _C. Then, when the following condition (B) is satisfied, the target pixel is classified into a character region. If this condition (B) is not satisfied, the pixel of interest is classified into a photographic area.
_{(B) D} max> _{P A} or _D min _{<P B,} or _D sub> _{P C,}
Then, the character / halftone dot / photo area separation unit 21 converts the area identification signal SEG indicating the classified result into a color correction unit 15, a black generation and under color removal unit 16, a spatial filter processing unit 17, and a gradation reproduction processing unit 19. To communicate.

Next, the black generation / under color removal processing by the black generation / under color removal unit 16 will be described.
FIG. 5 is a block diagram showing a configuration of the black generation and under color removal unit 16.
As shown in this figure, the black generation and under color removal unit 16 includes a maximum / minimum calculation unit 31, a UCR amount calculation unit 32, a UCR processing unit 33, and a black generation amount calculation unit 34.

  The maximum / minimum calculation unit 31 (parameter calculation unit) calculates the maximum value (MAX) and the minimum value (MIN) of the cmy data output from the color correction unit 15. Then, they are output to the UCR amount calculation unit 32 and the black generation amount calculation unit 34, respectively.

Based on the maximum value (MAX) and minimum value (MIN) of the cmy data calculated by the maximum / minimum calculation unit 31 and the region identification signal SEG output from the region separation processing unit 14, the UCR amount calculation unit 32 The color removal amount UCR is calculated.
On the other hand, similarly to the UCR amount calculation unit 32, the black generation amount calculation unit 34 outputs the maximum value (MAX) and the minimum value (MIN) of the cmy data calculated by the maximum / minimum calculation unit 31 and the output from the region separation processing unit 14. The black generation amount (black component amount) K is calculated based on the region identification signal SEG to be performed.
The processing of the UCR amount calculation unit 32 and the black generation amount calculation unit 34 will be described later.

The UCR processing unit 33 receives the cmy data output from the color correction unit 15. Then, a process of generating C, M, and Y data (under color removal process) is performed by subtracting the under color removal amount UCR calculated by the UCR amount calculation unit 32 from the cmy data.
C = c-UCR
M = m-UCR
Y = y-UCR
Then, the black generation and under color removal unit 16 converts the CMYK data obtained by combining the C, M, and Y data calculated by the UCR processing unit 33 and the K data calculated by the black generation amount calculation unit 34 into a spatial filter. It is designed to output to the processing unit 17.

  Here, processing of the UCR amount calculation unit 32 and the black generation amount calculation unit 34, which is a characteristic configuration of the copying machine, will be described.

  The UCR amount calculation unit 32 and the black generation amount calculation unit 34 calculate the under color removal amount UCR and the black generation amount K, respectively, except that these tables are different (K table or UCR table). Is done in a similar manner. Accordingly, only the black generation process by the black generation amount calculation unit 34 will be described below.

  FIG. 6 is an explanatory diagram showing the configuration of the black generation amount calculation unit 34. As shown in this figure, the black generation amount calculation unit 34 includes a K table memory 41, a memory access unit 42, and a black generation amount calculation unit 43.

  As shown in FIG. 7, the K table memory (table storage unit) 41 is a memory that stores n K tables (black generation tables). One K table is composed of a set of two one-dimensional tables LUT1 and LUT2.

Here, LUT1 and LUT2 will be described in detail.
FIG. 8 shows a relationship between the one-dimensional tables LUT1 and LUT2 storing black generation amounts determined for the minimum value MIN and the maximum value MAX of the cmy data, and the black generation amounts calculated using the LUT1 and LUT2. FIG.

LUT1 and LUT2 indicate black generation amounts corresponding to positions of two edge curves (indicated by bold lines in the figure) on the curved surface of FIG. 8 with respect to MIN and MAX. Since the optimum black generation amount differs between the dark and vivid image and the character image, the above LUT1 and LUT2 show different shapes.
The LUT 1 is a black generation table corresponding to a gray image (y = m = c, MIN = MAX image). That is, the LUT 1 is a one-dimensional table in which the MIN value (0 to 255) and the optimum black generation amount for each MIN are associated with such a gray image.

  On the other hand, the LUT 2 is a black generation table that takes into account the saturation according to a high-saturation image (an image with MAX = 255 in which “y = m = c and MIN = MAX” is not established). That is, the LUT 2 is a one-dimensional table in which the MIN value (0 to 255) and the optimum black generation amount for each MIN are associated with such a high saturation image.

The memory access unit (black component calculation unit) 42 selects a K table to be used from the n K tables based on the region identification signal SEG.
The memory access unit 42 also has a function of reading out two black generation amounts from the LUT1 and LUT2 of the selected K table and outputting them to the black generation amount calculation unit 43 based on the MIN of the cmy data.
In the following, the black generation amount read from LUT1 is K1 (gray black component amount), and the black generation amount read from LUT2 is K2 (high saturation black component amount).

  These K1 and K2 are points corresponding to the minimum value MIN of the cmy data in each of the curves LUT1 and LUT2 on the graph of FIG. The black generation amount K for the cmy data is located on a straight line (straight line K12) connecting these K1 and K2.

  The black generation amount calculation unit (black component calculation unit) 43 performs interpolation calculation based on the MIN and MAX of the cmy data with respect to the straight line K12 formed by connecting K1 and K2 read by the memory access unit 42. And the black generation amount K is calculated.

Here, the interpolation calculation by the black generation amount calculation unit 43 will be described.
FIG. 1 is a graph obtained by plotting the above-described straight lines K12, LUT1, and LUT2 on a plane with the horizontal axis representing the minimum value MIN and the vertical axis representing the maximum value MAX.

The black generation amount calculation unit 43 first calculates the following value f based on the minimum value MIN. Here, a · b is a constant.
f = a × MIN + b (1)
Then, the calculation method is changed depending on which of the following conditions (2) and (3) is satisfied by f and MAX.
f ≧ MAX ≧ MIN (2)
255 ≧ MAX> f (3)
When (2) is satisfied, MAX is located within the offset region shown in FIG.
This offset region is determined in advance with the straight line f shown in the above equation (1) and LUT1 (the line segment connecting (0, 0) and (255, 255) in FIG. 1) as a boundary. It is the range.
Then, when the MAX is within this region (for example, as shown in FIG. 9), the black generation amount calculation unit 43 reads “CMY data is a gray image because the difference between the minimum value MIN and the maximum value MAX is small. The value of K1 is the black generation amount K, that is,
K = K1
Designed to be

  9 and FIG. 10 to be described later, the left diagram shows the black generation amount K1 with respect to MIN in LUT1, the right diagram shows the black generation amount K2 with respect to MIN in LUT2, and the central diagram shows K1, K2 to MIN, It is a graph which shows the black generation amount K calculated | required by the interpolation calculation using f and MAX.

  On the other hand, when the condition (3) is satisfied (for example, as shown in FIG. 10), the MAX is located outside the offset area. In this case, the black generation amount calculation unit 43 determines that “the difference between the minimum value MIN and the maximum value MAX is large”, and executes linear interpolation calculation based on the ratio of α and β shown in FIG.

That is, in this case, from FIG. 10, α and β are expressed by the following equations.
α = MAX-f
β = 255-MAX
Then, as shown in the following equation (4), the black generation amount calculation unit 43 multiplies K1 and K2 by using these α and β as weighting factors, and adds the result to obtain the black generation amount K.
K = (β · K1 + α · K2) / (255−f) (4)
The UCR amount calculation unit 32 of the black generation and under color removal unit 16 shown in FIG. 5 replaces the K table memory 41 in the configuration of the black generation amount calculation unit 34 shown in FIG. ).
Similar to the K table memory 41, the UCR table memory includes a plurality of UCR tables. The operation of the UCR amount calculation unit 32 is the same as that of the black generation amount calculation unit 34 except that the table to be used is a UCR table.

Here, the operation of the black generation and under color removal unit 16 will be described together.
FIG. 11 is a flowchart showing this operation.
As shown in this figure, in the black generation / under color removal processing of the black generation / under color removal unit 16, the maximum / minimum calculation unit 31 calculates the maximum value MAX and the minimum value MIN of the cmy data in the target pixel (S21).

Next, using the calculated MIN and MAX, a black generation amount calculation process (S22) by the black generation amount calculation unit 34 and a UCR amount calculation process (S23) by the UCR amount calculation unit 32 are executed.
Thereafter, the UCR processing unit 33 performs undercolor removal processing for subtracting the UCR amount calculated in S23 from the cmy data (S24).

FIG. 12 is a flowchart showing black generation calculation processing.
In this process, the memory access unit 42 of the black generation amount calculation unit 34 selects a K table from the K table memory 41 in accordance with the region identification signal SEG. Then, K1 and K2 are read from the selected K table based on MIN (S41).

Thereafter, the black generation amount calculation unit 43 determines whether or not the MAX value of the cmy data is within the offset region (S42).
If the MAX value is within the offset region, K1 is set to the black generation amount K (S43).
On the other hand, if the MAX value is outside the offset region, interpolation calculation is performed using K1, K2, MIN, and MAX to obtain the black generation amount K (S44).

  FIG. 13 is a flowchart showing UCR calculation processing. As shown in this figure, this process is a process in which the table used is changed from the K table to the UCR table in the black generation calculation process shown in FIG. That is, in the UCR calculation process, the same process as the black generation calculation process (a process using the lower color removal amount UCR1 / UCR2 corresponding to the black generation amounts K1 and K2) is performed using the UCR table, and the lower color removal amount. Calculate the UCR.

As described above, the black generation amount calculation unit 34 in the black generation and under color removal unit 16 stores two one-dimensional tables, LUT1 and LUT2, in the K table memory 41.
Then, the memory access unit 42 and the black generation amount calculation unit 43 obtain black generation amounts K1 and K2 suitable for the minimum value MIN using these two one-dimensional tables.

As described above, in the black generation amount calculation unit 34, only two one-dimensional tables are necessary for the conversion table necessary for obtaining the optimum black generation amount K.
Therefore, the memory size can be greatly reduced as compared with the configuration storing the two-dimensional table.

In the black generation process described above, an offset area is set in the vicinity of LUT1 (gray axis).
Then, when the maximum value MAX is in the offset region, the black generation amount calculation unit 34 determines that “CMY data is a gray image because the difference between the minimum value MIN and the maximum value MAX is small”. The black generation amount K1 read from the LUT 2 is set to be K data of CMYK data.

That is, in the gray image, since all the color components (cmy) have the same amount, the minimum value MIN and the maximum value MAX related to the pixel value are the same value.
However, when CMY data is disturbed (for example, when an original image is read by the scanner unit 1 to generate CMY data, disturbance (such as noise of the scanner unit 1) is received), a gray image such as a black character has a CMY There may be a difference between the minimum value MIN and the maximum value MAX because the color components vary (are not aligned).
In such a case, the black component amount obtained from the interpolation calculation using the equation (1) (considering the maximum value MAX) is smaller than the gray black component amount.

  Therefore, when the difference between the minimum value MIN and the maximum value MAX is small (the maximum value is in the offset region), the black generation amount calculation unit 34 regards the CMY data as a gray image and calculates the black generation amount K. It has become. As a result, it is possible to set an optimal black generation amount K even for a gray image disturbed by a disturbance, and prevent a reduction in the black generation amount due to the disturbance.

In the black generation process described above, the character area and the area including neighboring pixels are separated into a character area, a dot area, and a photographic area (or other areas including the photographic area), and black is generated in each area. The amount is to be controlled.
Here, when the area identification signal SEG represents a character area, an offset area is set. In other cases (photograph, halftone dot area), a tone gap due to an increase in the amount of black generation is suppressed, and gradation is emphasized. It is also possible to configure such that no setting is made.

  Further, as described above, pixel values when scanning black characters may be off the gray axis and distributed in the periphery due to noise of the scanner unit 1 or the like, but are originally gray regions. Therefore, it is preferable to set an offset region in the distribution range of pixel values when black characters are read. Thereby, the black generation amount of the pixel values constituting the black character can be increased, and the reproducibility of the black character can be improved.

In the present embodiment, the MAX offset region is a region defined by a linear expression such as the straight line f and the LUT 1 field. However, the present invention is not limited to this, and the offset region can have an arbitrary shape.
For example, the boundary line of the offset region may be defined by a larger number of mathematical expressions (for example, the content of the straight line f may be changed according to the MIN range). It is also possible to set the offset region with a higher-order mathematical expression.

Further, the offset region may be set to a complicated shape (a shape that is not continuous but is divided into a plurality of locations, or a shape that cannot be defined by a straight line).
Here, in such a case, in order to accurately define (approximate) the offset region, a high-order polynomial is required instead of the above equation (1), and the amount of calculation for calculating this equation, The calculation time and the circuit configuration for calculation may increase. Moreover, there is a possibility that it cannot be determined by a polynomial.

Therefore, when the offset area has a complicated shape, a value representing the offset area may be included as a table value.
That is, in this case, the minimum value MIN and the offset value (value representing the boundary of the offset region; the value on the straight line f in FIG. 1) as shown in FIG. A graph (table) representing the correspondence relationship is stored in advance.

When the black generation amount calculation unit 43 calculates the black generation amount K, the memory access unit 42 reads an offset value with respect to the minimum value MIN and transmits it to the black generation amount calculation unit 43. Then, equations (2) to (4) are processed with the transmitted value as f.
Similarly, the under color removal amount may be calculated by preparing a table representing the offset value and reading the offset value f in the same manner as the black generation amount.

  Note that the width of the offset region (width in the vertical axis direction) shown in FIG. 1 is set according to the minimum value MIN. Therefore, this offset region can also be expressed as “a two-dimensional region determined by the minimum value MIN (the value of the first parameter) and its width (offset range)”. Further, when “the difference between the maximum value MAX and the minimum value MIN is within the width in the vertical axis direction in the offset region”, the maximum value MAX is in the offset region.

  Here, when the offset area is set by a mathematical expression, the black generation amount calculation unit 43 can determine whether there is a MAX (second parameter) value in this area without using a table or the like. It can be said that the storage capacity can be saved.

  In the present embodiment, the K table memory 41 of the black generation amount calculation unit 34 includes n K tables. In the black generation process, the memory access unit 42 selects a K table to be used from the n K tables based on the region identification signal SEG.

  Here, the K table may be designed so as to prepare the number of types of region separation. In addition, each area may be designed so that one K table is used redundantly (the same K table is used even if the areas are different). In this case, the number of K tables stored in the K table memory 41 is smaller than the number of types of areas.

  Further, the K table memory 41 may be provided with only one K table. In this case, the memory access unit 42 always reads K1 and K2 using the same LUT1 and LUT2 regardless of the area identification signal SEG.

Further, the copying machine may be set using the operation unit 4 so that the user can specify an image type (image mode). Here, the image type is the type of image (character, photograph, halftone dot) for printing.
In this case, as image types, it is preferable to be able to designate combinations of these (character and photo images, photo and halftone images, etc.) in addition to the three types of characters, photos and halftone dots.

In such a case, it is preferable that the memory access unit 42 selects the K table to be used based on the image type designated by the user instead of the area identification signal SEG.
Accordingly, in this case, it is preferable to store the number of K tables corresponding to the image type in the K table memory 41.

  The memory access unit 42 may be designed so as to select a K table to be used based on the image type designated by the user and the region identification signal SEG. In other words, in this case, even when the same area identification signal SEG is input, the memory access unit 42 switches the table to be used depending on the designated image type.

For example, when the image type “character and photographic image” is designated, the memory access unit 42 is considered to contain characters in the halftone dot area of the image, so that black is displayed in the halftone dot area. A large number of K tables are used.
On the other hand, when an image type of “photo image” is designated, a K table with a black generation amount K smaller than that of “character and photo image” is used for the halftone dot region of the image.
In such a case, the number of K tables stored in the K table memory 41 is larger than the number of types of area separation and the number of image types.

Further, the K table stored in the K table memory 41 in the present copying machine is small data including two one-dimensional tables LUT1 and LUT2. Therefore, even when a plurality of K tables are stored in the K table memory 41, the storage capacity required for storing the K tables can be reduced as compared with the technique of Patent Document 1 that stores a two-dimensional K table.
In particular, in the technique of Patent Document 1, in a configuration in which two-dimensional K tables corresponding to the number of types of area separation are stored and the K tables are switched according to the area separation results, the necessary storage capacity is Compared with the capacity required for the K table memory 41, it becomes extremely large.

In this embodiment, the memory access unit 42 selects a plurality of K tables stored in the K table memory 41 and reads K1 and K2 from the LUT1 and LUT2 included in the K table. In other words, the K table memory 41 stores a plurality of pairs of LUT1 and LUT2.
However, the present invention is not limited to this, and a plurality of types of LUT1 and LUT2 may be stored in the K table memory 41 separately without being grouped (without being combined to form a K table). . In this case, the memory access unit 42 selects appropriate LUT1 and LUT2 from the K table memory 41 based on the region identification signal SEG.

In the following, color correction processing by the color correction unit 15 will be described.
As a color correction processing method, there are the following methods (a) and (b).
(a) Method of having correspondence between digital RGB data input to color correction unit 15 and cmy data output from color correction unit 15 as an LUT
(b) There is a color masking method using a transformation matrix as shown in the following formula (5).

For example, when using the color masking method,
"Cmy data"
"Digital RGB data obtained when the scanner unit 1 reads a color patch having the same L ^* a ^* b ^* as the color obtained by printing this cmy data by the printing unit 3;
A large number of sets are prepared. Then, coefficients a11 to a33 of the transformation matrix shown in Expression (5) are calculated from these data sets. Then, color correction processing is performed using these coefficients. In addition, what is necessary is just to add a higher-order term more than a second order when you want to raise a precision more. The above L ^* a ^* b ^* means the CIE 1976 L ^* a ^* b ^* signal (CIE: Commission International de l'Eclairage). Note that L ^* is a symbol representing lightness, and a ^* and b ^* are symbols representing chromaticity.

  Further, in the present embodiment, it is assumed that the straight line K12 is obtained using LUT1 and LUT2, which are one-dimensional tables in which the minimum value MIN value (0 to 255) and the optimum black generation amount for each MIN are associated with each other. Yes. Then, the black generation amount K is obtained by an interpolation operation (equation (4)) using the straight line K12, the minimum value MIN, and the maximum value MAX.

However, regarding the calculation of the black generation amount, an appropriate black generation amount K can be obtained without using the minimum value MIN / maximum value MAX in this way.
Here, the parameter corresponding to the black generation amount in the one-dimensional table (in the above, the minimum value MIN) is the first parameter, and the other parameter (also the maximum value MAX) is the second parameter.

For example, the black generation amount can be obtained with the first parameter as the maximum value MAX and the second parameter as the minimum value MIN.
FIG. 15 is a two-dimensional graph of the straight lines K12, LUT1, and LUT2 in this case with the minimum value MIN on the vertical axis and the maximum value MAX on the horizontal axis. In this graph, one optimum black generation amount is set for a set of (MIN, MAX). In FIG. 15, LUT2 is a line with MIN = 0, and LUT1 is a line with MAX = MIN. Since the maximum value MAX ≧ minimum value MIN, the point indicating the optimum black generation amount exists in a triangular region surrounded by the horizontal axis, LUT1, and LUT2.

Further, the offset area in this case is set as shown in FIG. The black generation amount calculation unit 43 first calculates the following value f based on the maximum value MAX. Here, g · h is a constant.
f = g × MAX + h (6)
Then, the calculation method is changed depending on which of the following conditions (7) and (8) is satisfied by f and MIN.
MAX ≧ MIN ≧ f (7)
f> MIN (8)
When (7) is satisfied, MAX is located in the offset region shown in FIG.
This offset region is a predetermined range having the straight line f and the LUT 1 shown in the above equation (6) as a boundary.
Then, the black generation amount calculation unit 43 sets the value of K1 shown in FIG. 15 as the black generation amount K when MAX is in this region, that is,
K = K1
Designed to be

  On the other hand, when the condition (8) is satisfied, MAX is located outside the offset area. In this case, the black generation amount calculation unit 43 performs linear interpolation calculation based on the ratio of f-MIN and MIN.

That is, as shown in the following formula (9), the black generation amount calculation unit 43 multiplies K1 and K2 as weighting factors and adds the results to obtain the black generation amount K.
K = (MIN · K1 + (f−MIN) · K2) / f (9)
Further, as the first parameter or the second parameter, not only the minimum value MIN and the maximum value MAX, but also C, M, and Y component values, the median value MID (= mid (C, M, Y)), and the like are used. It is also possible.
Further, an average value AVE (= (C + M + Y) / 3) and a color component value M (magenta) may be used. However, there are conditions for combinations that can be set for the first parameter and the second parameter. Table 1 below shows setting examples and interpolation calculation methods using the minimum value MIN, maximum value MAX, median value MID, average value AVE, and color component value M as parameters.

  As the first parameter or the second parameter, only those having a magnitude relationship (MAX ≧ MIN) such as the maximum value MAX and the minimum value MIN can be used. Here, in the example of the combination of the first and second parameters shown in Table 1, “○” is described as a settable combination and “X” is described as a combination that cannot be set in the column of setting availability.

  In addition, it is necessary to switch the interpolation calculation formula used by the black generation amount calculation unit 43 according to the first and second parameters to be used. For example, when the first parameter is MIN and the second parameter is MAX, as shown in Table 1, the above-described equation (4) is used as an interpolation calculation equation. On the other hand, when the first parameter is MAX and the second parameter is MIN, Expression (9) is used as an interpolation calculation expression.

It should be noted that the parameter is set so that the interpolation calculation according to the above-described equation (9) is used for the character original or the character region, and the interpolation calculation according to the above-described equation (4) is used for the other regions. By selecting, color reproduction with improved reproducibility of the character part can be expected.
Similarly, it is preferable to use the interpolation calculation by the equation (4) for the character mode and the interpolation calculation by the equation (9) for the other document modes.

Further, when AVG described above is used for the first parameter and MAX is used for the second parameter, generally higher black generation is performed than when MIN is used for the first parameter and MAX is used for the second parameter. For this reason, it can be said that this is another configuration suitable for a character region or a character document. The same effect is obtained when MID is set as the first parameter and MAX is set as the second parameter.
Therefore, what is selected as the first parameter / second parameter is preferably determined based on the region type included in the output image, for example, as described above.

In the present embodiment, both black generation processing and under color removal processing are performed in consideration of the offset region (processing using equation (4) or equation (9) as an interpolation calculation equation).
However, the above-described processing may be used only for one of the black generation processing and the under color removal processing, and the conventional method may be used for the other.

  Further, as a process of concept wider than black generation, secondary color generation processing (C, M in multicolor printing (in addition to normal CMYK color materials, color materials such as R (red) and B (blue) are also used)) The processing considering the offset region can also be applied to the processing of generating the secondary color components of R and B from the color components of.

  For example, in the secondary color generation process, when the process of replacing the C and M color components with the C ′, M ′, and R color components is performed, a part of the C and M components is replaced with the R component as in the black generation process. Process to replace with. For example, by setting the first parameter to the minimum value MIN (C, M) and the second parameter to the maximum value MAX (C, M), the R component can be generated in the same processing procedure as that for black generation.

  That is, two table values R1 and R2 corresponding to the first parameter are read, and R ′ is obtained by performing an interpolation operation using the first and second parameters. As the LUT to be used, the same LUTs 1 and 2 shown in FIG. 7 can be used. The processing for correcting the C and M color components to the C ′ and M ′ color components in consideration of the generation of the R component is performed in the same manner as the under color removal at the time of black generation.

  In the present embodiment, CMYK is used as a color used for printing, and black generation is performed from CMY data. However, the present invention is not limited to this, and RGBK may be used as a color used for printing. In this case, black is generated from the RGB data.

In the present embodiment, the two black generation amounts K1 and K2 are read from the two black generation tables LUT1 and LUT2, and the black generation amount is calculated using them.
However, when determining the black generation amount, a third black generation table LUT3 may be prepared in addition to LUT1 and LUT2, and the three black generation amounts set in the three black generation tables may be used. Here, LUT3 is a table for setting an intermediate black generation amount between LUT1 and LUT2.

As shown in FIG. 17, the black generation amount calculated from LUT1 is K1, the black generation amount calculated from LUT3 is K2, and the black generation amount calculated from LUT2 is K3.
As shown in the figure, when MAX is between P2 and 255, K is obtained by interpolation calculation using K2 and K3. Similarly, when MAX is between P1 (= MIN) and P2, interpolation calculation is performed using K1 and K2. The offset region is set as shown in FIG. Here, f represents the boundary of the offset corresponding to MIN.

In addition, the following equations (10) to (13) are used for the interpolation calculation.
When P2> y ≧ P1 When y> MAX ≧ P1 K = K1 (10)
When P2> MAX ≧ f K = {(P2-MAX) K1 + (MAX-f) K2} / (P2-f) (11)
When 255 ≧ y ≧ P2 When y> MAX ≧ P2 K = K2 (12)
When 255 ≧ MAX ≧ y K = {(255−MAX) K1 + (MAX−f) K2} / (255−f) (13)
A similar calculation method is used when four or more black generation amounts are used.

  Further, as described above, the LUT 1 shown in the present embodiment is a black generation table corresponding to a gray image (y = m = c, MIN = MAX image). That is, the LUT 1 is a one-dimensional table in which the MIN value (0 to 255) and the optimum black generation amount for each MIN are associated with such a gray image.

  On the other hand, the LUT 2 is a black generation table that takes into account the saturation according to a high-saturation image (an image with MAX = 255 in which “y = m = c and MIN = MAX” is not established). In other words, the LUT 2 is a one-dimensional table in which the MIN value (0 to 255) and the black generation amount considering the optimum saturation for each MIN are associated with such a high saturation image.

  In the present embodiment, the scanner unit 1 is used as an output device for image data (analog RGB data). However, the present invention is not limited to this, and another image input device (such as a facsimile device) may be provided.

  In this embodiment, the black generation and under color removal unit 16 is provided in the image processing unit 2 of the digital color copying machine. However, the present invention is not limited to this, and the black generation and under color removal unit 16 can be applied to any apparatus as long as it is an image processing apparatus that inputs digital or analog RGB data or cmy data and outputs CMYK data. It is.

In this embodiment, recording paper is used as the print medium, but other media (medium made of a material other than paper) may be used.
In the present embodiment, the printing unit 3 is an electrophotographic printing apparatus (printer). However, you may comprise the printing part 3 from the printer of another system (inkjet system).

  Further, the black generation / undercolor removal processing in the black generation / undercolor removal unit 16 may be realized as software. That is, for example, it is possible to provide a computer with a printer driver incorporating software for realizing black generation and undercolor removal processing.

FIG. 19 is a block diagram showing a configuration of a computer 100 provided with such a printer driver 110.
As shown in this figure, the computer 100 includes (incorporates) a printer driver 110, a printer language translation unit 114, a communication port driver 115, and a communication port 116.

Further, the printer driver 110 includes a color correction unit 15, a black generation lower color removal unit 16, and a gradation reproduction processing unit 19 similar to those shown in FIG. 3.
Further, the computer 100 is connected to a printer (printing apparatus; image output apparatus) 117, and the printer outputs an image according to image data output from the computer.

  Image data (RGB data) generated by executing various application programs in the computer 100 is sent to the color correction unit 15, the black generation and under color removal unit 16, and the gradation reproduction processing unit 19 in the printer driver 110. The same processing as that of the copying machine is performed.

Then, the image data (CMYK data) subjected to such processing is converted into a printer language by the printer language translation unit 114. Then, the data is input to the printer 117 via the communication port driver 115 and the communication port (for example, RS232C / LAN) 116.
The printer 117 may be a digital multifunction machine having a copy function and a fax function in addition to the printer function.

  In the present embodiment, the black generation / under color removal process is performed by the black generation / under color removal unit 16. However, the present invention is not limited to this, and an information processing apparatus (computer) capable of recording a program for performing these processes on a recording medium and reading and executing the program is replaced with the black generation and under color removal unit 16. You may make it use.

  In this configuration, the arithmetic unit (CPU or MPU) of the information processing apparatus reads the program recorded on the recording medium and executes the process. Therefore, it can be said that this program itself realizes the processing.

  Here, as the information processing apparatus, in addition to a general computer (workstation or personal computer), a function expansion board or a function expansion unit mounted on the computer can be used.

  The above program is a program code (execution format program, intermediate code program, source program, etc.) of software that realizes processing. This program may be used alone or in combination with other programs (such as OS). The program may be read from the recording medium, temporarily stored in a memory (RAM or the like) in the apparatus, and then read and executed again.

  The recording medium for recording the program may be easily separable from the information processing apparatus, or may be fixed (attached) to the apparatus. Furthermore, it may be connected to the apparatus as an external storage device.

  Such recording media include magnetic tapes such as video tapes and cassette tapes, magnetic disks such as floppy (registered trademark) disks and hard disks, and optical disks such as CD-ROM, MO, MD, DVD and CD-R (magneto-optical). Disc), memory cards such as IC cards and optical cards, semiconductor memories such as mask ROM, EPROM, EEPROM, and flash ROM can be applied.

  Also, a recording medium connected to the information processing apparatus via a network (intranet / Internet) may be used. In this case, the information processing apparatus acquires the program by downloading via the network. That is, the above program may be acquired via a transmission medium (a medium that dynamically holds the program) such as a network (connected to a wired line or a wireless line). The program for downloading is preferably stored in advance in the apparatus (or in the transmission side apparatus / reception side apparatus).

  The present invention also relates to an image processing method and an image processing apparatus that perform color conversion processing on input image data, and an image forming apparatus, a program, and a recording medium including the image processing method. It can also be said that the present invention relates to an image processing method and an image processing apparatus that perform black generation processing on a signal, and an image forming apparatus, a program, and a recording medium including the same.

  Further, the input tone correction unit 13 adjusts the color balance of the RGB signal (RGB reflectance signal) from which various distortions have been removed by the shading correction unit 12, and at the same time, adopts it in a color image processing apparatus such as a density signal. It may be converted into a signal that can be easily handled by the image processing system being used.

Further, as a method of removing color turbidity by the color correction unit 15, there are a method having a correspondence relationship between an input RGB signal and an output cmy signal as an LUT, and a color masking method using a transformation matrix as shown in Expression (5). . For example, in the case of using a color masking method, the color to be output when given a certain cmy to the image output device ^L * ^a * ^{b *} value (CIE1976L ^* a ^* b ^* signal) to the same ^L * ^a * ^{b *} Prepare a large number of RGB data when the scanner reads color patches and CMY data given to the image output device, and calculate the coefficients of the transformation matrix from a11 to a33 in equation (5) from these combinations To do. Color correction processing is performed using these coefficients. In order to increase the accuracy, it is only necessary to add a second or higher order term. Further, the output tone correction unit 18 may perform an output tone correction process for converting a signal such as a density signal into a halftone dot area ratio that is a characteristic value of the printing unit 3.

  In FIG. 1, the offset range is defined as an offset range between a line segment connecting (0, 0) and (255, 255) and the other boundary line. Here, when the offset is expressed by a mathematical formula, the boundary line is approximated by the mathematical formula. In addition, it is not necessary to express the boundary line with one mathematical expression, and a plurality of expressions may be used in the form of Expression 1 for a certain section and Expression 2 for another section. However, when the boundary line has a complicated shape and cannot be approximated by a simple mathematical expression, it is preferable to represent the boundary using an LUT.

As shown in FIG. 1, in this copying machine, when the condition (3) is satisfied, the black generation amount is obtained using the expression (4). Here, if c = m = y, there is a point on the line segment (gray axis) connecting (0, 0) and (255, 255), but the gray region does not actually fall on this line segment. And it is located in the place where it shifted. Then, in the above processing, if it is within the deviation range (within the offset region), the black generation amount is maintained by performing the same black generation as that on the gray axis, and the saturation is outside the offset region. By approaching the black generation amount considering the above, an appropriate black generation amount according to the saturation is obtained.
In the present invention, LUT1 and LUT2 need not be stored in pairs in each K table, and a corresponding one-dimensional table may be selected from a plurality of one-dimensional tables.

  Moreover, the technique of patent document 1 can also be described as follows. That is, in this document, there is no clear description as to whether or not the table is switched according to the area identification signal (image area identification information). Therefore, if the table is switched according to the area identification signal, a plurality of black generation tables are required. In Patent Document 1, since a two-dimensional table is used, as many two-dimensional black generation tables as the number of area identification signals are required. Accordingly, the required memory capacity is extremely large as compared with the case of using a one-dimensional table.

  The present invention can also record an image processing method for performing black generation and undercolor removal processing by a one-dimensional LUT and interpolation calculation on a computer-readable recording medium in which a program to be executed by a computer is recorded.

  As a result, a recording medium on which a program for performing an image processing method for performing black generation and undercolor removal processing by a one-dimensional LUT and interpolation calculation is recorded can be provided in a portable manner.

  The recording medium may be a non-illustrated memory, for example, a program medium such as a ROM because processing is performed by a microcomputer, and a program reading device as an external storage device (not illustrated) is provided, and the recording medium is stored therein. It may be a program medium that can be read by being inserted.

  In either case, the stored program may be configured to be accessed and executed by the microprocessor, or the program is read out and the read program is stored in a program storage area (not shown) of the microcomputer. A method of downloading and executing the program may be used. In this case, it is assumed that the download program is stored in the main device in advance.

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

  In this case, since the system configuration is capable of connecting a communication network including the Internet, the medium may be a medium that fluidly carries the program so as to download the program from the communication network. When the program is downloaded from the communication network in this way, the download program may be stored in the main device in advance or installed from another recording medium.

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

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

  The present invention can also be expressed as the following first to fourth image processing apparatuses, first image forming apparatuses, first and second image processing methods, first image processing programs, and first recording media. In other words, the first image processing apparatus performs the first parameter (cmy) calculated from the image data including a plurality of color components in the image processing apparatus that performs black generation and under color removal processing on the image data including the plurality of color components. The black generation amount storage unit (1DLUT for black generation) that stores the black generation amount in association with the minimum value MIN), and a plurality of first black generation amounts read from the black generation amount storage unit based on the first parameter And a black generation calculation unit that calculates a second black generation amount by calculation using a second parameter (maximum value of cmy) calculated from image data composed of a plurality of color components. The calculation unit determines whether or not the second parameter is within a predetermined range (offset region), and the determination unit determines that the second parameter is within the predetermined range. In this case, one of the first black generation amounts is output as the second black generation amount, and when it is determined that the second parameter is out of the predetermined range, the calculation unit that obtains the second black generation amount by calculation It is the composition which becomes. Even if it is a gray pixel, it is not always the case that cmy is aligned. Therefore, if the pixel is shifted from the gray axis due to the variation, the black generation amount is reduced. By setting the offset region, the same black generation amount as the gray axis can be generated even if the pixel value is shifted from the gray axis, and appropriate black generation can be performed.

  The second image processing apparatus corresponds to the first parameter calculated from the image data composed of a plurality of color components in the image processing apparatus that performs black generation and under color removal processing on the image data composed of a plurality of color components. A lower color removal amount storage unit (1DLUT for lower color removal) that stores the lower color removal amount, and a plurality of first lower color removal amounts and a plurality of read out from the lower color removal amount storage unit based on the first parameter. A lower color removal calculation unit that obtains a second lower color removal amount by calculation using a second parameter calculated from image data composed of color components of the first color component, the lower color removal calculation unit, A determination unit that determines whether or not two parameters are within a predetermined range (offset region), and a second undercolor removal amount when the determination unit determines that the second parameter is within the predetermined range. As the first below And outputting one of the removal amount, the configuration and the second parameter if it is determined to be outside a predetermined range of a computing unit for obtaining a second under color removal amount by calculation. Even if it is a gray pixel, it is not always the case that cmy is aligned. Therefore, if the pixel is shifted from the gray axis due to the variation, the black generation amount is reduced. By setting the offset region, even if the pixel value is shifted from the gray axis, it is possible to perform the same black generation and lower color removal as that of the gray axis, and appropriate color reproduction can be performed.

  Further, the third image processing apparatus is configured such that, in the first or second image processing apparatus, the region in the predetermined range is specified by a calculation formula. As a result, the offset area can be represented by a small number of parameters, and the amount of memory required for designating the offset area can be reduced.

  Further, the fourth image processing apparatus is configured such that, in the first or second image processing apparatus, the region in the predetermined range is specified by a lookup table. Even an offset area having a complicated shape can be specified, and calculation for calculating the offset area is unnecessary, so that the processing can be speeded up.

  The first image forming apparatus includes any one of the first to fourth image processing apparatuses. Even if it is a gray pixel, it is not always the case that cmy is aligned. Therefore, if the pixel is shifted from the gray axis due to the variation, the black generation amount is reduced. By providing an offset area, an image forming apparatus capable of performing the same black generation and lower color removal as the gray axis even if the pixel value is shifted from the gray axis and performing appropriate color reproduction is provided. can do.

  The first image processing method is an image processing method in which black generation and under color removal processing is performed on image data composed of a plurality of color components. The first parameter (minimum value of cmy) is obtained from image data composed of a plurality of color components. MIN) and a black generation amount storage unit (black generation 1DLUT) for storing the black generation amount in association with the first parameter (minimum value MIN of cmy) based on the first parameter. A step of reading a plurality of first black generation amounts from the generation amount storage unit; a step of calculating a second parameter (maximum value of cmy) from image data comprising a plurality of color components; the first parameter and the second A black generation calculation step of obtaining a second black generation amount by calculation using a parameter and the first black generation amount, wherein the second parameter is within a predetermined range (offset). In the determination step for determining whether the second parameter is within the predetermined range, and in the determination step, if it is determined that the second parameter is within a predetermined range, one of the first black generation amounts is output, When it is determined that the second parameter is outside the predetermined range, this is a method including a calculation step of obtaining a second black generation amount by calculation.

  The second image processing method calculates a first parameter calculated from image data consisting of a plurality of color components in an image processing method that performs black generation and under color removal processing on image data consisting of a plurality of color components. And a step of reading a plurality of first lower color removal amounts from the lower color removal storage unit based on the first parameter from a lower color removal amount storage unit storing the lower color removal amount based on the first parameter. Calculating the second parameter from the image data composed of a plurality of color components, and calculating the second lower color removal amount by using the first parameter, the second parameter, and the first lower color removal amount. A lower color removal calculation step to be obtained, wherein the lower color removal calculation step includes: a determination step for determining whether the second parameter is within a predetermined range (offset region); When it is determined that the parameter is within the predetermined range, one of the first undercolor removal amounts is output, and when it is determined that the second parameter is out of the predetermined range, the second black color is calculated. This is a method comprising a calculation step for obtaining the generation amount.

  The first image processing program is an image processing program for operating any one of the first to fourth image processing apparatuses, and is a program for causing a computer to function as each of the above-described means. Thus, the above-described image processing apparatus can be realized by realizing each unit of the above-described image processing apparatus with a computer.

  The first recording medium is a computer-readable recording medium that records the first image processing program. Accordingly, the image processing apparatus can be realized on the computer by the image processing program read from the recording medium.

  The present invention can be suitably used for an image processing apparatus that converts primary image data including a plurality of color components into secondary image data including a black component.

3 is a two-dimensional graph for explaining a configuration for obtaining a black generation amount with a first parameter as a minimum value MIN and a second parameter as a maximum value MAX, with the horizontal axis representing the minimum value MIN and the vertical axis representing the maximum value MAX. 1 is a block diagram showing a schematic configuration of a digital color copying machine according to an embodiment of the present invention. FIG. 3 is an explanatory diagram illustrating a configuration of an image processing unit provided in the copier illustrated in FIG. 2. It is explanatory drawing which shows the structure of the area | region separation process part provided in the image process part shown in FIG. FIG. 4 is a block diagram illustrating a configuration of a black generation and under color removal unit provided in the image processing unit illustrated in FIG. 3. FIG. 6 is an explanatory diagram illustrating a configuration of a black generation amount calculation unit provided in the black generation and under color removal unit illustrated in FIG. 5. It is explanatory drawing which shows the structure of K table memory provided in the black production | generation amount calculation part shown in FIG. It is a figure which shows the relationship of the black production | generation amount calculated using the one-dimensional table LUT1 and LUT2 which each stored the black production | generation amount defined with respect to the minimum value MIN and the maximum value MAX of Cmy data, and LUT1 and LUT2. The horizontal axis represents the MIN, f, MAX gradation values, and the vertical axis represents the black generation amount K. The horizontal axis represents the MIN, f, MAX gradation values, and the vertical axis represents the black generation amount K. It is a flowchart which shows operation | movement of a black production | generation undercolor removal part. It is a flowchart which shows a black production | generation calculation process. It is a flowchart which shows a UCR calculation process. It is a graph showing the correspondence between minimum value MIN of cmy data and offset value. 4 is a two-dimensional graph for explaining a configuration for obtaining a black generation amount with a first parameter as a maximum value MAX and a second parameter as a minimum value MIN, with the vertical axis indicating the minimum value MIN and the horizontal axis indicating the maximum value MAX. It is a graph which shows an offset area | region in the structure which calculates | requires black generation amount by making the 1st parameter the maximum value MAX and the 2nd parameter the minimum value MIN. It is a two-dimensional graph with the horizontal axis representing the minimum value MIN and the vertical axis representing the maximum value MAX for explaining a configuration using three black generation amounts set in the three black generation tables. It is a graph which shows an offset area | region in the structure which uses three black production | generation amounts set to three black production | generation tables. And FIG. 11 is a block diagram illustrating a configuration of a computer including a printer driver that incorporates software for realizing black generation and undercolor removal processing.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Scanner part 2 Image processing part 3 Printing part 4 Operation part 5 Control part 11 A / D conversion part 12 Shading correction part 13 Input gradation correction part 14 Area separation processing part 15 Color correction part 16 Black generation under color removal part 17 Space Filter processing unit 18 Gradation reproduction processing unit 18 Output gradation correction unit 19 Gradation reproduction processing unit 21 Character / halftone dot / photo area separation unit 31 Maximum / minimum calculation unit 32 UCR amount calculation unit 33 UCR processing unit 34 Black generation amount calculation Part 41 K table memory (table storage part)
42 Memory access unit (black component calculation unit)
43 Black generation amount calculation part (black component calculation part)
100 Computer 110 Printer Driver 114 Printer Language Translation Unit 115 Communication Port Driver 116 Communication Port 117 Printer K Black Generation Amount K1 Black Generation Amount (Gray Black Component Amount)
K1 Black generation amount (high saturation black component amount)
UCR Undercolor removal amount LUT1 to 3 One-dimensional table MAX Maximum value MID Median value MIN Minimum value SEG Area identification signal

Claims (10)

In an image processing apparatus for converting primary image data composed of a plurality of color components into secondary image data including a black component using a first parameter and a second parameter obtained from pixel values of the data,
A gray table in which a plurality of first parameters are associated with “a gray black component amount that is a black component amount corresponding to a gray image” suitable for each first parameter, a plurality of first parameters, A table storage unit for storing a high saturation table associated with “high saturation black component amount that is black component amount considering saturation” suitable for one parameter;
A parameter calculation unit for calculating the first parameter and the second parameter from the pixel value of the primary image data;
The gray black component amount and the high saturation black component amount suitable for the calculated first parameter are read from both the above tables, and are included in the secondary image data using the black component amount, the first parameter, and the second parameter. A black component calculation unit for determining the amount of black component to be generated,
The black component calculation unit is
The image processing is characterized in that when the difference between the second parameter and the first parameter is within a predetermined offset range, the gray black component amount is set as a black component amount to be included in the secondary image data. apparatus. With respect to primary image data composed of a plurality of color components, the first parameter and the second parameter obtained from the pixel values of this data are used to add black components and remove undercolor to convert the image data into secondary image data. In the image processing apparatus,
A gray table in which a plurality of first parameters are associated with a “gray undercolor removal amount that is an undercolor removal amount corresponding to a gray image” suitable for each first parameter; and a plurality of first parameters; A table storage unit that stores a high saturation table associated with “high saturation undercolor removal amount that is a lower color removal amount considering saturation” suitable for each first parameter;
A parameter calculation unit for calculating the first parameter and the second parameter from the pixel value of the primary image data;
A gray undercolor removal amount and a high saturation undercolor removal amount suitable for the calculated first parameter are read from both the above tables, and the primary image is read using these undercolor removal amount, the first parameter, and the second parameter. And an under color removal calculating unit for obtaining an under color amount to be removed from the data,
The under color removal calculation unit is
An image characterized in that when the difference between the second parameter and the first parameter is within a predetermined offset range, the gray undercolor removal amount is set to a lower color amount to be removed from the primary image data. Processing equipment.   The image processing apparatus according to claim 1, wherein the offset range depends on a value of the first parameter.   The image processing apparatus according to claim 1, wherein the offset range is set by a calculation formula.   The image processing apparatus according to claim 3, wherein the offset range is set by a correspondence table between the offset range and the first parameter.   A printing apparatus comprising the image processing apparatus according to claim 1. In an image processing method for converting primary image data composed of a plurality of color components into secondary image data including a black component using a first parameter and a second parameter obtained from pixel values of the data,
A gray table in which a plurality of first parameters are associated with “a gray black component amount that is a black component amount corresponding to a gray image” suitable for each first parameter, a plurality of first parameters, A storage step of storing a high saturation table associated with “a high saturation black component amount that is a black component amount considering saturation” suitable for one parameter;
A parameter calculating step of calculating the first parameter and the second parameter from the pixel value of the primary image data;
The gray black component amount and the high saturation black component amount suitable for the calculated first parameter are read from both the above tables, and are included in the secondary image data using the black component amount, the first parameter, and the second parameter. A black component calculation step for obtaining a black component amount to be
The above black component calculation step is
The image processing is characterized in that when the difference between the second parameter and the first parameter is within a predetermined offset range, the gray black component amount is set as a black component amount to be included in the secondary image data. Method. With respect to primary image data composed of a plurality of color components, the first parameter and the second parameter obtained from the pixel values of this data are used to add black components and remove undercolor to convert the image data into secondary image data. In the image processing method,
A gray table in which a plurality of first parameters are associated with a “gray undercolor removal amount that is an undercolor removal amount corresponding to a gray image” suitable for each first parameter; and a plurality of first parameters; A table storage step for storing a high saturation table associated with “high saturation undercolor removal amount that is a lower color removal amount considering saturation” suitable for each first parameter;
A parameter calculating step for calculating the first parameter and the second parameter from the pixel value of the primary image data;
A gray undercolor removal amount and a high saturation undercolor removal amount suitable for the calculated first parameter are read from both the above tables, and the primary image is read using these undercolor removal amount, the first parameter, and the second parameter. An under color removal calculating step for obtaining an under color amount to be removed from the data,
The under color removal calculation process is as follows.
An image characterized in that when the difference between the second parameter and the first parameter is within a predetermined offset range, the gray undercolor removal amount is set to a lower color amount to be removed from the primary image data. Processing method.   A computer-readable image processing program for causing a computer to execute each step according to claim 8 or 9.   A recording medium on which the image processing program according to claim 9 is recorded.

Images