JP2005223666A - Image processor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To optimize a conversion coefficient to be used for converting CMY data into CMYK data. <P>SOLUTION: The image processor having a color conversion processing part 3 for converting CMY data into CMYK data by using the conversion coefficient is provided with a coefficient variable part 12 for changing the conversion coefficient, a data conversion part 8 for converting the CMYK data into Lab data when the color conversion processing part 3 converts CMY evaluation reference data supplied from a data supply part 7 into CMYK data by applying the conversion coefficient changed by the coefficient variable part 12, an evaluation data generation part 9 for generating evaluation data for evaluating color reproducibility by using the Lab data, a table storage part 10 for storing a table allowing the evaluation data to correspond to the conversion coefficient, and a coefficient setting part 11 for setting the conversion coefficient corresponding to the evaluation data of which the evaluation of color reproducibility is highest as the conversion coefficient for color conversion in the second color conversion processing part 3. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an image processing apparatus including color conversion means for converting CMY data into CMYK data using a conversion coefficient set for color conversion.

  In image forming apparatuses such as color printers and color copiers that form images using an electrophotographic process, K (black) is added to C (cyan), M (magenta), and Y (yellow), which are the three primary colors of subtractive color mixing. In addition, by printing using four color materials (toners), the total amount of the color materials used is reduced, and the color reproducibility is improved by sharpening the color of black. In addition, when generating CMYK data necessary for forming an image, a first conversion of R (red) G (green) B (blue) data, which is input image data from a scanner or the like, into CMY data. A CMYK data for printing is generated by sequentially performing a color conversion process and a second color conversion process for converting the CMY data generated by the first color conversion process into CMYK data according to a predetermined algorithm. It has been known.

  As an example, in Patent Document 1 below, when converting input RGB data into CMY data, and further converting this CMY data into CMYK data, the minimum value of CMY data is extracted, and this minimum value is nonlinearly converted. Thus, a technique for suppressing the roughness of an image by generating black ink is disclosed. In Patent Document 2 below, the input RGB data and the K data generated according to the RGB data are used to perform CMY data conversion by non-linear conversion without performing UCR (Under Color Removal) processing. Is generated, and final CMYK data for printing is generated by gradation correction using the CMY data and the K data.

JP 2000-13618 A JP-A-11-275374

  Conventionally, when converting CMY data into CMYK data, various parameters set (prepared) in advance for black generation processing and UCR processing are used as conversion coefficients for color conversion. Therefore, if any of the various parameters included in this conversion coefficient is changed, the conversion result of CMYK data, particularly the color gamut range, differs due to the influence. Therefore, for example, if the parameters for black ink generation are individually adjusted to reduce the roughness of the image, the color gamut range that is actually used as print data for the color gamut (Gamut) that can be expressed by a printer, etc. May be narrowed and color reproducibility may be degraded.

  The present invention has been made to solve the above-described problems, and an object of the present invention is to provide an image processing apparatus capable of optimizing conversion coefficients used when converting CMY data into CMYK data. There is to do.

  An image processing apparatus according to the present invention is an image processing apparatus including color conversion means for converting CMY data into CMYK data using a conversion coefficient set for color conversion, and a coefficient variable means for changing the conversion coefficient; The supply means for supplying the CMY evaluation reference data prepared for evaluating the color reproducibility due to the difference of the conversion coefficient to the color conversion means, and the CMY evaluation reference data supplied by the supply means are changed by the coefficient variable means. When the color conversion unit converts the CMYK data into color data on a uniform color space when the color conversion unit converts the converted conversion coefficient into CMYK data, the color data converted by the conversion unit is used. Generating means for generating evaluation data for evaluating color reproducibility, and associating the evaluation data generated by the generating means with a conversion coefficient Storage means for storing the data, and setting means for setting the conversion coefficient corresponding to the evaluation data having the highest evaluation of color reproducibility among the evaluation data stored in the storage means for color conversion in the color conversion means. It is to be prepared.

  In the image processing apparatus according to the present invention, when setting the conversion coefficient used for color conversion in the color conversion unit, the CMY evaluation reference data supplied from the supply unit uses the conversion coefficient changed by the coefficient variable unit. The CMYK data is converted into CMYK data by the color conversion means, and the CMYK data is converted into color data in a uniform color space by the data conversion means, and evaluation data for color reproducibility evaluation is performed using the color data. Generated by the generating means. Therefore, a plurality of different conversion coefficients and corresponding evaluation data can be obtained by sequentially changing the conversion coefficients applied to the color conversion by the color conversion means by the coefficient variable means. Therefore, the conversion coefficients and the evaluation data are associated with each other and stored in the storage unit, and the conversion coefficient corresponding to the evaluation data having the highest evaluation of color reproducibility is set for color conversion in the color conversion unit. Thus, when the CMY data is converted into CMYK data by the color conversion means, it is possible to perform color conversion using a more appropriate conversion coefficient.

  According to the image processing apparatus of the present invention, the evaluation data generated when the CMY evaluation reference data is converted into CMYK data using different conversion coefficients, and the conversion coefficients used for color conversion in generating the evaluation data The conversion coefficient can be optimized by storing the data in association with each other and setting the conversion coefficient having the highest evaluation of color reproducibility among them for color conversion.

  Hereinafter, specific embodiments of the present invention will be described in detail with reference to the drawings.

  FIG. 1 is a block diagram illustrating a configuration example of an image processing apparatus to which the present invention is applied. In the figure, an image input unit 1 inputs RGB data serving as input image data. The first color conversion processing unit 2 converts the RGB data input by the image input unit 1 into CMY data by using, for example, a DLUT (direct lookup table) or matrix calculation.

  The second color conversion processing unit 3 converts the CMY data provided from the first color conversion processing unit 2 into CMYK data using conversion coefficients set in advance for color conversion. This corresponds to the conversion means. The coefficient storage unit 4 stores conversion coefficients used when the second color conversion processing unit 3 performs color conversion.

  The gradation correction unit 5 generates image data (CMYK data) for printing by performing gradation correction on the CMYK data given from the second color conversion processing unit 3. The image output unit 6 prints out an image in accordance with the printing image data provided from the gradation correction unit 5.

  FIG. 2 is a block diagram illustrating an example of an internal configuration of the second color conversion processing unit 3. In the figure, the saturation correction processing unit 31 uses the CMY data input from the image input unit 1 to extract the minimum value K ′ of this CYM data and give it to the black generation processing unit 32. Information Ch on saturation is acquired from the balance of data values and is given to the black generation processing unit 32. Further, the saturation correction processing unit 31 generates correction data C′M′Y ′ in which the saturation of CMY data is corrected, and supplies this correction data C′M′Y ′ to the UCR processing unit 33.

  The black generation processing unit 32 determines the black amount based on the minimum value K ′ and the saturation information Ch given from the saturation correction processing unit 31, and generates black color data K ″ corresponding to the black amount. The UCR processing unit 33 removes a lower color component corresponding to the black generation from the correction data C′M′Y ′ given from the saturation correction processing unit 31. UCA (Under Color The Addition processing unit 34 determines the amplification rate rate of the CMY color data in accordance with the black color data K ″ supplied from the black generation processing unit 32, and adds the amplification rate to the correction data generated from the UCR processing unit 33. By multiplying the rate, the color data C "M" Y "of the three colors is generated and generated from the color data C" M "Y" thus generated and the black generation processing unit 32. Black color data "Becomes equivalent to CMYK data provided by the second color conversion processing section 3 in FIG. 1 the tone correction section 5.

  In the second color conversion processing unit 3 configured as described above, parameters suitable for the respective processes are used in each of the saturation correction processing unit 31, the black generation processing unit 32, the UCR processing unit 33, and the UCA processing unit 34. It is done. In other words, the saturation correction processing unit 31 applies parameters prepared for saturation correction, and the black generation processing unit 32 applies parameters prepared for black generation. Further, the UCR processing unit 33 applies parameters prepared for UCR, and the UCA processing unit 34 applies parameters prepared for UCA. These parameters are stored in advance in the coefficient storage unit 4 as conversion coefficients for performing color conversion in the second color conversion processing unit 3.

  FIG. 3 shows a processing function unit for setting (optimizing) conversion coefficients used for color conversion (CMY → CMYK) in the second color conversion processing unit 3 in the image processing apparatus according to the embodiment of the present invention. It is a block diagram. In the figure, a data supply unit 7 uses CMY evaluation reference data prepared in advance for relatively evaluating conversion coefficients (parameters) applied by the second color conversion processing unit 3 from the viewpoint of color reproducibility. 2 is supplied to the second color conversion processing unit 3.

When the data conversion unit 8 converts the CMY evaluation reference data supplied from the data supply unit 7 into CMYK data by the second color conversion processing unit 3, the CMYK data is looked up for conversion beforehand. It is converted into Lab data according to the table. The Lab data is color data represented by a value of L ^* representing lightness and values (coordinate values) of a ^* and b ^* representing hue and saturation. The Lab data is color data representing a position (point) on a uniform color space, preferably a CIELAB color system color space, which is a device-independent color space such as a printer.

  The evaluation data generation unit 9 generates evaluation data for evaluating color reproducibility using Lab data given from the data conversion unit 8. The table storage unit 10 stores a table in which conversion coefficients are associated with evaluation data. On this table, the conversion coefficient applied when the second color conversion processing unit 3 converts the CMY evaluation reference data into CMYK data, and the second color conversion processing unit 3 applies this conversion coefficient. The generated CMYK data is converted into Lab data by the data conversion unit 8, and the evaluation data generated by the evaluation data generation unit 9 using this Lab data is registered in association with each other.

  The coefficient setting unit 11 refers to the table stored in the table storage unit 10 to extract evaluation data having the highest color reproducibility evaluation from the evaluation data registered in the table, and this evaluation data Is obtained from the table storage unit 10 and set (stored) in the coefficient storage unit 4. The conversion coefficient set in the coefficient storage unit 4 by the coefficient setting unit 11 is the first in the normal print mode in which an image based on the RGB data input from the image input unit 1 is printed out by the image output unit 6. This is applied when CMY data given from the color conversion processing unit 2 is converted into CMYK data by the second color conversion processing unit 3.

  When the second color conversion processing unit 3 performs color conversion using the conversion coefficient stored in the coefficient storage unit 4, the coefficient variable unit 12 changes the conversion coefficient used for the color conversion in advance. It changes in order according to. More specifically, the coefficient storage unit 4 stores conversion coefficients used for color conversion in the second color conversion processing unit 3. This conversion coefficient includes at least one parameter among the above-described four types of parameters (saturation correction parameter, black generation parameter, UCR parameter, UCA parameter). As an example, in the present embodiment, it is assumed that conversion coefficients having the four types of parameters as one data set are stored in the coefficient storage unit 4. In such a case, when changing the conversion coefficient stored in the coefficient storage unit 4, the coefficient variable unit 12 sets initial values of the four types of parameters in advance, and each parameter is set based on the initial values. Slightly change (increase or decrease) the value in order.

  For example, if the initial value of the saturation correction parameter is P1, the initial value of the black generation parameter is P2, the initial value of the UCR parameter is P3, and the initial value of the UCA parameter is P4, these parameters First, only the saturation correction parameters are slightly changed by P1 ± ΔP1, and then only the black generation parameters are slightly changed by P2 ± ΔP2, with reference to the initial values P1, P2, P3, P4 of Next, only the UCR parameter is slightly changed by P3 ± ΔP3, and then only the UCA parameter is slightly changed by P4 ± ΔP4. In this case, the total number of transform coefficients (number of parameter data sets) varied by the coefficient varying unit 12 is nine including the initial value. Also, a composite combination of conversion coefficients when each parameter is slightly changed (for example, the saturation correction parameter is P1 + ΔP1, the black generation parameter is P2 + ΔP2, the UCR parameter is P3, the UCA parameter Including all data sets such as P4, the total number of transform coefficients is 81.

  Next, a processing procedure (image processing method) in the case of actually setting a conversion coefficient for color conversion in the image processing apparatus according to the embodiment of the present invention will be described based on the flowchart of FIG.

  First, when the conversion coefficient setting mode is entered, the initial value of the conversion coefficient stored in the coefficient storage unit 4 is designated by the coefficient variable unit 12, and the color conversion in the second color conversion processing unit 3 is performed accordingly. The conversion coefficient is set to an initial value (step S1). Next, CMY evaluation reference data prepared for conversion coefficient evaluation is supplied from the data supply unit 7 to the second color conversion processing unit 3, and the CMY evaluation reference data is supplied to the second color conversion processing unit 3. Then, the data is converted into CMYK data using the conversion coefficient (step S2).

  FIG. 5 is a diagram showing a specific example of CMY evaluation reference data. First, the CMY evaluation reference data shown in FIG. 5A is obtained by changing the value of C data, the value of M data, and the value of Y data individually by 16 within a range of 0 to 255, respectively. Is generated. In this case, since the number of combinations of CMY data can take 17 values for each color data, the total number is 4913 for 3 colors. On the other hand, the CMY evaluation reference data shown in FIG. 5B includes at least one of the C data value, the M data value, and the Y data value in the range of 0 to 255, respectively. The CMY data is generated by changing the data values of the other colors one by one while fixing the data value of 1 to the maximum value (255). Specifically, the value of the C data and the value of the M data are changed when the value of the M data and the value of the Y data are each changed from 0 to 255 while fixing the value of the C data to the maximum value (255). An example is shown in which the values are changed one by one in order from 0 of the Y data while fixing the values to the maximum value (255).

  Here, when the CMY evaluation reference data shown in FIG. 5A is adopted, the CMY data is evenly distributed to the outer portion of the color gamut indicating the color reproduction range and the inner portion surrounded by the outer portion. In addition, when the CMY evaluation reference data shown in FIG. 5B is adopted, the CMY data is evenly distributed along the outline portion of the color gamut indicating the color reproduction range. Of these, the CMY evaluation reference data shown in FIG. 5A is suitable for roughly evaluating the color gamut and gradation in the entire color gamut because the CMY data is widely distributed throughout the color gamut. Since the CMY evaluation reference data shown in FIG. 5B is a form in which the CMY data is finely distributed in the outline portion of the color gamut, the color gamut and gradation are precisely evaluated in the outline portion of the color gamut. It will be suitable for

  Next, the CMYK data is sent from the second color conversion processing unit 3 to the data conversion unit 8, and the CMYK data is converted into Lab data by the data conversion unit 8 (step S3).

  Next, the Lab data is sent from the data conversion unit 8 to the evaluation data generation unit 9, and evaluation data based on the Lab data is generated by the evaluation data generation unit 9 (step S4).

  Here, an evaluation data generation method applied to the evaluation data generation unit 9 will be described. First, the color gamut (Gamut) that can be expressed when an image is printed by the image processing apparatus is a color of the CIELAB color system when the data value of each color of CMY is changed by 1 within a range of 0 to 255. This is expressed as the maximum color reproduction range (hereinafter referred to as the maximum color reproduction range) defined on the space (uniform color space). This maximum color reproduction range can be represented three-dimensionally in the LAB space as shown in FIG. Whether or not this maximum color gamut can be used effectively depends on the color gamut (actual color gamut) when the CMY evaluation reference data is actually converted into CMYK data by the second color conversion processing unit 3. It depends on what percentage (%) it has for the reproduction range. Although it is ideal that the actual color gamut has a color gamut equivalent to the maximum color gamut, the ratio (%) of the actual color gamut to the maximum color gamut is determined by the second color conversion processing unit 3. Since it depends on the conversion coefficient used for color conversion, it is important to optimize the conversion coefficient for color conversion.

Therefore, in this embodiment, the ratio of the actual color gamut to the maximum color gamut is used as the gamut usage rate, and this gamut usage rate (%) is one of the evaluation data for color reproducibility evaluation. As described above, it is determined by the evaluation data generation unit 9. That is, when color conversion (CMY → CMYK → Lab) is performed using the CMY evaluation reference data shown in FIGS. 5A and 5B, Lab data indicating the outline portion of the actual color reproduction range is obtained. Therefore, using this Lab data, C ^* representing saturation (distance from the L * axis representing lightness) in the LAB space is obtained by a calculation formula of “C ^* = √ (a ^{* 2} + b ^{* 2} )”. . Thereby, as shown in FIG. 7, correlation data of L * and C ^* is obtained. This correlation data indicates the color reproduction range when the LAB space is sectioned along the L * axis.

  In such a case, in FIG. 7, for example, if the maximum color reproduction range is an area surrounded by a solid line in the drawing and the actual color reproduction range is an area surrounded by a broken line in the drawing, the size of each area The color gamut usage rate can be obtained from the thickness (area). Specifically, assuming that the color gamut usage rate is R (%), the maximum color reproduction gamut size is S1, and the actual color reproduction gamut size is S2, the calculation formula R (%) = S2 / S1 × 100. The color gamut usage rate can be obtained by However, since the gamut usage rate is actually obtained for each hue, the average value of the gamut usage rate for each hue is finally obtained as a representative value. The representative value (average value) of the color gamut usage rate is a value that approximates the volume ratio of the maximum color reproduction area and the actual color reproduction area that are three-dimensionally represented in the LAB space.

  Next, evaluation data is sent from the evaluation data generation unit 9 to the table storage unit 10, and this evaluation data is stored (registered) in association with the conversion coefficient used for generating the evaluation data in the table of the table storage unit 10. (Step S5).

  Next, it is determined whether or not the processing for all conversion coefficients has been completed (step S6). For example, when the number of transform coefficients changed by the coefficient variable unit 12 is N, N evaluation data corresponding to the N transform coefficients are stored in the table storage unit 10. It is determined that the process has been completed, and it is determined that the process has not been completed.

  If it is determined in step S6 that No (the processing has not been completed), after the conversion coefficient used for color conversion in the second color conversion processing unit 3 is changed in the coefficient variable unit 12 (step S7), the above The processing of steps S2 to S5 is performed, and the evaluation data corresponding to the conversion coefficient is stored in the table of the data storage unit 10.

  After that, if it is determined Yes in step S6 (processing is completed), the table data stored in the table storage unit 10 is referred to by the coefficient setting unit 11 and the color reproducibility is determined based on the table data. A conversion coefficient corresponding to evaluation data having the highest evaluation is extracted, and the conversion coefficient is stored in the coefficient storage unit 4 in order to set the conversion coefficient for color conversion in the second color conversion processing unit 3 (step S8). In this case, the evaluation data having the highest color gamut usage rate obtained as described above is extracted as the evaluation data having the highest evaluation of color reproducibility. The conversion coefficient is stored by rewriting (updating) the values of various parameters included in the conversion coefficient. Also, using the conversion coefficient obtained in the flow of FIG. 4 as an initial value, the process of obtaining the correspondence between the conversion coefficient and the evaluation data is performed again by the flow of FIG. 4, and extraction of the conversion coefficient and storage of the conversion coefficient are repeated.

  By performing such setting processing, it is possible to optimize the conversion coefficient used when the second color conversion processing unit 3 performs color conversion (CMY → CMYK). As a result, the image output unit 6 can print out an image by effectively using a color gamut that can be expressed by the image processing apparatus. Therefore, it is possible to improve color reproducibility when printing an image with the image processing apparatus.

  In addition, the evaluation of color reproducibility is not limited to the evaluation of only the color gamut (color gamut usage rate), and it is desirable to add an evaluation of gradation. The superiority or inferiority of the gradation is evaluated according to how accurately the gradation of the original CMY evaluation reference data is reflected in the Lab data when the CMY evaluation reference data is converted from CMYK data to Lab data. For example, as shown in FIG. 8A, when the CMY evaluation reference data in which only the value of the C data is uniformly changed so as to form an even data arrangement in the CMY space is adopted, this CMY evaluation reference data is used. If the data obtained by converting CMYK data to Lab data is an array of data strings having uniform color differences even in the Lab space as shown in FIGS. It is determined that the data is maintained well, and if the color difference is a non-uniform data string as shown in FIGS. 8D and 8E, it is determined that the gradation is deteriorated. Quantitatively, the degree of variation in color difference between adjacent data in the LAB space is obtained as a standard deviation, and it is determined that the gradation is better as the standard deviation is smaller.

  As an example of data conversion, FIG. 9 shows CMY evaluation criteria for a total of 256 data sets in which the value of C data is fixed at 255 and the value of M data and Y data are changed by 1 in the range of 0 to 255 respectively. As data, the CMYK data is converted into CMYK data using the initial value of the conversion coefficient, and the CMYK data is converted into Lab data by the data converter 8.

  Further, when both the color gamut usage rate and gradation are used as evaluation items for color reproducibility, they are comprehensively evaluated. Various methods for comprehensive evaluation are conceivable. In the present embodiment, a comprehensive evaluation method based on a point system is adopted as an example. For example, as shown in FIG. 10, when the conversion coefficient data set is prepared in order from No. 1 and No. 1 is the initial value of the conversion coefficient, the color gamut obtained by applying different conversion coefficients to each other. Using the usage rate and the gradation evaluation value (standard deviation value), a comprehensive evaluation point is obtained for each conversion coefficient.

  The comprehensive evaluation point is generated by the evaluation data generation unit 9 as one of the evaluation data, similarly to the color gamut usage rate and the gradation evaluation value. In the example, numbers (No.) are assigned to the conversion coefficient data sets in order from No. 1, and the color gamut usage rate and gradation corresponding to the No. 1 conversion coefficient (initial value) are matched to this number. The evaluation values are R1 and E1, respectively, the color gamut usage rate corresponding to the No. 2 conversion coefficient and the gradation evaluation value are R2 and E2, respectively, and the color gamut usage rate and the floor corresponding to the No. 3 conversion coefficient. The tonality evaluation values are R3 and E3, respectively, and the color gamut usage rate and the tone evaluation value corresponding to the conversion coefficient No. 4 are R4 and E4, respectively (the description is omitted for No. 5 and later). The total evaluation point (Point) of the color gamut usage rate and the gradation evaluation value obtained when the initial value (No. 1 conversion coefficient) is applied to the conversion coefficient is set to 100, and No. 2 based on this. Comprehensive evaluation points are calculated when the subsequent conversion coefficients are applied. Specifically, the total evaluation point is calculated by a calculation formula of Point = 50 × (Rn / R1 + E1 / En) (n is a positive integer and corresponds to a conversion coefficient number). In this case, the evaluation of the color gamut usage rate and the evaluation of the gradation may be weighted to make a difference between the dominance levels.

  Thus, when evaluating color reproducibility from both sides of the color gamut usage rate and gradation, the coefficient setting unit 11 obtains the total evaluation point that comprehensively evaluates them, so that the coefficient setting unit 11 is the most out of them. A conversion coefficient with a high overall evaluation (points) (No. 3 conversion coefficient in the range of No. 1 to No. 4 in FIG. 10) is extracted, and this conversion coefficient is the color in the second color conversion processing unit 3. It will be set for conversion. Therefore, not only the color gamut usage rate is high, but also color reproducibility including gradation is evaluated, and the second color conversion processing unit 3 performs color conversion using a conversion coefficient suitable for this. be able to. As a result, the color reproducibility can be further improved.

It is a block diagram which shows the structural example of the image processing apparatus to which this invention is applied. It is a block diagram which shows an example of an internal structure of a 2nd color conversion process part. It is a block diagram which shows the processing function part for setting (optimizing) the conversion coefficient used for the color conversion in the 2nd color conversion process part in the image processing apparatus which concerns on embodiment of this invention. It is a flowchart which shows the process sequence in the case of setting the conversion coefficient for color conversion with the image processing apparatus which concerns on embodiment of this invention. It is a figure which shows an example of CMY evaluation reference | standard data. It is a figure explaining the color gamut on the color space of CIELAB color system. It is a conceptual diagram explaining the evaluation example of a color gamut. It is a conceptual diagram explaining the evaluation example of gradation property. It is a figure which shows an example of data conversion. It is a figure which shows an example of comprehensive evaluation of color reproducibility.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 3 ... 2nd color conversion process part, 4 ... Coefficient storage part, 7 ... Data supply part, 8 ... Data conversion part, 9 ... Evaluation data generation part, 10 ... Table storage part, 11 ... Coefficient setting part, 12 ... Coefficient Variable unit, 31 ... saturation correction processing unit, 32 ... black generation processing unit, 33 ... UCR processing unit, 34 ... UCA processing unit

Claims (4)

An image processing apparatus comprising color conversion means for converting CMY data into CMYK data using a conversion coefficient set for color conversion,
Coefficient variable means for changing the conversion coefficient;
Supply means for supplying CMY evaluation reference data prepared for evaluating color reproducibility due to the difference in the conversion coefficient to the color conversion means;
When the color conversion unit converts the CMY evaluation reference data supplied by the supply unit into CMYK data by applying the conversion coefficient changed by the coefficient variable unit, the CMYK data is converted into a uniform color space. Data conversion means for converting to color data;
Generating means for generating evaluation data for evaluating color reproducibility using the color data converted by the converting means;
Storage means for storing the evaluation data generated by the generating means in association with the conversion coefficient;
Setting means for setting the conversion coefficient corresponding to the evaluation data having the highest evaluation of color reproducibility among the evaluation data stored in the storage means for color conversion in the color conversion means. An image processing apparatus. The image processing apparatus according to claim 1, wherein the conversion coefficient includes a parameter applied to at least one of black generation processing, UCR processing, UCA processing, and saturation correction processing. The generation unit generates evaluation data indicating the color gamut and gradation that the color data can take on the uniform color space as the evaluation data,
The said setting means sets the said conversion coefficient corresponding to the evaluation data with the highest comprehensive evaluation of the said color gamut and the said gradation property for the color conversion in the said color conversion means. Image processing device. The image processing apparatus according to claim 1, wherein the color data is Lab data.

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