JP2014042119A - Data processing device and data processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To suppress variations in appearance of color, caused by variations in color-matching functions, without increasing the number of primary colors used by a device.SOLUTION: A target spectral data acquisition part 6 acquires target spectral data. A primary color spectral property setting part 8 sets a plurality of pieces of primary color spectral data which show spectral properties of each of a plurality of primary colors. A gain calculation part 10 and a color-matching spectral data calculation part 11 calculate RGB gains and obtain color-matching spectral data so that the set primary color spectral data are color-matched with the target spectral data. A color fluctuation calculation part 12 calculates variation evaluation values which show variations in appearance of color in the target spectral data and the color-matching spectral data on the basis of a plurality of color-matching functions obtained by a color-matching function acquisition part 7. An evaluation result determination part 13 selects data having the smallest variation evaluation value from the plurality of pieces of primary color spectral data as an optimization result.

Description

  The present invention relates to a data processing apparatus and a data processing method for faithfully reproducing a color of a reference image on a device.

  In recent years, in color management technology, an extended color space that is wider than the sRGB color space, which is a conventional standard color space, has been proposed in order to improve the color reproducibility of highly saturated colors. Along with the technical trend of widening the color gamut, in image display devices such as display devices, the size of the color reproduction range is regarded as important in order to faithfully reproduce the color of highly saturated content. For example, in liquid crystal displays, the spectral characteristics of the three primary colors of RGB are narrowed by improving color filters and backlights, and so-called narrow-band spectral characteristics improve the color purity of the three primary colors and expand the color reproduction range. doing.

  In general, color reproduction in an image display device is based on so-called colorimetric color reproduction, and even if the spectral characteristics are different, they appear to be the same color if the tristimulus values calculated using the color matching functions match.

  On the other hand, research is also being conducted on visual characteristics of human colors, that is, variations in color matching functions. For example, CIE (International Commission on Illumination) proposes a CIE170-1 model in which the color matching function varies depending on age and viewing angle as a visual characteristic variation model. In the CIE170-1 model, human visual characteristics, that is, color matching functions, are not always constant, but change according to individual differences (age differences) and viewing angle differences. Due to such variations in color matching functions, colorimetric color reproduction technology based on the color matching functions of standard observers may cause individual differences in color appearance and may not always provide satisfactory color matching results. is there.

  Therefore, as a technology to suppress the change in color appearance due to variations in the color matching function while expanding the color reproduction range of image equipment, a technology that reproduces images using six primary colors more than three primary colors is proposed. (For example, see Patent Document 1).

JP 2003-141518 A

  However, according to the technique described in Patent Document 1, the number of primary colors increases with respect to the three primary colors (RGB) used in a normal display. In order to realize such multi-primary color reproduction, it is necessary to increase the complexity and size of device devices, such as displaying images superimposed on multiple projectors of different primary colors, resulting in high costs. It becomes the cause of the conversion.

  In view of the above problems, an object of the present invention is to perform color reproduction while suppressing variations in color appearance due to variations in color matching functions without increasing the number of primary colors used in the device.

  As a means for achieving the above object, a data processing apparatus of the present invention comprises the following arrangement. That is, a data processing apparatus for determining spectral characteristics for a plurality of primary colors used in a device, the target spectral data acquiring means for acquiring target spectral data indicating the spectral characteristics of the target color, and the spectral characteristics of each of the plurality of primary colors Primary color spectral data setting means for setting primary color spectral data indicating characteristics, uniform color spectral data calculating means for calculating uniform color spectral data that is the same color as the target spectral data from the primary color spectral data, and a plurality of identical colors Color variation for calculating a variation evaluation value indicating a color appearance variation amount based on the plurality of color matching functions between the target spectral data and the color matching spectral data, and a color matching function acquisition unit for acquiring a function Of the plurality of primary color spectral data set by the calculation means and the primary color spectral data setting means, the variation evaluation value is the smallest. Anda selection means for selecting from, the primary spectral data selected by said selecting means, and determines as the optimum spectral characteristics of the plurality of primary colors used in the device.

  The present invention makes it possible to perform color reproduction while suppressing variations in color appearance due to variations in color matching functions without increasing the number of primary colors used in the device.

FIG. 2 is a block diagram showing the configuration of the image processing apparatus according to the first embodiment of the present invention; Flowchart showing spectral data optimization processing in the first embodiment, The figure which shows the UI example for the optimization condition setting in 1st execution form, The figure which shows the example UI for the optimization result display in 1st execution form, The figure which shows the example UI for the optimization result display in 1st execution form, A block diagram showing a configuration of an image processing apparatus in the second embodiment, A flowchart showing an optimal device selection process in the second embodiment, The figure which shows the UI example for the optimization result display in 2nd execution form, It is a figure which shows the example of a fluctuation | variation of a color matching function.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. The following embodiments do not limit the present invention related to the scope of claims, and all combinations of features described in the present embodiments are essential for the solution means of the present invention. Is not limited.

<First Embodiment>
Apparatus Configuration The configuration of the image processing apparatus in this embodiment will be described with reference to the block diagram of FIG. In the figure, reference numeral 1 denotes a data processing apparatus of the present embodiment, which determines (optimizes) the spectral characteristics of the RGB three primary colors used for color reproduction in an image display device. The optimization result by the data processing device 1 is stored in the optimization result storage unit 14 and displayed on the optimization result display device 15 such as a PC display. Reference numeral 2 denotes a target spectral data storage unit that stores spectral data of the target color. Reference numeral 3 denotes an optimization condition setting unit that sets the wavelength range, step width, and the like of the spectral characteristics of the RGB three primary colors to be optimized. Reference numeral 4 denotes a color gamut constraint condition setting unit that sets a constraint condition (for example, a reference color gamut) related to the color gamut when the spectral characteristics of the RGB three primary colors are optimized. Reference numeral 5 denotes a color matching function storage unit for storing a plurality of color matching functions.

  In the data processing apparatus 1, the target spectral data acquisition unit 6 reads the target spectral data stored in the target spectral data storage unit 2, and the color matching function acquisition unit 7 is stored in the color matching function storage unit 5. Read color matching function data. The primary color spectral data setting unit 8 sets primary color spectral data indicating the spectral characteristics of the primary color based on the conditions set by the optimization condition setting unit 3. The color gamut determining unit 9 determines how much the color gamut based on the primary color spectral data set by the primary color spectral data setting unit 8 satisfies the condition set by the color gamut constraint condition setting unit 4. The gain calculation unit 10 calculates an RGB gain for making the primary color spectral data the same color as the target spectral data. The color matching spectral data calculation unit 11 calculates color matching spectral data based on the gain calculated by the gain calculation unit 10. The color variation calculation unit 12 is based on a plurality of color matching functions stored in the color matching function storage unit 5, and the color shift between the color matching spectral data calculated by the color matching spectral data calculation unit 11 and the target spectral data Is calculated. The evaluation result determination unit 13 determines whether or not the color variation amount calculated by the color variation calculation unit 12 is minimum.

● Optimization processing of primary color spectral data (overall)
FIG. 2 is a flowchart showing image processing performed in the data processing apparatus 1 of the present embodiment having the configuration shown in FIG. 1, that is, optimization processing of spectral data of RGB three primary colors.

  First, in S201, the target spectral data acquisition unit 6 reads target spectral data indicating the target spectral characteristics stored in the target spectral data storage unit 2. In S202, the color matching function acquisition unit 7 reads a plurality of color matching functions stored in the color matching function storage unit 5. Next, in S203, the optimization condition setting unit 3 sets optimization conditions indicating spectral characteristic setting conditions (wavelength range, step width, etc.) for each primary color in the RGB three primary colors. Details of the optimization condition setting process will be described later.

  Next, in S204, the primary color spectral data setting unit 8 sets primary color spectral data indicating the spectral characteristics of the RGB three primary colors to initial values based on the conditions set by the optimization condition setting unit 3. In S205, the color gamut determination unit 9 calculates a color gamut that can be reproduced by the primary color spectral data set in S204, and the calculated color gamut is the color gamut constraint set by the color gamut constraint condition setting unit 4. The degree to which the condition is satisfied is determined. Specifically, the ratio (coverage) in which the color gamut that can reproduce the primary color spectral data includes the reference color gamut set as the color gamut constraint condition is calculated. In S206, the gain calculation unit 10 calculates the RGB gain so as to be the same color as the target spectral data acquired in S201. Details of the gain calculation processing will be described later.

  In step S207, the color matching spectral data calculation unit 11 calculates the color matching spectral data by multiplying the primary color spectral data set by the primary color spectral data setting unit 8 by the RGB gain calculated by the gain calculation unit 10. To do. In S208, the color variation calculation unit 12 calculates a color variation amount with respect to the target spectral data by using a plurality of color matching functions stored in the color matching function storage unit 5 for the color matching spectral data calculated in S207. This is used as a variation evaluation value. Details of the evaluation value calculation process will be described later.

  Then, in S209, the evaluation result determination unit 13 determines whether or not the variation evaluation value calculated in S208 is the smallest among the evaluation values calculated so far, and if it is the minimum, the process proceeds to S210. If it is, proceed to S212.

  In S210, the evaluation result determination unit 13 assumes that the currently set primary color spectral data is the primary color spectral data optimal for the plurality of color matching functions stored in the color matching function storage unit 5. In other words, the memory area in which the primary color spectral data as the optimization result in this embodiment is temporarily stored is updated with the currently set primary color spectral data. In step S211, the evaluation result determination unit 13 stores the evaluation value calculated in step S208 and the color gamut calculated in step S205 for the optimal primary color spectral data. In S210 and S211, the primary color spectral data, the evaluation value, and the color gamut are assumed to be stored in an internal memory (not shown) in the evaluation result determination unit 13.

  In S212, it is determined whether or not evaluation value calculation has been completed for all primary color spectral data corresponding to the optimization conditions set in S203. If completed, the process proceeds to S214, and if not completed, the process proceeds to S213. Proceed to In S213, the primary color spectral data setting unit 8 updates the primary color spectral data to an unprocessed one and returns to S205. In S214, the optimization result of the primary color spectral data is stored in the optimization result storage unit 14 and displayed on the optimization result display device 15. Details of this display processing will be described later.

Optimization condition setting process (S203)
Here, the setting process of the optimization conditions for the primary color spectral data in S203 will be described in detail. FIG. 3 is an example of a user interface (hereinafter referred to as UI) for setting optimization conditions for primary color spectral data. In the present embodiment, the spectral data of the three primary colors of RGB are modeled with a Gaussian distribution by changing them within the ranges specified by the peak wavelength and the standard deviation, as indicated by 301, 302, and 303 in FIG. That is, in this embodiment, a plurality of types are sequentially set as combinations of RGB primary color spectral data in accordance with the optimization conditions set in the UI, and subsequent optimization processing is performed for each combination.

  In the present embodiment, a color space as a reference color gamut can be designated in order to compare the color gamut after optimization of the primary color spectral data with a predetermined color gamut (reference color gamut). Reference numeral 304 in FIG. 3 is an area for designating a reference color gamut. For example, a specific color gamut such as sRGB or AdobeRGB can be designated as the reference color gamut. The reference color gamut specified here is the color gamut constraint condition. As the reference color gamut, the chromaticity (xR, yR), (xG, yG), (xB, yB) of the RGB three primary colors may be directly designated numerically.

RGB gain calculation processing (S206)
Hereinafter, the RGB gain calculation method in S206 will be described in detail. Here, it is assumed that the target spectral data is S_target (λ), and the RGB three primary color spectral data to be equalized in the target spectral data are R (λ), G (λ), and B (λ), respectively. Also, if the reference color matching functions used for color matching are x ~ (λ), y ~ (λ), z ~ (λ), the tristimulus values of R (λ), G (λ), B (λ) XR, YR, ZR, XG, YG, ZG, XB, YB, and ZB are calculated by the following equation (1). Here, the notation of “x˜ (λ)” represents a color matching function (x bar) with a bar on top of x.

  Further, tristimulus values of the target spectral data S_target (λ) are set as X_target, Y_target, and Z_target. In order to make the tristimulus value by the color mixture of the RGB tristimulus value calculated by the equation (1) equal to the tristimulus value of the target spectrum, the RGB gain (r, g, b shown in the following equation (2): ).

  Therefore, by changing the equation (2), the RGB gain can be calculated by the following equation (3).

● Evaluation value calculation process (S208)
Hereinafter, the evaluation value calculation method in S208 will be described in detail. The color matching spectral data calculated in S207 is different in spectral characteristics from the target spectral data, but the visual characteristics conform to the reference color matching functions x ~ (λ), y ~ (λ), z ~ (λ) described above. For the observer, the so-called conditional color is established, in which they look the same color. However, for an observer whose visual characteristics are different from the reference color matching function, the color matching relationship between the color matching spectral data calculated in S207 and the target spectral data does not hold, that is, they do not look the same color.

  Here, as color matching functions different from the reference color matching functions, for example, color matching functions x to _20,10 (λ), y calculated by parameter setting of age 20 years and viewing angle 10 degrees in the CIE170-1 model Consider ~ _20,10 (λ) and z ~ _20,10 (λ). When this color matching function (hereinafter, set color matching function) is used, the tristimulus values (X_target_20, 10, Y_target_20, 10, Z_target_20, 10) of the target spectral data S_target (λ) are expressed by the following equation (4). Is calculated.

  Similarly, tristimulus values (X_RGB_20, 10, Y_RGB_20, 10, Z_RGB_20, 10) of the color matching spectral data S_RGB (λ) using the set color matching function are calculated by the following equation (5).

  As described above, the tristimulus value of the target spectral data S_target (λ) and the tristimulus value of the color matching spectral data S_RGB (λ) calculated by the equations (4) and (5) are different from each other. A shift in appearance occurs. This deviation is calculated by the following equation (6) in the Lab space.

  Here, in FIG. 9 (a), (b), (c), in the CIE170-1 model, the age is 20 to 60 years (10-year interval), the viewing angle is 2 to 10 degrees (1 degree interval) The variation of the set color matching functions x˜ (λ), y˜ (λ), z˜ (λ) when the parameters are changed is shown. Note that the target spectral data is CIE standard light source D50. However, since the CIE170-1 model is a model of the spectral sensitivity of the LMS cone, the LMS sensitivity is shown in FIGS. 9 (a), (b), and (c) in the 3 × 3 matrix. Graphs converted into (λ), y˜ (λ), and z˜ (λ) are shown. In the present embodiment, a plurality of such color matching functions are held in the color matching function storage unit 5, and the color variation amount E is calculated by using the following equation (7) for the plurality of color matching functions, for example. To do. The variation amount E calculated by the equation (7) is the color variation amount of the color matching spectral data S_RGB (λ) with respect to the target spectral data S_target (λ), and this is used as a variation evaluation value.

  Note that a * age, size, b * age, and size in equation (7) indicate values for each color matching function, and correspond to a * and b * in equation (6). That is, a * and b * in Equation (6) represent a * 20,10 and b * 20,10, respectively.

● Optimization result display (S214)
Hereinafter, the display processing of the optimization result in S214 will be described in detail. In this embodiment, in S211, the color appearance variation evaluation value E (calculated in S208) and the color gamut (calculated in S205) with respect to the change in the color matching function for the optimal primary color spectral data are held. These are displayed together with information on optimization results (calculated in S210) on a UI as shown in FIG. 4, for example.

  In FIG. 4, 401 is an area for displaying a primary color spectral data graph that minimizes the color appearance variation evaluation value E, that is, an optimization result in this embodiment. Reference numeral 402 denotes an area for displaying numerical data of the peak wavelength and half-value width of the primary color spectral data displayed in 401. Reference numeral 403 denotes an area for displaying a graph representing the color appearance variation in the optimized primary color spectral data on the Lab plane. Reference numeral 404 denotes an area for displaying a graph in which the corresponding color gamut of the optimized primary color spectral data is compared on the xy chromaticity diagram with the color gamut specified by the UI shown in FIG.

  However, the result display in the present embodiment is not limited to displaying only the primary color spectral data with the smallest evaluation value, that is, optimized, and other display methods can also be applied. For example, evaluation results may be stored for all processed primary color spectral data, and the evaluation results to be displayed may be switched according to the user's selection. Specifically, as shown in the UI of FIG. 5, an area 505 for displaying the relationship between the color gamut and the color appearance variation evaluation value is provided, and the evaluation result for the primary color spectral data designated by the user based on the display is displayed. As with the UI in FIG. 4, it may be displayed in the areas 501 to 504. Note that the horizontal axis in the area 505 indicates the identification number when the combinations of RGB spectral data are arranged, for example, in the order of fluctuation evaluation values.

  In addition, although reference color gamut (color space) can be specified in 304 of FIG. 3, for example, using the color gamut data calculated in S205, the color gamut of the color space specified in 304 (for example, Adobe RGB) is changed. It is also possible to optimize under the constraint of 100% inclusion. Alternatively, a numerical value input unit for designating the color gamut coverage may be separately provided, and optimization may be performed under a constraint condition that covers a color gamut that is greater than the designated numerical value.

  As described above, according to the present embodiment, primary color spectral data can be optimized for a plurality of color matching functions. By performing image display on the image display device using the three primary colors having the spectral characteristics optimized in this way, the color appearance change with respect to the change in the color matching function can be achieved while satisfying the desired color gamut. Less color reproduction can be performed.

<Second Embodiment>
Hereinafter, a second embodiment according to the present invention will be described. In the first embodiment described above, a method of approximating and optimizing primary color spectral data with a mathematical formula has been described. In the second embodiment, a description will be given of a method of selecting a device with the smallest color variation when matching with a target device from primary color spectral data of a plurality of devices stored in advance.

  FIG. 6 shows a block configuration of the data processing device according to the second embodiment. In the figure, reference numeral 601 denotes the data processing apparatus of the second embodiment, and among the given primary color spectral data, the optimal primary color spectral data is selected by performing the same optimization process as in the first embodiment. The optimization result (selection result) of the primary color spectral data is stored in the optimization result storage unit 612 and displayed on the optimization result display device 613 such as a PC display. Reference numeral 602 denotes a target spectroscopic data measuring apparatus such as a spectrophotometer that measures spectroscopic data of a target device, and reference numeral 603 denotes a primary color spectroscopic data storage unit that stores primary color spectroscopic data in a plurality of devices. A color matching function storage unit 604 stores a plurality of color matching functions.

  In the data processing device 601, the target spectral data acquisition unit 605 reads the target spectral data measured by the target spectral data measurement device 602, and the color matching function acquisition unit 606 is stored in the color matching function storage unit 604. Load color function. The primary color spectral data input unit 607 reads primary color spectral data stored in the primary color spectral data storage unit 603. The gain calculation unit 608 calculates an RGB gain for making the primary color spectral data the same color as the target spectral data. The color matching spectral data calculation unit 609 calculates color matching spectral data based on the gain calculated by the gain calculation unit 608. The color variation calculation unit 610 is a color shift between the color matching spectral data calculated by the color matching spectral data calculation unit 609 and the target spectral data based on a plurality of color matching functions stored in the color matching function storage unit 604. Is calculated. The evaluation result determination unit 611 determines whether the color variation amount calculated by the color variation calculation unit 610 is the minimum.

● Optimization processing of primary color spectral data (overall)
FIG. 7 is a flowchart showing image processing performed in the data processing apparatus 601 of the second embodiment having the configuration shown in FIG. 6, that is, optimal device selection processing.

  First, in step S701, the target spectral data measurement device 602 measures spectral data of a device that is a matching target. In step S702, the color matching function acquisition unit 606 stores a plurality of color matching functions stored in the color matching function storage unit 604. Is read. In step S <b> 703, the primary color spectral data input unit 607 reads the primary color spectral data of a plurality of devices stored in the primary color spectral data storage unit 603 into the data processing apparatus 601.

  Next, in S704, the target device to be subjected to color appearance variation evaluation is set to an initial value, and in S705, the gain calculation unit 608 matches the target spectral data acquired in S201 with the same color as in the first embodiment. The RGB gain of the primary color spectral data is calculated.

  In step S706, the color matching spectral data calculation unit 609 uses the primary color spectral data input by the primary color spectral data input unit 607 and the RGB gain calculated by the gain calculation unit 608 in the same manner as in the first embodiment. Spectral data is calculated. In S707, as in the first embodiment, the color variation calculation unit 610 calculates color variations for a plurality of color matching functions stored in the color matching function storage unit 604, and uses these as evaluation values.

  In S708, the evaluation result determination unit 611 determines whether or not the evaluation value calculated in S707 is the smallest among the evaluation values calculated so far. Proceed to S710. In S709, the evaluation result determination unit 611 updates the currently set device as the optimum device, and the process proceeds to S710. In S710, it is determined whether evaluation value calculation has been completed for all the devices read in S703. If completed, the process proceeds to S712, and if not completed, the process proceeds to S711. In S711, the target device is updated to an unprocessed device, and the process returns to S705. In S712, the optimum device is stored in the optimization result storage unit 712 and displayed on the optimization result display device 613. Details of this display processing will be described later.

Optimization result display (S712)
Hereinafter, the optimization result in S712, that is, the display process of the optimum device will be described in detail. In the second embodiment, for each of the evaluation target devices, a color appearance variation evaluation value with the target device is calculated and displayed as an optimization result on a UI as shown in FIG. 8, for example.

  In FIG. 8, 801 is an area for displaying the device names of target devices, and 802 is an area for displaying the device names of a plurality of devices to be evaluated. An area 803 displays a device name having the smallest evaluation value, that is, a device name with a small variation in color appearance. Reference numeral 804 denotes an area for displaying an evaluation value for variation in color appearance of each device, and 805 indicates a difference in evaluation value for each color on the Lab plane with respect to the device having the smallest evaluation value or the device designated by the user. This area is displayed as a bubble chart. The display of areas 804 and 805 is not essential.

  In the second embodiment, the target spectral data is measured by the target spectral data measuring device 602, and the primary color spectral data of the evaluation target device is stored in the primary color spectral data storage unit 603 in advance. The invention is not limited to this method. For example, target spectral data that has been separately measured may be read, or primary color spectral data of the evaluation target device may be obtained by measurement. Similarly to the first embodiment described above, a reference color gamut may be designated, and information on a color gamut reproducible by a selected device may be displayed in contrast with the reference color gamut.

  As described above, according to the second embodiment, based on the spectral characteristics of the target image display device and the image display device that reproduces a color image, an image having the smallest variation in color appearance due to a change in the color matching function. A display device can be selected.

  The present invention is not limited to the configurations and processes shown in the first and second embodiments described above. For example, the processing target device is not limited to the image display device, and for example, the spectral characteristics of ink and toner may be optimized for a printer that is a printing device. Furthermore, as an example of using the change in color matching function according to the CIE170-1 model as a variation in color matching function, the present invention is not limited to this example. It is also possible to use actual measurement data obtained by performing the above.

<Other embodiments>
The present invention is also realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and the computer of the system or apparatus (or CPU, MPU, etc.) reads the program. It is a process to be executed.

Claims (10)

A data processing apparatus for determining spectral characteristics of a plurality of primary colors used in a device,
Target spectral data acquisition means for acquiring target spectral data indicating spectral characteristics of the target color;
Primary color spectral data setting means for setting primary color spectral data indicating spectral characteristics of each of the plurality of primary colors;
Color matching spectral data calculation means for calculating color matching spectral data having the same color as the target spectral data from the primary color spectral data,
Color matching function acquisition means for acquiring a plurality of color matching functions;
Color variation calculation means for calculating a variation evaluation value indicating a variation amount of color appearance based on the plurality of color matching functions between the target spectral data and the color matching spectral data;
Selecting means for selecting the smallest fluctuation evaluation value among the plurality of primary color spectral data set by the primary color spectral data setting means,
The data processing apparatus, wherein the primary color spectral data selected by the selection unit is determined as an optimal spectral characteristic of the plurality of primary colors used in the device. Furthermore, it has an input means for inputting spectral characteristic setting conditions for each color set by the primary color spectral data setting means,
2. The data processing apparatus according to claim 1, wherein the primary color spectral data setting unit sets a plurality of the primary color spectral data according to the setting condition. Furthermore, it has holding means for holding the primary color spectral data for a plurality of devices in advance,
2. The data processing apparatus according to claim 1, wherein the primary color spectral data setting unit sets a plurality of the primary color spectral data held in the holding unit.   4. The data processing apparatus according to claim 1, further comprising a result display unit that displays information about the primary color spectral data selected by the selection unit.   5. The data processing apparatus according to claim 4, wherein the result display unit displays information on the variation amount in the primary color spectral data selected by the selection unit.   6. The data processing apparatus according to claim 4, wherein the result display unit displays information about all the primary color spectral data set by the primary color spectral data setting unit. Furthermore, it has a reference color gamut specifying means for specifying the reference color gamut,
7. The result display means displays information on a color gamut reproducible by the primary color spectral data selected by the selection means in contrast with the reference color gamut. The data processing device according to item.   8. The data processing apparatus according to claim 1, wherein the color matching function acquisition unit acquires a plurality of color matching functions according to a CIE170-1 model. In a data processing apparatus having a target spectral data acquisition unit, primary color spectral data setting unit, color matching spectral data calculation unit, color matching function acquisition unit, color variation calculation unit, and selection unit, spectral data for a plurality of primary colors used in the device. A data processing method for determining characteristics,
The target spectral data acquisition means acquires target spectral data indicating spectral characteristics of the target color,
The primary color spectral data setting means sets primary color spectral data indicating spectral characteristics of each of the plurality of primary colors;
The color matching spectral data calculating means calculates color matching spectral data having the same color as the target spectral data from the primary color spectral data,
The color matching function acquisition means acquires a plurality of color matching functions,
The color variation calculating means calculates a variation evaluation value indicating a variation in color appearance based on the plurality of color matching functions between the target spectral data and the color matching spectral data;
The selection unit selects the smallest variation evaluation value among the plurality of primary color spectral data set by the primary color spectral data setting unit;
A data processing method, wherein the selected primary color spectral data is determined as optimal spectral characteristics of the plurality of primary colors used in the device.   9. A program for causing a computer device to function as the data processing device according to claim 1 when executed on the computer device.

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