JP2011215509A - Method for creating color conversion profile for multi-primary color display, and multi-primary color projector using the same - Google Patents

Abstract

A color conversion profile for multi-primary color display and a multi-primary color display device capable of smoother color reproduction than before are provided.
In a profile creation method, each sample multi-primary color data is converted into a spectral intensity of a virtual sample color patch using a spectral projection model converter. In addition, an evaluation index including a color difference index of a previously specified type representing a color difference related to the sample color of each sample multi-primary color data is calculated. The plurality of sample multi-primary color data is classified into a plurality of sets according to the sample color, and the best sample multi-primary color data is selected in each of the plurality of sets based on the evaluation index. Then, a color conversion profile is created based on the plurality of selected best sample multi-primary color data. As the color difference index, an index indicating the color difference when the color patch projected on the screen is observed at different angles is used.
[Selection] Figure 4

Description

  The present invention relates to a color conversion profile for multi-primary color display, and a color image display device such as a multi-primary projector using the color conversion profile.

  Ordinary color image display devices usually perform color display using RGB three primary colors (additive mixed three primary colors). However, in recent years, in order to display a clear color image using a wider color reproduction range (color gamut), color display is performed using four or more primary colors including other primary colors such as cyan and magenta in addition to RGB. A multi-primary color display device has been proposed (Patent Document 1). In a multi-primary color display device, there are many combinations of primary color values that represent an arbitrary color. Therefore, as a color conversion profile, a profile indicating a combination of primary color values for reproducing individual colors is prepared in advance and mounted on a multi-primary color display device.

JP 2000-338950 A

  Patent Document 1 discloses a method of dividing a color reproduction range into a plurality of pyramid regions and calculating output values of four primary colors corresponding to input tristimulus values in each pyramid region. In this method, the region to which the display color corresponding to the input tristimulus value belongs is obtained by performing a condition determination on the input tristimulus value. However, with this method, a sense of incongruity may occur between display colors that are particularly near the boundary of the pyramid region. Therefore, conventionally, a color conversion profile for multi-primary color display capable of smoother color reproduction has been desired.

  Further, a projector that projects and displays an image may project an image on various screens. Therefore, it is preferable to create a color conversion profile in consideration of the screen characteristics for a multi-primary projector that performs color images using four or more types of color light. However, conventionally, in the color conversion profile for a multi-primary projector, the screen characteristics are hardly taken into consideration. Also, the color appearance varies considerably depending on the viewing conditions of the screen. However, conventionally, the screen observation conditions have not been sufficiently considered.

  Further, in general, color unevenness often becomes a problem in a color image display device. However, conventionally, when creating a color conversion profile, the actual situation is that no consideration has been given to the reduction of color unevenness. In addition, the smoothness of gradation reproduction and the granularity have not been so much considered.

  The various problems as described above are not limited to projectors, but are common to multi-primary color display devices that display a color image using four or more primary colors.

  SUMMARY An advantage of some aspects of the invention is to solve at least a part of the problems described above, and the invention can be implemented as the following forms or application examples.

[Application Example 1]
As a color conversion profile used in a multi-primary projector capable of projecting a color image using four or more primary colors, a correspondence relationship between multi-primary color data including primary color values of the plurality of primary colors and colorimetric values is defined. A method for creating a color conversion profile
(A) preparing a spectral projection model converter that converts the multi-primary color data into spectral intensities of color patches projected according to the multi-primary color data;
(B) preparing a plurality of sample multi-primary color data;
(C) using the spectral projection model converter, converting each sample multi-primary color data into a spectral intensity of a virtual sample color patch to be projected according to the sample multi-primary color data;
(D) for each sample multi-primary color data, calculating an evaluation index including a color difference index of a predesignated type representing a color difference related to the sample color calculated from the spectral intensity;
(E) classifying the plurality of sample multi-primary color data into a plurality of sets according to the sample color calculated for each of the plurality of sample multi-primary color data, and in each of the plurality of sets based on the evaluation index Selecting the best sample multi-primary color data;
(F) creating a color conversion profile defining a correspondence relationship between colorimetric values and multi-primary color data based on the selected plurality of best sample multi-primary color data;
With
The color difference index is an index indicating a color difference when the color patches projected on the screen are observed at different angles.
According to this method, the best sample multi-primary color data is selected based on the evaluation index including the color difference index indicating the color difference when the color patch projected on the screen is observed at different angles. It is possible to create a color conversion profile for multi-primary color display capable of smoother color reproduction than in the case where a region is divided into a plurality of pyramid regions. Further, when images on the screen are observed at different angles, it is possible to display an image with a small change in color appearance.

[Application Example 2]
A method described in Application Example 1,
The color conversion profile creation method, wherein the evaluation index includes a power consumption index indicating power consumption of the multi-primary color projector together with the color difference index.
According to this configuration, it is possible to create a color conversion profile that enables smooth color reproduction and that can reduce power consumption.

[Application Example 3]
A multi-primary projector capable of projecting a color image using four or more primary colors,
A color conversion unit that converts an input color image signal into primary color values of the plurality of primary colors with reference to a color conversion profile prepared in advance;
An image projection unit that projects an image on a screen according to primary color values of a plurality of primary colors after the color conversion;
With
The color conversion profile is a multi-primary color projector that is generated such that an evaluation index including a color difference index indicating a color difference when a color patch projected on a screen is observed at different angles is minimized.
According to this multi-primary projector, color is generated using a color conversion profile generated so that an evaluation index including a color difference index indicating a color difference between color patches projected on a plurality of different screens having different spectral characteristics is minimized. Since the conversion is performed, smoother color reproduction is possible as compared with the conventional case where the color reproduction region is divided into a plurality of pyramid regions. Further, when images on the screen are observed at different angles, it is possible to display an image with a small change in color appearance.

[Application Example 4]
An image display device capable of displaying a color image using four or more primary colors,
A color conversion unit that converts an input color image signal into primary color values of the plurality of primary colors with reference to a color conversion profile prepared in advance;
An image display unit that displays an image according to primary color values of a plurality of primary colors after the color conversion;
With
The color conversion profile is an image display device that is generated such that an evaluation index including a color difference index indicating a color difference when the color patches displayed by the image display unit are observed at different angles is minimized.
According to this image display device, color conversion is performed using the color conversion profile generated so that the evaluation index including the color difference index indicating the color difference between displayed color patches is minimized. In addition, a smoother color reproduction is possible as compared with the case where the color reproduction area is divided into a plurality of pyramid areas. In addition, when an image is observed at a different angle, an image with a small change in color appearance can be displayed.

  The present invention can be realized in various forms. For example, a color conversion profile creation method and device, a color conversion profile creation system, a multi-primary color display device in which a color conversion profile is implemented, and their The present invention can be realized in the form of a computer program for realizing the function of the method or apparatus, a recording medium on which the computer program is recorded, or the like. In this specification, “recording medium” means a substantial recording medium such as a DVD, a hard disk, or a semiconductor memory.

It is a block diagram of the color conversion system in one embodiment of the present invention. It is explanatory drawing which shows the example of 1 structure of the image projection part of a multi-primary color display apparatus. It is explanatory drawing which shows the other structural example of the image projection part of a multi-primary color display apparatus. It is a block diagram of a profile creation system. It is a flowchart which shows the preparation procedure of a color conversion profile. It is a flowchart which shows the process sequence which selects the best sample. It is a flowchart which shows the calculation procedure of the color difference index CDIAa. 4 is a graph showing an example of a measured value of spectral reflectance of the screen 1. 4 is a graph showing an example of a measured value of spectral reflectance of a screen 2. 4 is a graph showing an example of a measured value of spectral reflectance of a screen 3. It is a graph which shows the example of the measured value of the spectral reflectance of the screen. It is a graph which shows the example of the spectral reflectance at the time of seeing the screen 4 from another angle. It is a flowchart which shows the calculation procedure of the color difference index CDIb in 2nd Embodiment. It is a block diagram of the profile creation system in 3rd Embodiment. It is a flowchart which shows the preparation procedure of the profile in 3rd Embodiment. It is a flowchart which shows the process sequence which selects the best sample in 3rd Embodiment. It is a flowchart of the calculation method of color nonuniformity index UE. It is a flowchart of the calculation method of the gradation property index SI. It is a flowchart of the calculation method of the graininess index GI.

Next, embodiments of the present invention will be described in the following order.
A. Overall configuration of the color conversion system:
B. First embodiment (creation of a profile that minimizes the color difference between screens):
B-1. Example of profile creation:
B-2. An example of a spectral projection model:
B-3. Effect of spectral reflectance of screen:
C. Second Embodiment (Creation of a profile that minimizes the color difference depending on the observation angle):
D. Third Embodiment (Creation of a profile that minimizes color unevenness):
E. Variations:

A. Overall configuration of the color conversion system:
FIG. 1 is a block diagram of a color conversion system according to an embodiment of the present invention. This color conversion system includes a color conversion device 100, a multi-primary color display device 200, and a screen 300. This color conversion system is a system that projects and displays a color image on the screen 300 in accordance with an input image signal. This color conversion system is also called a “multi-primary color display system”.

  The multi-primary color display device 200 is a color image display device using N (N is an integer of 4 or more) primary color lights. The multi-primary color display device 200 corresponds to N multi-primary color display signals (R, G, B, Y, C) input from the color conversion device 100, and N types of color light (also referred to as “primary color light”). And the modulated color light is projected onto the screen. In the example of FIG. 1, a projector using light of five primary colors of R (Red), G (Green), B (Blue), Y (Yellow), and C (Cyan) is illustrated. However, various types and numbers of primary color lights used in the multi-primary color display device 200 can be employed. Note that colors other than RGB are not normally used as primary colors for additive color mixing, but in this specification, the color of light modulated for color image display is referred to as “primary color”. A specific example of the multi-primary color display device 200 will be described later.

  The color conversion device 100 is a device that converts an input image signal of a three primary color system such as an RGB signal input from an image input device such as a PC into an image signal of a multi primary color system. The color conversion apparatus 100 includes a color conversion unit 110, a color conversion profile storage unit 120, and a color conversion profile selection unit 130. The color conversion unit 110 is a module that converts the three primary color data R, G, and B into multi-primary color data R, G, B, Y, and C with reference to the profile selected by the color conversion profile selection unit 130. The color conversion device 100 may be provided inside the multi-primary color display device 200.

  In the color conversion profile storage unit 120, a plurality of types of color conversion profiles PF1, PF2, PF3. The first profile PF1 is a profile that minimizes the color difference between different screens. The second profile PF2 is a profile that minimizes a color difference due to a difference in observation angle when the same screen is used. The third profile PF3 is a profile that minimizes color unevenness. As will be described later, each profile is created using a different evaluation index. Various other color conversion profiles can be used.

  Each profile is a profile for converting RGB data (for example, sRGB data) into RGBYC primary color values. Each profile expresses and associates colors with the sRGB and RGBYC color systems. It is a table that describes this correspondence relationship for a plurality of colors selected in advance over the entire reproduction range. The color conversion unit 110 can convert an arbitrary color expressed in the sRGB color system to a color in the RGBYC color system using an interpolation operation with reference to one profile.

  Note that the data included in each profile has values corresponding to input grid points obtained by finely dividing the color gamut, and the number of grid point divisions is set to an arbitrary number, such as 9x9x9, 17x17x17, or 33x33x33. Is possible.

  The color conversion profile selection unit 130 selects and acquires an appropriate profile from a plurality of profiles PF1, PF2, PF3... Stored in advance in the color conversion profile storage unit 120. That is, since the profile data PF1, PF2, PF3, ... are created using different evaluation indices, the multi-primary color display data obtained by each profile is different from each other, and preferable images and display conditions are suitable for color conversion. Different. Therefore, the color conversion profile selection unit 130 selects an appropriate profile, and the color conversion unit 110 refers to the selected profile, so that a color that appropriately corresponds to the image to be displayed, the viewing conditions, the user's intention, and the like. Conversion can be performed.

  The color conversion profile selection unit 130 only needs to be able to select an appropriate profile. As an embodiment, a configuration in which a user selects one profile in advance can be employed. For example, a selection screen (not shown) for profile selection is displayed on the OSD setting screen (on-screen menu display screen) of the projector, and selection is performed by accepting a user input operation using a switch provided in the projector. The color conversion profile selection unit 130 can recognize the profile obtained. If the color conversion profile selection unit 130 selects this profile, it is possible to perform color conversion that accurately corresponds to the user's intention.

  When the first profile PF1 is selected, the color conversion unit 110 performs color conversion so that colors when the same image is observed on different screens substantially match. In addition, when the second profile PF2 is selected, the color conversion unit 110 performs color conversion so that colors when the same image is observed on the same screen at different observation angles substantially match. Further, when the third profile PF3 is selected, the color conversion unit 110 performs color conversion so that the color unevenness of the image is minimized.

  FIG. 2 is an explanatory diagram illustrating a configuration example of the image projecting unit of the multi-primary color display device 200. The multi-primary color display device 200 includes a control unit 210, two light source lamps 221, 222, dichroic mirrors 231-233, reflection mirrors 241-245, modulation elements 251-255 formed of liquid crystal panels, Dichroic prisms 261 and 262 and a projection lens 270 are provided. Actually, various optical elements (lens, color filter, polarization separation film, etc.) other than these are also provided, but are omitted here for simplification. Both the light source lamps 221 and 222 emit white parallel light. The white light emitted from the first light source lamp 221 is separated into RGB three-color light by the dichroic mirrors 231 and 232, modulated by the modulation elements 251 to 253 for each color, and then integrated by the cross dichroic prism 261. Is done. The white light emitted from the second light source lamp 222 is separated into two colors of Y and C by the dichroic mirror 233 and modulated by the modulation elements 254 to 255 for the respective colors. The second cross dichroic prism 262 integrates the two color lights Y, C and the color lights R, G, B integrated by the first cross dichroic prism 261 to obtain five color lights R, G, B. , Y, and C are generated. This combined image light is projected onto the screen 300 by the projection lens 270. The control unit 210 has a function of transmitting modulation signals to the modulation elements 251 to 255 to perform modulation, and adjusting the outputs of the light source lamps 221 and 222 as necessary. The brightness of the projected image is determined by the product of the intensity of light emitted from the light source lamp and the light transmittance of the modulation element. Therefore, for example, when it is not necessary to increase the luminance of the color lights R, G, and B, the output of the first light source lamp 221 can be reduced to reduce power consumption. Similarly, when it is not necessary to increase the luminances of the color lights Y and C, the output of the second light source lamp 222 can be reduced to reduce power consumption. As the light source lamp, only one lamp may be provided, or a different light source lamp may be provided for each color. The greater the number of light source lamps, the higher the possibility of reducing power consumption according to the color of the image.

  FIG. 3 is an explanatory diagram illustrating another configuration example of the image projection unit of the multi-primary color display device. The multi-primary color display device 200a is obtained by replacing the light source lamps 221 and 222, the dichroic mirrors 231 to 233, and the reflection mirrors 241 to 245 in the image projection unit of FIG. Actually, various optical elements (lenses, polarization separation films, etc.) other than these are also provided, but are omitted here for the sake of simplicity. The pixel light emitting elements 281 to 285 are elements that emit different color lights R, G, B, Y, and C for each pixel. The control unit 210 controls the light emission amount of each pixel by supplying display signals (control signals) of the respective colors to the individual pixel light emitting elements 281 to 285. In the multi-primary color display device 200a, when the luminance of a certain color light is small, the output of the pixel light emitting element is lowered, and accordingly, the power consumption of the entire device is lowered.

  As can be understood from FIGS. 2 and 3, an image projection unit (also referred to as an “image display unit”) having two or more light sources and an optical system that generates one or more primary color lights from each light source. Can be used. In such a multi-primary color display device, since the output of each light source can be controlled independently, the power consumption can be reduced considerably by devising a color reproduction method using multi-primary colors. However, only one light source may be provided. Further, the multi-primary color display device is not limited to a projector (projection display device), and a direct-view display device can also be used.

  Hereinafter, a method for creating various color conversion profiles that can be used in such a color conversion system will be described.

B. First embodiment (creation of a profile that minimizes the color difference between screens):
B-1. Example of profile creation:
In the first embodiment, when an image is projected and displayed on a plurality of screens having different spectral characteristics (spectral reflectance or spectral transmittance), a profile that minimizes the color difference between the screens is created.

  FIG. 4 is a block diagram of a profile creation system that creates a color conversion profile. This profile creation system includes a spectral projection model converter 500, an index selection unit 510, a power consumption index calculation unit 520, a color difference index calculation unit 530, an evaluation index calculation unit 550, a sample selection unit 560, and a profile generation unit. 570 and a gamut mapping processing unit 580.

  The spectral projection model converter 500 converts the multi-primary color data into the spectral intensity Ismp (λ) of the image light of the color patch projected according to the multi-primary color data. That is, the spectral intensity Ismp (λ) is the spectral intensity of the image light emitted from the multi-primary color display device 200. In the present specification, the term “color patch” has a broad meaning including not only a chromatic color patch but also an achromatic color patch. In this embodiment, a projector that can use five primary colors of R, G, B, Y, and C is assumed. The spectral projection model converter 500 also receives the intensity (primary color value) of these five primary colors as input. Yes. Since the spectral intensity Ismp (λ) depends on the type of the multi-primary color display device 200, the spectral projection model converter 500 is prepared in advance for each type of the multi-primary color display device. The spectral projection model will be described in detail later. Hereinafter, the “spectral projection model” is also referred to as a “forward model”.

  The index selection unit 510 has a function of supplying data and parameters necessary for creation of various indexes to the individual index calculation units 520 and 530 together with the spectral intensity Ismp (λ). The data and parameters required to create the index include, for example, spectral reflectance data for multiple screens, spectral reflectance data for each viewing angle on the same screen, and consumption of multi-primary color display devices according to the signal level of each primary color Power, weighting factors for each index, etc. are used. The power consumption index calculation unit 520 includes a Tpower calculation unit 522 for calculating a power consumption index Tpower indicating the power consumption of the multi-primary color display device 200. The color difference index calculation unit 530 includes a CDI calculation unit 532 for calculating a color difference index CDI indicating a color difference when images are projected on a plurality of screens having different characteristics.

  The index selection unit 510 can set the weight of the power consumption index Tpower and the color difference index CDI in the range of 0.0 to 1.0 according to the designation from the user, and these weights are set to the power consumption index calculation unit 520 and the color difference index. The calculation unit 530 can be supplied. Thereby, the index is calculated by each of the calculation units 520 and 530. The index selection unit 510 can employ various configurations such as receiving an instruction from a user and determining which index to use in advance.

  The evaluation index calculation unit 550 selects sample multi-primary color data satisfying high color constancy and / or low power consumption from the indexes Tpower and CDI output from the power consumption index calculation unit 520 and the color difference index calculation unit 530. Calculate the evaluation index EI. In the present specification, the term “high color constancy” means that a color difference between different screens or a color difference between different observation angles on the same screen is small.

  This evaluation index EI is calculated for each of a plurality of sample multi-primary color data input to the spectral projection model converter 500. The sample selection unit 560 selects sample multi-primary color data having a good evaluation index EI from the evaluation index EI for each of the plurality of sample multi-primary color data. The profile generation unit 570 uses the selected sample multi-primary color data and the colorimetric values (L * a * b * values) of the color patches displayed using the sample multi-primary color data, and the primary color profile 572. Create The primary color profile 572 is a look-up table showing the correspondence between the colorimetric values (L * a * b * values) and the multi-primary color data RGBYC. The “primary color profile” is also referred to as “output device profile”. In this specification, “profile” means a conversion rule for color space conversion, and has a wide meaning including various device profiles and lookup tables. .

  The gamut mapping processing unit 580 creates profile data 590 by performing gamut mapping using the primary color profile 572 and the sRGB profile 582 prepared in advance. In the first embodiment, the profile data 590 is data of the first profile PF1 in FIG. Here, as the sRGB profile 582, for example, a profile for converting the sRGB color space into the L * a * b * color space can be used. The “sRGB profile” is also called “input device profile”.

  FIG. 5 is a flowchart showing a procedure for creating a color conversion profile by the profile creation system. In step S100, a spectral projection model is determined and a spectral projection model converter 500 is created. In one embodiment, a linear model is used as a spectroscopic projection model that weights and combines the maximum output of each primary color. Details thereof will be described later.

In the next step S110, a large number of virtual samples are set. Here, the “virtual sample” means temporary multi-primary color data used in the profile creation process and a virtual color patch displayed in accordance with the multi-primary color data. Hereinafter, the virtual sample is also simply referred to as “sample”. In one embodiment, for each primary color of RGBYC, 11 primary color values are set every 10% in the range of 0 to 100%, and all combinations of the five primary color values are set as virtual samples (sample multi-primary color display data). ) Prepare as. In this way, 11 ⁵ = 161,051 virtual samples are prepared. Note that a color having a “primary color value of 100%” means a color when the output of one primary color is maximized.

  In the next step S120, the spectral projection model converter 500 is used to convert the multi-primary color data of each virtual sample into the spectral intensity Ismp (λ) of the multi-primary color display device 200 (also referred to as “spectral emission intensity Ismp (λ)”). Convert. The index selection unit 510 acquires the spectral intensity Ismp (λ), and the CIELAB table when the light having the spectral intensity Ismp (λ) is projected onto an ideal white plate having reflectances of all wavelengths of 1.0. The colorimetric value L * a * b * of the color system is calculated. This colorimetric value L * a * b * can be calculated, for example, under the observation conditions of the CIE 1932-observer. The correspondence between the colorimetric value L * a * b * of each sample and the sample multi-primary color data RGBYC is temporarily stored in a memory (not shown).

  In the next step S130, the entire color space of the colorimetric values L * a * b * (here, CIELAB space) is divided into a plurality of cells, and a plurality of sample colors prepared in advance are sorted (classified) with respect to the cells. For example, the CIELAB space may be equally divided into 16 × 16 × 16 cells.

ここで、CDIaは色差指数であり、Tpowerは電力消費指数である。k₁とk₂はCDIaとTpowerに乗じられる重み付け係数であり、それぞれの指数が評価指数ＥＩ₁に寄与する度合を調整する。なお、典型的な例では、係数k₁は0以外の数（例えば1.0)であり、係数k₂は0を含む任意の数（例えば、0又は0.5）に設定される。すなわち、色差指数CDIaは必ず評価指数EI₁に含まれるが、消費電力指数Tpowerは任意の好ましい重みで評価指数EI₁に含め得る。なお、係数k₁，k₂の値は、任意に変更しても良い。これらの係数k₁，k₂は、主観評価により、試行錯誤的に決めることが可能である。 With the above processing, preparation of data necessary for calculating the evaluation index EI is completed. In the next step S140, the evaluation index EI used for selecting a preferred sample is set. The evaluation index EI ₁ used in the first embodiment is assumed to be expressed by the following equation (1-1).

Here, CDIa is a color difference index and Tpower is a power consumption index. k ₁ and k ₂ are weighting coefficients multiplied by CDDIa and Tpower, and adjust the degree of contribution of each index to the evaluation index EI ₁ . In a typical example, the coefficient k ₁ is a number other than 0 (eg, 1.0), and the coefficient k ₂ is set to an arbitrary number including 0 (eg, 0 or 0.5). That is, the color difference index CDIa always included in the evaluation index EI _1, the power consumption index Tpower may include the evaluation index EI ₁ in any desired weight. Note that the values of the coefficients k ₁ and k ₂ may be arbitrarily changed. These coefficients k ₁ and k ₂ can be determined by trial and error by subjective evaluation.

In step S150, the evaluation index calculation unit 550 calculates an evaluation index EI ₁ for each sample, and the sample selection unit 560 selects the best sample in each cell in the CIELAB color space according to the evaluation index EI ₁ .

FIG. 6 is a flowchart showing the detailed procedure of step S150. In the first step S151, one sample in a certain cell is selected. In the next step S152, a color difference index CDia is calculated. When the weight k ₂ of the power consumption index Tpower in the next step S153 is not 0 determined by calculating the power index Tpower in step S154, when the weight k ₂ is determined to be zero, the next step S155 move on. In step S155, the evaluation index EI ₁ is calculated according to the above equation (1-1), and this process is continued until the evaluation index EI ₁ is calculated for all the samples in the cell. When the calculation of the indices for all the samples in the cell is completed, in the next step S157, the sample with the best evaluation index EI ₁ is selected, and the process is terminated. Note that the processing of FIG. 6 is executed for all cells in the CIELAB space.

  FIG. 7 is a flowchart showing a calculation procedure of the color difference index CDDIa in step S152 of FIG. This process is performed by the CDI calculation unit 532 (FIG. 4). In this process, the index selection unit 510 passes the spectral intensity Ismp (λ) supplied from the spectral projection model converter 500 to the CDI calculation unit 532. In the first step S200, the value 1 indicating the first screen A is assigned to the parameter i indicating the screen number.

ここで、i番目のスクリーンの分光反射特性Rscr（i,λ）は既知である。 In the next step S210, the CDI calculation unit 532 multiplies the spectral intensity Ismp (λ) of the projected color patch by the spectral reflection characteristic Rscr (1, λ) of the screen A, so that the spectral intensity Osmp incident on the vision is obtained. Calculate (1, λ).

Here, the spectral reflection characteristic Rscr (i, λ) of the i-th screen is known.

  In the next step S220, tristimulus values XYZ are calculated from the spectral intensity Osmp (1, λ). For example, the tristimulus values XYZ can be calculated under the CIE19332-observer observation conditions when projected onto the screen A having a certain spectral reflection characteristic Rscr (1, λ). In this specification, “observation condition” means a combination of a screen and an observer, but CIE1931 2-observer is used as an observer unless otherwise specified.

  In the next step S230, chromatic adaptation conversion is applied to the tristimulus values XYZ to calculate the corresponding color under the standard viewing conditions. For example, standard light D65 can be used as a light source for standard viewing conditions, and CIECAT02 can be used as chromatic adaptation conversion. For CIECAT02, for example, “The CIECAM02 Color Appearance Model”, Nathan Moroney et al., IS & T / SID Tenth Color Imaging Conference, pp. 23-27, and “The performance of CIECAM02”, Changjun Li et al., IS & T / SID Tenth Color Imaging Conference, pp. 28-31. However, as the chromatic adaptation conversion, any other chromatic adaptation conversion such as a von Kries chromatic adaptation prediction formula may be used. Further, the chromatic adaptation conversion may be omitted, but if the chromatic adaptation conversion is performed, the difference in color appearance can be evaluated more correctly.

  In the next step S240, a colorimetric value L * a * b * of the CIELAB color system of the corresponding color is calculated. In step S250, the parameter i is incremented by 1. In step S260, it is determined whether the parameter i has exceeded the screen number Nscr. The screen number Nscr is the number of screens to be evaluated, and is an arbitrary integer of 2 or more. If the parameter i does not exceed the screen number Nscr, the process returns to step S210, and the processes of steps S210 to S250 are repeated. After obtaining the colorimetric values L * a * b * of the CIELAB color system for all screens in this way, the process proceeds to the last step S270.

ここで、Nscrは評価対象とするスクリーンの数、L*(i)はi番目のスクリーンでのL*値、a*(i)はi番目のスクリーンでのa*値、b*(i)はi番目のスクリーンでのb*値である。(1-3)式の分母は、Nscr個の要素から２つの要素をとる組み合わせの数である。 In the final step S270, a color difference index CDia is calculated from a plurality of sets of colorimetric values L * a * b * obtained as described above. The color difference index CDIa is expressed by the following equation, for example. This formula finds the average of the color differences for all screen pairs obtained by selecting two of all screens.

Where Nscr is the number of screens to be evaluated, L * (i) is the L * value on the i-th screen, a * (i) is the a * value on the i-th screen, b * (i) Is the b * value on the i-th screen. The denominator of equation (1-3) is the number of combinations that take two elements from Nscr elements.

  It should be noted that other formulas can be used as the color difference formula used to calculate the color difference index CDDIa. The color difference index CDIa is defined as a difference in color appearance when a certain color patch is projected onto a plurality of different screens and observed. Therefore, a sample having a small color difference index CDDIa is preferable in that the difference in color appearance when projected onto different screens is small.

  After calculating the color difference index CDDIa as described above, in step S154 of FIG. 6, a process for calculating the power consumption index Tpower is executed by the Tpower calculator 522. The Tpower calculation unit 522 receives the sample multi-primary color data RGBYC as an input, and calculates the power consumed by the multi-primary color display device 200 when a color patch represented by the multi-primary color data RGBYC is displayed by simulation. The power consumption index Tpower is obtained, for example, by measuring the power consumption when displaying color patches according to a plurality of sets of multi-primary color data, and linearly interpolating the power consumption corresponding to each multi-primary color data. .

(1-4)式の右辺第１項と第２項は２つの光源ランプ２２１、２２２の消費電力をそれぞれ示している。係数a₁, a₂は、原色値とランプ消費電力との換算係数である。 The power consumption and the adjustable range of the multi-primary color display device 200 depend on the type of the multi-primary color display device 200. For example, as shown in FIG. 2, when a multi-primary color display device 200 having two light source lamps 221 and 222 is used, the output (luminance) required for each light source lamp 221 and 222 is reproduced. It depends on the color to be used. Therefore, an index indicating the total power consumption of the two light source lamps 221 and 222 can be used as the power consumption index Tpower. For example, the power consumption index Tpower relating to the multi-primary color display device 200 of FIG. 2 can be expressed by the following equation.

The first and second terms on the right side of equation (1-4) indicate the power consumption of the two light source lamps 221 and 222, respectively. The coefficients a ₁ and a ₂ are conversion coefficients between primary color values and lamp power consumption.

The power consumption index Tpower indicates the power consumption when only one color patch is displayed on the screen. Therefore, even if a color image composed of a large number of colors is displayed in a color with a small power consumption index Tpower, it is not guaranteed that the power consumption of the entire screen will be reduced. However, normally, if a color image is displayed with a color with a small power consumption index Tpower, it is estimated that the power consumption is sufficiently low on the entire screen. In this sense, it is sufficiently meaningful to use an index that includes the power consumption index Tpower as the evaluation index EI ₁ when selecting a color patch.

(1-5)式の右辺第１項〜第５項は５つの画素発光素子２８１〜２８５の消費電力をそれぞれ示している。係数a₁〜a₅は、原色値とランプ消費電力との換算係数である。 Further, as shown in FIG. 3, even when using a multi-primary color display device 200a having pixel light-emitting elements 281 to 285 provided for each primary color, the output required for each pixel light-emitting element 281 to 285 is used. (Luminance) varies depending on the color to be reproduced. Therefore, an index indicating the total power consumption of the plurality of pixel light emitting elements 281 to 285 can be used as the power consumption index Tpower. Such a power consumption index Tpower can be calculated by the following equation, for example.

The first to fifth terms on the right side of equation (1-5) indicate the power consumption of the five pixel light emitting elements 281 to 285, respectively. Coefficients a _{1 to} a ₅ are conversion coefficients between primary color values and lamp power consumption.

  Unlike the device of FIG. 2, the multi-primary color display device 200a emits light separately for each pixel. Therefore, using only color reproduction with a small power consumption index Tpower guarantees that the power consumption of the entire screen is reduced. Is done.

The power consumption index Tpower related to the multi-primary color display device having only one light source can be calculated using, for example, the following equation.

  Even in such a multi-primary color display device having only one light source, if the entire screen is displayed with a color with a small power consumption index Tpower, it can be expected that the power consumption is reduced.

Since the color difference index CDDIa and the power consumption index Tpower as the constituent elements of the evaluation index EI ₁ are calculated by the processing in steps S151 to S154 in FIG. 6, in the next step S155 in FIG. The evaluation index EI ₁ is calculated by the equation -1). In the next step S156, it is determined whether or not the calculation of the evaluation index EI ₁ has been completed for all sample colors included in the cell to be processed. In this way, each step is repeatedly executed, and the evaluation index EI ₁ is calculated for all the sample colors in the cell. In the next step S157, the sample selection unit 560 selects a sample having the best evaluation index EI _{1 from} among a plurality of sample colors in the cell as a representative sample for the cell. As a result, one representative sample is selected for each cell containing at least one sample. Hereinafter, the representative sample is also referred to as “highly evaluated sample” or “best sample”.

  In the final step S160 of FIG. 5, the gamut mapping processing unit 580 (FIG. 4) performs gamut mapping based on the primary color profile 572 and the sRGB profile 582, and creates profile data 590. The reason for performing gamut mapping is that there is a difference between a color gamut that can be reproduced by the multi-primary color display device 200 and a color gamut that can be expressed in an input color space (in this embodiment, an sRGB space). The color gamut of the primary color space is defined by the primary color profile 572, and the color gamut of the input color space is defined by the sRGB profile 582. Generally, since there is a discrepancy between the input color space and the primary color space, it is preferable to map the color gamut of the input color space to the color gamut of the primary color space.

When gamut mapping is performed in this way, final profile data 590 is completed. If the profile data 590 is mounted on the multi-primary color display device 200, color constancy is high (that is, the change in color appearance is small even when projected onto different screens), and high-quality display is possible. Further, using the profile data generated using the weight without the weight k ₂ 0 power consumption index tPOWER, it is possible to realize a low power consumption.

ここで、I_R(λ), I_G(λ), I_B(λ), I_Ye(λ), I_C(λ)はそれぞれ各原色の入力レベル、BK(λ)は全原色の入力レベルを0にしたときの分光強度（バックグラウンド強度）、Rmax(λ), Gmax(λ), Gmax(λ), Yemax(λ), Cmax(λ)はそれぞれ、各原色の最大出力の分光強度，γは画像投影部のγ値である。なお、上記(1-8a)〜(1-8e)式は、各色の強度I_R(λ), I_G(λ), I_B(λ), I_Ye(λ), I_C(λ)からバックグラウンド強度BK(λ)を減算した値がγ特性を示すことを表している。 B-2. An example of a spectral projection model:
Hereinafter, an example of a spectral projection model will be described. The spectral intensity Ismp (λ) of the light projected on the screen by the projector is obtained according to the following equation.

Where I _R (λ), I _G (λ), I _B (λ), I _Ye (λ), and I _C (λ) are the input levels for each primary color, and BK (λ) is the input level for all primary colors. Is the spectral intensity (background intensity) when R is 0, Rmax (λ), Gmax (λ), Gmax (λ), Yemax (λ), Cmax (λ) γ is a γ value of the image projection unit. The above formulas (1-8a) to (1-8e) are calculated from the intensities I _R (λ), I _G (λ), I _B (λ), I _Ye (λ), and I _C (λ) of each color. A value obtained by subtracting the background intensity BK (λ) represents a γ characteristic.

  Note that the spectral intensities Rmax (λ), Gmax (λ), Gmax (λ), Yemax (λ), Cmax (λ), and BK (λ) used here are the images actually projected on the screen from the projector. This is a characteristic obtained by measuring the spectral intensity and dividing the measured value by the spectral reflectance (known) of the screen. That is, when these spectral intensities Rmax (λ), Gmax (λ), Gmax (λ), Yemax (λ), Cmax (λ), BK (λ) are projected onto a screen having a spectral reflectance of 1.0, This is the observed light intensity. Since each spectral intensity is affected by the spectral characteristics of the optical elements of the projector (light source, lens, dichroic mirror, color filter, liquid crystal panel, etc.), this model is applied to projectors of different types. In such a case, it is preferable to re-measure the spectral intensity. Even in the same type of projector, the characteristics are actually slightly different. Therefore, it is preferable to prepare a plurality of projectors of the same type, measure their spectral intensities, and take their average values.

B-3. Effect of spectral reflectance of screen:
8 to 11 are graphs showing examples of measured values of the spectral reflectance of an existing screen. These measurement values are measurement examples when light is projected and displayed substantially perpendicularly to the screens 1 to 4 and observed from a direction inclined by a predetermined angle (for example, 30 degrees) from the normal line of the screen.

Table 1 below is an example of calculating the color difference index CDDIa when three types of color patches having different colors are respectively projected on these screens.

  From Table 1, it can be understood that there are a plurality of samples having a combination of different primary color values having substantially the same (L *, a *, b *) values, and the color difference index CDDIa is different for each sample. Therefore, it can be seen that by selecting a sample (combination of primary color values) having the smallest color difference index CDDIa, it is possible to display an image with a small change in color appearance on a plurality of screens. Table 1 shows the result of evaluating only a part of the total combination of primary color values, and if all the samples are evaluated, the difference in the value of the color difference index CDDIa may be further widened.

As described above, in the first embodiment, as the evaluation index EI ₁ in selecting a sample including at least color difference index CDIA, also using the evaluation index EI ₁ including power consumption index Tpower desired. Therefore, it is possible to easily create a color conversion profile in consideration of these various indexes and their weights. In other words, it is possible to easily create a color conversion profile that achieves color reproduction with little change in color appearance even when projected on different screens, and at the same time achieves this color reproduction, displays with low power consumption. Possible color conversion profiles can be created. Furthermore, in this embodiment, unlike the prior art, the color reproduction area is not divided into a plurality of pyramid areas, so it is possible to create a color conversion profile that enables smoother color reproduction than in the prior art. It is.

C. Second Embodiment (Creation of a profile that minimizes the color difference depending on the observation angle):
In the second embodiment, the screen is fixed to one type, and even if the viewer is sitting at a different position, that is, when viewing the screen from different angles, the color difference is minimized. Create a conversion profile.

  FIG. 12 is a graph showing an example of the spectral reflectance when the screen 4 shown in FIG. 11 is viewed from different angles. FIG. 12 shows an example in which light is projected and displayed substantially perpendicular to the screen 4 and observed at an angle substantially close to the normal line of the screen. From the comparison between FIG. 11 and FIG. 12, it can be understood that the spectral reflectance varies depending on the observation angle, and the color appearance also varies when the image is observed from different positions. Therefore, by creating a color conversion profile that outputs a combination of primary color values that minimizes the difference in color appearance, it is possible to perform display with little color change from any direction. The second embodiment is different from the first embodiment in the flow for obtaining the color difference index CDI, and the apparatus configuration is the same as that in the first embodiment.

  FIG. 13 is a flowchart illustrating a procedure for calculating a color difference index according to the second embodiment. The processing in FIG. 13 is a modification of steps S210 and S260 in FIG. 7, and the other steps are the same as in FIG. The parameter i in step S200 is a parameter indicating the number of observation angles of the screen, and the angle number Nangle in step S260a is a parameter indicating the number of different observation angles.

  In step S210a, the spectral reflection characteristic Rscr (i, λ) of the screen A when the screen is observed from the i-th angle is multiplied by the spectral intensity Ismp (λ) of the sample, and the spectral intensity Osmp incident on the vision is obtained. Calculate (1, λ). The processing after step S220 is almost the same as the processing after step S220 in FIG.

ここで、Nangleは評価対象とする観察角度の数、L*(i)はi番目の角度から見た場合のL*値、a*(i)はi番目の角度から見た場合のa*値、b*(i)はi番目の角度から見た場合のb*値である。なお、色差指数CDIbの算出に使用する色差式としては、他の式を用いることも可能である。 In the final step S270 of FIG. 13, the color difference index CDIb is calculated. The color difference index CDIb is expressed by the following formula, for example. In this equation, the average of the color differences for all angle pairs is obtained.

Here, Nangle is the number of observation angles to be evaluated, L * (i) is the L * value when viewed from the i-th angle, and a * (i) is a * when viewed from the i-th angle The value b * (i) is the b * value when viewed from the i-th angle. As the color difference formula used for calculating the color difference index CDIb, another formula can be used.

  This color difference index CDIb is defined as the difference in color appearance when the same color patch displayed on the same screen is observed from a plurality of different angles. Therefore, a sample having a small color difference index CDIb is preferable in that the difference in color appearance when observed from different angles is small.

In the second embodiment, as an evaluation index used when the sample selection unit 560 selects a high evaluation sample, an evaluation index EI given by the following equation (2-2) similar to the above equation (1-1) ₂ can be used.

  According to the second embodiment described above, a color conversion profile with a small difference in color appearance can be created even when observed from different angles. If this color conversion profile data is installed in a projector, high-quality display with high color constancy when observed from different angles is possible. Further, if a value other than 0 is used as the weight k2 in the equation (2-2), it is possible to create a profile that has a small color difference depending on the viewing angle and can be displayed with low power consumption.

ここで、L*, a*, b*は評価対象サンプルに対して算出された測色値であり、L*_Target, a*_Target, b*_Targetは、各サンプルがターゲットとする測色値である。 As the color difference index CDI, those other than the above-described two kinds of color difference indices CDIa and CDIb can be used. For example, if the color difference index CDI is calculated according to the following equation (2-3), it is possible to create a color conversion profile capable of displaying a color faithful to the target color on a specific screen.

Here, L *, a *, b * are colorimetric values calculated for the sample to be evaluated, and L * _Target , a * _Target , b * _Target are the colorimetric values targeted by each sample. is there.

  As described above, the color difference index CDI is a color difference index representing the color difference relating to the sample color calculated from the spectral intensity Ismp (λ) of the sample, and a color difference index of a predetermined type can be used. .

D. Third Embodiment (Creation of a profile that minimizes color unevenness):
In the third embodiment, a color conversion profile that minimizes the color unevenness of the displayed color patch is created.

  FIG. 14 is a block diagram of a profile creation system in the third embodiment. This profile creation system has a configuration in which an image quality index calculation unit 540 is added to the system of FIG. 4, and other configurations are the same as the system of FIG.

  The image quality index calculation unit 540 includes a UE calculation unit 542 that calculates a color unevenness index UE that indicates the degree of color unevenness on the screen as the image quality index of each displayed patch, and a gradation property index SI that indicates the smoothness of gradation. SI calculation unit 546 for calculating the granularity, and GI calculation unit 544 for calculating the granularity index GI indicating the granularity. Further, the power consumption index calculation unit 520 and the color difference index calculation unit 530 can calculate the same index as that described in the first embodiment or the second embodiment.

  The index selection unit 510 passes data and parameters necessary for calculating the index in each index calculation unit 520 to 540 to each index calculation unit 520 to 540. In addition, the index selection unit 510 controls the index calculation units 520 to 540 so that the weights of the image quality indexes UE, GI, SI, the power consumption index Tpower, and the color difference index CDI change between 0.0 and 1.0.

  FIG. 15 is a flowchart showing a procedure for creating a color conversion profile in the third embodiment. This procedure is obtained by changing the contents of steps S140 and S150 in FIG. 5, and other steps are the same as those in FIG.

ここで、CDIは第１又は第２実施形態で説明した色差指数であり、Tpowerは電力消費指数、UEは色むら指数、SIは階調性指数、GIは粒状性指数である。k₁〜k₅は各指数の重み付け係数であり、それぞれの指数が評価指数EI₃に寄与する度合を示す。なお、第３実施形態では、色差指数CDIの係数k₁と色むら指数UEの係数k₃は０以外の数であり、他の係数k₂, k₄, k₅は０を含む任意の数に設定可能である。これらの係数は、主観評価により、試行錯誤的に決められる値である。 In step S140a, an evaluation index EI ₃ used for selecting a preferred sample is set. This evaluation index EI ₃ is expressed by the following formula, for example.

Here, CDI is the color difference index described in the first or second embodiment, Tpower is the power consumption index, UE is the color unevenness index, SI is the gradation index, and GI is the graininess index. k _{1 to} k ₅ are weighting coefficients for each index, and indicate the degree to which each index contributes to the evaluation index EI ₃ . In the third embodiment, the coefficient k ₁ and the coefficient k ₃ mottling index UE chrominance index CDI is a number other than 0, the other coefficients k _2, k _4, k ₅ is any number including 0 Can be set. These coefficients are values determined by trial and error by subjective evaluation.

In step S150a of FIG. 15, the evaluation index calculation unit 550 calculates an evaluation index EI ₃ for each sample, and the sample selection unit 560 selects the best sample in each cell in the CIELAB color space according to the evaluation index EI _3. select.

FIG. 16 is a flowchart showing the detailed procedure of step S150a. The processing procedure of FIG. 16 is obtained by adding steps S301 to S306 between step S154 and step S155 of FIG. 6, and the other steps are the same as those of FIG. In steps S301 to S306, when the color unevenness index UE, the gradation index SI, and the weighting coefficients k ₃ , k ₄ , and k _{5 of} the graininess index GI are not 0, the respective indices are calculated. As described above, in the third embodiment, the weighting factor k ₃ color unevenness index UE is set to a value other than 0, at least uneven color index UE preferably be calculated. However, five indices CDI of the equation (3-1), tPOWER, UE, SI, coefficient k ₁ to k ₅ of the GI may be set to at least one value other than 0, the other coefficients 0 May be set.

  FIG. 17 is a flowchart of a method for calculating the color unevenness index UE. In step S410, the color patch is displayed on the entire screen of the modulation element according to the sample multi-primary color data, and in step S420, RGB data is measured at a plurality of measurement positions in the screen. In step S430, the RGB data is converted into tristimulus values XYZ, and in step S440, an average value of these tristimulus values XYZ is calculated. In step S450, the average value of the tristimulus values XYZ is converted into a colorimetric value (L * a * b * value), thereby obtaining an average colorimetric value over the entire color patch. In step S460, L * a * b * values are calculated for each measurement position in the same manner as in steps S430 to S450.

ここで、Npixはサンプルカラーパッチ上の測定位置の数、L*(i)はi番目の測定位置のL*値、a*(i)はi番目の測定位置のa*値、b*(i)はi番目の測定位置のb*値である。この色むら指数UEは、各測定位置における測色値と、その平均値との間のユークリッド距離の平均値に相当する。なお、色むら指数UEの算出には、他の式を用いることも可能である。 In step S470, the color unevenness index UE is calculated according to the following equation using the L * a * b * value at each measurement position and the L * a * b * average value of the entire color patch.

Where Npix is the number of measurement positions on the sample color patch, L * (i) is the L * value of the i-th measurement position, a * (i) is the a * value of the i-th measurement position, b * ( i) is the b * value at the i-th measurement position. The color unevenness index UE corresponds to the average value of the Euclidean distance between the colorimetric value at each measurement position and the average value. It should be noted that other equations can be used to calculate the color unevenness index UE.

  In the above equation (3-2), the Euclidean distance of the three components L *, a *, and b * is obtained. Instead, only the a * and b * components are considered without considering the L * component. A considered Euclidean distance may be used. Further, the above equation (3-2) may be configured to multiply the correction term corresponding to the luminance of the patch.

  The color unevenness in the multi-primary color display device 200 is considered to occur due to manufacturing errors of various optical components such as a modulation element (liquid crystal light valve), a lens, a color filter, and a pixel light emitting element. For example, in an optical component having a thin film, even if the dimensional error is the same, the thinner the design film thickness, the larger the luminance unevenness across the screen due to the error. Accordingly, among the four or more primary color lights, there may be a primary color light having a relatively large luminance unevenness and a relatively small primary color light. In such a case, among various color reproduction methods using multi-primary colors, a color reproduction method that uses more primary color light with a large luminance unevenness tends to have large color unevenness. Conversely, if a color reproduction method that uses a larger amount of primary color light with less luminance unevenness is used, color unevenness can be reduced. In order to reflect such specific characteristics, in step S410, a plurality of multi-primary color display devices 200 are sequentially used to display the same color patch, and a plurality of measurements in the displayed color patch are displayed. It is preferable to measure the color at each location. In this way, it is possible to obtain a color unevenness index UE indicating the degree of color unevenness that occurs when a color patch is displayed on the entire screen of the modulation element using the multi-primary color display device 200.

FIG. 18 is a flowchart of a method for calculating the gradation index SI. In the first step S510, the evaluation index calculation unit 550 calculates an evaluation index EI ₃ 'given by the sum of each term other than the fourth term (k ₄ · SI) on the right side of the above equation (3-1), and selects the sample. The unit 560 selects one sample having the smallest evaluation index EI ₃ ′ for each cell, and uses this as a representative sample set. Instead, in each cell, select a plurality of samples (for example, 10 samples) having the smallest evaluation index EI ₃ ′, and adopt the color represented by the average value of those samples as the representative sample of that cell. Also good. When the evaluation index EI ₃ includes the graininess index GI, the gradation index SI may be calculated after the graininess index GI is calculated. In step S520, smoothing processing on the representative sample of each cell is performed using these representative sample sets. That is, here, the blurring process is performed by a three-dimensional Gaussian function in the CIELAB space. The Gaussian function gives a weight to a representative sample (target sample) of one cell in the CIELAB space and a representative sample of another cell close thereto. Then, a value obtained by multiplying the primary color data of the target sample and the representative sample by the weight is added, and normalization is performed with the total of the weights, and smoothed sample multi-primary color data for the target sample is obtained. Note that simple averaging may be used as the smoothing process. In the next step S530, rescaling processing is performed to prevent the primary color value from dropping to 0 outside the color reproduction range. That is, each primary color data is divided by the maximum value of the primary color data of each color and multiplied by the maximum value of the dynamic range of the primary color data. As a result, the maximum value of each primary color data is normalized to the maximum value (for example, 255) of the dynamic range. This rescaling process is performed in order to prevent the primary color values in the gamut from being reduced in the repetition of the smoothing process, but may be omitted.

ここで、Aprimeは、ぼかし前の原色値であり、Aprime,blurは、ぼかし後の原色値、Primeは原色の種類を示すパラメーターである。 In the next step S540, the Euclidean distance between the color represented by the multi-primary color data before blurring of the target sample and the color represented by the multi-primary color data after blurring is calculated by the following formula, and the gradation index SI is calculated. And

Here, Aprime is a primary color value before blurring, Aprime and blur are primary color values after blurring, and Prime is a parameter indicating the type of primary color.

  This gradation index SI indicates a change in color before and after blurring, and indicates how close the color of the original sample is to the color after blurring. Here, the smaller the gradation index SI, the smaller the change in color, so the distance between the target sample color and the representative sample colors of other surrounding cells is more evenly spaced, and the local color It can be considered that the gradation is reproduced smoothly in the range. Therefore, the gradation index SI can be used as an index representing the smoothness of the gradation change with respect to the input.

FIG. 19 is a flowchart of a method for calculating the graininess index GI. In this process, a sample color patch is displayed, and the display result is taken to calculate the difference between the blurred image of the color patch and the original image, and this difference is used as the graininess index GI. And This graininess index GI is, MD Fairchild and GM Johnson, " Meet iCAM: and Image Color Appearance Model" IS & T / SID 10 th Color Imaging Conference, Scottsdale, (2002), or GM Johnson and MD Fairchild, "Rendering HDR Images ^{"iS * T / SID 11 th} Color Imaging Conference, see Scottsdale, the described model (2003) (iCAM).

  In step S550, first, the sample patch is displayed on the multi-primary color display device 200 using the sample multi-primary color data. In step S560, the displayed sample patch is photographed by a scanner to obtain RGB data. Here, since the granularity of the sample patch is evaluated, it is preferable to perform measurement at a resolution higher than the resolution of the modulation element or the pixel light emitting element (that is, at a finer pixel pitch). Since the RGB data is data in the device-dependent color space, in step S570, scanner characteristics conversion (scanner characterization) is performed to convert the data into data in the XYZ color space, which is a device-independent color space.

ここで、AC₁C₂は反対色チャンネル（opponent channels)であり、Aが輝度チャンネルであり、C₁C₂がクロミナンスチャンネルである。 In steps S580 to S620, a blurred image is created. First, in step S580, the XYZ color space is converted into an opposite-colors space. That is, for each channel in the opposite color space, the contrast sensitivity function (csf) in the human eye can be defined in the frequency space by experiment etc., so the conversion is performed so that this csf can be used. Do. This conversion can be calculated by the following equation, for example.

Here, AC ₁ C ₂ is an opposite channel, A is a luminance channel, and C ₁ C ₂ is a chrominance channel.

ここで、fは周波数、csf_lumは輝度コントラスト感度関数（luminance contrast sensitivity function）、csf_chromはクロミナンスコントラスト感度関数（chrominance contrast sensitivity function）である。また、係数a,b,c,a₁,a₂,b₁,b₂,c₁,c₂は予め設定される値である。 Since csf is defined in the frequency space, in step S590, Fourier transform is performed on each opposite color channel. In step S600, filtering is performed for each opposite color channel using the csf described above. That is, each component is multiplied by csf. In one embodiment, the following equation (3-5) can be used for luminance, and the following equation (3-6) can be used for chrominance channels.

Here, f is a frequency, csf _lum is a luminance contrast sensitivity function, and csf _chrom is a chrominance contrast sensitivity function. The coefficients a, b, c, a ₁ , a ₂ , b ₁ , b ₂ , c ₁ , c ₂ are values set in advance.

As described above, when filtering is performed, in step S610, the filtered function is subjected to inverse Fourier transform, and in step S620, the opposite color space is further converted to the XYZ color space. This conversion can be calculated by the following equation, for example.

  With the above processing, the XYZ value of the blurred image is calculated, and the XYZ value of the original image is calculated in step S570. Therefore, in step S630, the CIELAB value is calculated for each image. In step S640, the color difference between the blurred image and the original image is calculated by the CIEDE2000 color difference formula. This color difference corresponds to the difference between the blurred image of the color patch and the original image, and shows a larger value as the granularity of the original color patch increases. Therefore, this difference value can be used as the graininess index GI indicating the degree of graininess of the original color patch.

  In the calculation of the graininess index GI described above, the GI was calculated by photographing the actually displayed image. However, a virtual area in which a predetermined area is obtained by collecting a plurality of pixels of the color indicated by the multi-primary color data. Considering a typical sample color patch, the graininess index GI may be calculated by simulation.

  Further, the granularity index GI of the sample color patch may be obtained using the RMS granularity or the Wiener spectrum. Furthermore, the graininess index may be obtained after separating the banding component and the granular component contained in the color patch by the method described in Hirokazu Kasahara: “Banding measurement method capability ochJapan Hardcopy '04”.

With the above processing, various indexes CDI, Tpower, UE, SI, and GI that should be included in the evaluation index EI ₃ are calculated. In the next step S155 of FIG. 16, the above equation (3-1) is used. The evaluation index EI ₃ is calculated. In the next step S156, it is determined whether or not the calculation of the evaluation index EI ₃ has been completed for all sample colors included in the processing target cell. In this way, each step is repeatedly executed, and the evaluation index EI ₃ is calculated for all the sample colors in the cell. In the next step, the sample selection unit 560 selects a sample having the best evaluation index EI _{3 from} among sample colors in the cell as a representative sample for the cell. As a result, one representative sample is selected for each cell containing at least one sample.

As described above, in the third embodiment, since the evaluation index EI ₃ including the color difference index CDI and the color unevenness index EI is used, a profile that achieves smooth color reproduction and achieves image display with less color unevenness. Can be created. If the same color difference index CDIa as that of the first embodiment is used as the color difference index CDI, a profile that achieves color reproduction with a small change in color appearance when the same image is projected onto a different screen can be created. . Further, if the same color difference index CDIb as that of the second embodiment is used as the color difference index CDI, a profile that achieves color reproduction with a small change in color appearance even when the same image is observed at different angles on the same screen is created. be able to. Further, if to include power consumption index Tpower the evaluation index EI _3, can be created that can be carried out display with low power consumption profile. In addition, if the evaluation index EI ₃ includes the gradation index SI and the graininess index GI, it is possible to create profiles that achieve smoother color reproduction with local gradation reproduction and display with less granularity. It is. Which of these various desirable characteristics is to be emphasized can be adjusted using the weighting factors k _{1 to} k ₅ in the equation (3-1) relating to these characteristics.

E. Variations:
The present invention is not limited to the above-described embodiments and examples, and can be implemented in various modes without departing from the gist thereof. For example, the following modifications are possible.

・ Modification 1:
In the first embodiment and the second embodiment described above, the optimum multi-primary color data is selected using the power consumption index Tpower and the color difference index CDI, but the index included in the evaluation index EI relates to image quality and device life. An index may be included. For example, in liquid crystal elements, EL elements, laser oscillation elements, etc., the intensity (temperature) of the primary color to be displayed has an effect on the lifetime. Therefore, a life index indicating the degree of apparatus life due to the combination of primary color values may be included in the evaluation index. Note that the formulas and calculation methods for obtaining the various indices described above are examples, and the indices may be calculated using other formulas and calculation methods different from those.

Modification 2
In each of the above-described embodiments, the color space of the colorimetric value is divided into a plurality of cells, and the sample having the best evaluation index EI in each cell is selected as the representative sample. However, the method of selecting a plurality of representative samples used when creating a color conversion profile is not limited to these, and generally a plurality of representative samples can be selected based on the evaluation index EI. For example, it is possible to select a plurality of representative samples (best samples) without dividing the color space of the colorimetric values into a plurality of cells. Specifically, multiple grid points (nodes) are set in the color space of the colorimetric values, and the sample with the smallest evaluation index EI among the samples existing in a predetermined range near each node is represented by that node. Can be selected as sample (best sample). These cases are common in that the samples are classified into a plurality of groups according to the color of the sample (that is, the colorimetric value), and the best sample according to the evaluation index EI is selected for each group. I can understand that.

・ Modification 3:
In the above embodiment, a reflective screen is used, but a transmissive screen may be used instead. In this case, the spectral transmittance may be used instead of the spectral reflectance of the screen. That is, if the spectral characteristics (spectral reflectance or spectral transmittance) of the screen are used, the spectral intensity of the image observed on the screen can be calculated.

-Modification 4:
In the above-described embodiment, the case where a projector (projection display device) is used as the multi-primary color display device has been described. However, the present invention can also be applied to a direct-view display device such as a television or a monitor. In particular, for a display device whose appearance varies greatly depending on the observation angle, it is preferable to use a color conversion profile that suppresses the change in appearance due to the observation angle as described in the second embodiment.

DESCRIPTION OF SYMBOLS 100 ... Color conversion apparatus 110 ... Color conversion part 120 ... Color conversion profile storage part 130 ... Color conversion profile selection part 200 ... Multi-primary color display apparatus 210 ... Control part 221, 222 ... Light source lamp 231-233 ... Dichroic mirror 241-245 ... Reflection mirrors 251 to 255 ... modulation elements 261 and 262 ... cross dichroic prisms 270 ... projection lenses 281 to 285 ... pixel light emitting elements 300 ... screen 500 ... spectral projection model converter 510 ... index selection unit 520 ... power consumption index calculation unit 530 ... color difference Index calculation unit 540 ... Image quality index calculation unit 550 ... Evaluation index calculation unit 560 ... Sample selection unit 570 ... Profile generation unit 572 ... Primary color profile 580 ... Gamut mapping processing unit 590 ... Profile data

Claims (4)

As a color conversion profile used in a multi-primary projector capable of projecting a color image using four or more primary colors, a correspondence relationship between multi-primary color data including primary color values of the plurality of primary colors and colorimetric values is defined. A method for creating a color conversion profile
(A) preparing a spectral projection model converter that converts the multi-primary color data into spectral intensities of color patches projected according to the multi-primary color data;
(B) preparing a plurality of sample multi-primary color data;
(C) using the spectral projection model converter, converting each sample multi-primary color data into a spectral intensity of a virtual sample color patch to be projected according to the sample multi-primary color data;
(D) for each sample multi-primary color data, calculating an evaluation index including a color difference index of a predesignated type representing a color difference related to the sample color calculated from the spectral intensity;
(E) classifying the plurality of sample multi-primary color data into a plurality of sets according to the sample color calculated for each of the plurality of sample multi-primary color data, and in each of the plurality of sets based on the evaluation index Selecting the best sample multi-primary color data;
(F) creating a color conversion profile defining a correspondence relationship between colorimetric values and multi-primary color data based on the selected plurality of best sample multi-primary color data;
With
The color difference index is an index indicating a color difference when the color patches projected on the screen are observed at different angles. The method of claim 1, comprising:
The color conversion profile creation method, wherein the evaluation index includes a power consumption index indicating power consumption of the multi-primary color projector together with the color difference index. A multi-primary projector capable of projecting a color image using four or more primary colors,
A color conversion unit that converts an input color image signal into primary color values of the plurality of primary colors with reference to a color conversion profile prepared in advance;
An image projection unit that projects an image on a screen according to primary color values of a plurality of primary colors after the color conversion;
With
The color conversion profile is a multi-primary color projector that is generated such that an evaluation index including a color difference index indicating a color difference when a color patch projected on a screen is observed at different angles is minimized. An image display device capable of displaying a color image using four or more primary colors,
A color conversion unit that converts an input color image signal into primary color values of the plurality of primary colors with reference to a color conversion profile prepared in advance;
An image display unit that displays an image according to primary color values of a plurality of primary colors after the color conversion;
With
The color conversion profile is an image display device that is generated such that an evaluation index including a color difference index indicating a color difference when the color patches displayed by the image display unit are observed at different angles is minimized.

Images