JP2011095386A - Lookup table forming method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To intuitively and quantitatively evaluate a difference between an actual display color and an ideal color to easily and accurately converting a color into a reference color. <P>SOLUTION: A method of forming a lookup table includes: converting a color signal output from a color image generator 11 to a display device 12 by using a lookup table; measuring the wavelength strength distribution of light emitted from the display device by the converted color signal; calculating an XYZ value from the wavelength strength distribution to be converted into a first RGB value by using matrix data for associating the XYZ value with an RGB value; calculating a second RGB value based on the color signal from the color signal generator 11, and comparing the first RGB value with the second RGB value, to correct the lookup table. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a lookup table creation method for optimizing colors displayed on a display device and colors acquired by an imaging device.

  Conventionally, a color system such as an XYZ color system or a UCS color system defined by the International Commission on Illumination (CIE) has been used for evaluating colors displayed on a display device. The lookup table creation methods disclosed in the following Patent Document 1 and Patent Document 2 evaluate colors displayed on the display device using such a color system. Further, as a method for creating a three-dimensional lookup table used for color gamut conversion, there is a method described in Patent Document 3 below.

JP 2002-209230 A JP 2002-218261 A JP 2008-85980 A

  However, the chromaticity diagram used for conventional color evaluation is a diagram in which the color space is distorted. Further, in the conventional chromaticity diagram, the symmetry of the positions of primary colors and secondary colors is poor, and white is not located at the origin. Therefore, in the conventional chromaticity diagram, it is difficult to grasp in the color space the actual color difference with respect to the ideal color to be displayed by the display device and the ideal color to be acquired by the imaging device.

  In addition, since the display device and the imaging device become high definition and the pixels of the device approach each other, crosstalk between adjacent pixels cannot be ignored. Further, in a liquid crystal display or the like, the color filter is likely to be displaced. Due to these factors, the intermediate color is displayed with a deviation from the ideal state, but such a deviation cannot be easily observed, inspected, or evaluated.

  In addition, it is difficult to modify the three-dimensional lookup table based on the information of each grid point in the table because the number of grid points is very large, and it is easy to measure colors for individual display devices and imaging devices. It is difficult to obtain a correction value. Moreover, even if information for the number of grid points is obtained, it is necessary to interpolate correction values included in the table, and an inaccurate result may be obtained.

  Therefore, the present invention provides a look-up table creation method capable of intuitively and quantitatively evaluating a difference between an ideal color and an actual display color and easily and accurately performing conversion to a reference color. The purpose is to provide.

  In the lookup table creation method of the present invention, the color image generation step in which the color image generation means outputs the color signal to the display device, the lookup table is read from the first storage means, and the lookup table is used. A conversion step for converting a color signal sent from the color image generating means to the display device, a wavelength intensity distribution of light from the display device or a measurement step for measuring a tristimulus value based on the light, a wavelength intensity distribution or a tristimulus value First, the matrix data that associates the XYZ values or chromaticity xyz obtained from the chromaticity xyz with the RGB values is read from the second storage means, and the XYZ values obtained in the measurement step are converted into the first RGB values using the matrix data. A second step of calculating a second RGB value based on the calculation step and the color signal input from the color image generating means; Comprising the steps out, compared with the first RGB value and the second RGB value, a correction step for correcting the look-up table in the first memory means.

  According to this lookup table creation method, the RGB value (measured value) calculated based on the measurement result is compared with the RGB value (reference value) calculated based on the input signal, thereby eliminating the deviation of the measured value. Can be simple and quantitative. Further, by correcting the lookup table based on the comparison, conversion to a reference color can be performed easily and accurately.

  The lookup table creation method of the present invention calculates a first hue and saturation based on a first RGB value, and creates a first distribution map indicating the position of the first hue and saturation. A first creation step, a second creation step of calculating a second hue and saturation based on the second RGB value, and creating a second distribution map indicating the position of the second hue and saturation; An output step of outputting the first distribution chart and the second distribution chart may be further included. Here, the first distribution chart and the second distribution chart are distribution charts in which hue is a declination and saturation is a moving radius.

  In this case, the position of the hue and saturation of the color emitted by the display device is indicated by a distribution diagram in which the hue is the declination and the saturation is the radius, so the color from the display device is red, green, blue. It is possible to know intuitively and quantitatively which direction of the lens is displaced. In addition, since the first distribution map is created based on the matrix data, the position of the hue and saturation based on the measurement value (the first distribution map) is compared by comparing the first distribution map and the second distribution map. The difference between the position shown in the distribution map) and their ideal position (position shown in the second distribution map) can be grasped quantitatively. Furthermore, it is possible to check whether the look-up table is functioning correctly based on the distribution chart, and if necessary, not only automatically correct the table but also easily correct it artificially. .

  In the lookup table creation method of the present invention, the matrix data is calculated based on the maximum saturation red, green, blue, and white XYZ values of the display device, or a reference XYZ value of a predetermined color space. And the reference color temperature. In the former case, since the point of maximum saturation is converted to the RGB maximum value around the white point of the display device itself, the gamma characteristic of the display device itself can be easily evaluated. In the latter case, the standard value becomes the reference, so that deviation from the standard value can be evaluated.

  In the lookup table creation method of the present invention, the color image generation means outputs the selected color or the randomly generated color to the display device, or displays the selected color or the randomly generated color on the display device. The color obtained by recording with the imaging device may be output to the display device again.

  By arbitrarily selecting and displaying colors, it is possible to assign grid points evenly in the lookup table or to provide many correction points in visually sensitive areas. In addition, correction points can be provided at random. In addition, the color emitted from the display device using the corrected lookup table is acquired by the imaging device and developed again from the display device, so that the color of the imaging device itself is evaluated, or the lookup table used by the imaging device Can be corrected.

  In the look-up table creation method of the present invention, the color image generating means uses a pattern in which the intensity of red, green, and blue is changed, a pattern in which the saturation of yellow, cyan, and magenta is changed, and the saturation is constant. The color of the pattern changed in the hue direction by 0 degrees or more and less than 360 degrees is output to the display device, and the correction step is based on at least 12 types of gamma characteristics obtained from the first RGB value and the second RGB value. The lookup table may be modified.

  A single-color gamma characteristic is obtained by changing the intensity of red, green, and blue. When the saturation of yellow, cyan, and magenta is changed, the complementary colors of blue, red, and green are obtained. However, in the latter case, the two colors other than the complementary colors have the same RGB value. Also, if the hue is changed at an angle of 0 degrees or more and less than 360 degrees in the hue direction with constant saturation, one color of RGB changes, and the other two colors have strength but do not change. be able to. In particular, when the saturation is changed to the maximum, it is possible to create a state in which one of RGB is 0, the other is maximum, and the other one is changed. Therefore, when these are combined, 12 types of gamma characteristics can be obtained, which is equivalent to tracing each side of the RGB color solid. By obtaining gamma characteristics in this way, it is possible to correct the look-up table by evaluating the state in which crosstalk occurs between pixels. The intensity represents brightness, and the same applies hereinafter.

  In the lookup table creation method of the present invention, in the correction step, the lookup table is modified based on the modification values calculated using at least 12 types of gamma characteristics, and in the conversion step, based on the modified lookup table. Thus, the color signal may be converted by estimating the correction amount inside the RGB color solid. In this case, for example, instead of the three-dimensional lookup table, twelve one-dimensional lookup tables are used, so that the correction amount in the color solid can be estimated with a much smaller number of points. Further, the correction amount inside the color solid can be accurately interpolated based on a lookup table corresponding to each side of the RGB color solid.

  In the lookup table creation method of the present invention, the correction amount inside the RGB color solid may be determined in the conversion step according to the distances from the sides parallel to each other in the RGB color solid. Thereby, the calculation of the correction amount becomes very simple, and the calculation time can be shortened.

  In the lookup table creation method of the present invention, in the measurement step, a colorimeter using a color filter having a transmission spectrum corresponding to the XYZ color matching function, or the light input for each wavelength component by splitting the input light. The wavelength intensity distribution or tristimulus value of light may be measured by a spectrocolorimeter that acquires the intensity. A colorimeter using a color filter has the advantage of being a simple device. In addition, since the spectrocolorimeter can output the wavelength intensity distribution, it can provide the wavelength intensity distribution together with the above distribution diagram, and the color value of the color value due to the difference in the wavelength intensity distribution of the display devices with different coloring methods can be provided. Information such as subtle differences can also be provided.

  In the lookup table creation method of the present invention, the spectrocolorimeter is output from an optical fiber having an end face for receiving light, an adapter for defining the distance between the end face of the optical fiber and the display device, and the optical fiber. You may have the spectral element which splits light, and the several light receiving element which light-receives the light disperse | distributed by the spectral element for every wavelength component. According to such a spectrocolorimeter, the distance between the end face of the optical fiber and the display device can be kept substantially constant by the adapter, so that a stable spectral distribution can be obtained. In addition, since the area corresponding to the numerical aperture (NA) of the optical fiber is measured, it is possible to know the state of a relatively narrow area of the display device. That is, the non-uniformity of the display device regarding the color can be evaluated.

ここで、ａ及びｂは定数であり、ＭＩＮ，ＭＡＸはそれぞれ、ＲＧＢ値のうちの最大値、最小値である。また、Ｉは彩度Ｓを無次元量にするための規格化定数であり、以下のように定義される。なお、定数Ｉの定義は下記に限定されない。

In the lookup table creation method of the present invention, in the first creation step, the hue is based on the following expressions (1a) and (1b) or the following expressions (1a) and (1c) using the first RGB values. H and saturation S may be obtained.

Here, a and b are constants, and MIN and MAX are the maximum value and the minimum value of the RGB values, respectively. I is a normalization constant for making the saturation S dimensionless, and is defined as follows. The definition of the constant I is not limited to the following.

  By displaying the hue and saturation obtained by such calculation on the distribution map, when a = b = 1, the positional relationship of red, green, and blue is an equilateral triangle on each distribution map, The positional relationship of yellow, cyan, and magenta can be an equilateral triangle. White is the origin of each distribution map. Therefore, a distribution map that is very easy to understand can be obtained. Further, the distribution map is displayed as a vectorscope. Further, a desired color region can be enlarged by selecting the values of a and b.

ここで、ａ及びｂは定数である。また、Ｊは彩度Ｓを無次元量にするための規格化定数であり、以下のように定義される。なお、定数Ｊの定義は下記に限定されない。

In the lookup table creation method of the present invention, the hue H and the saturation S may be obtained based on the following equation (2) using the first RGB values in the first creation step.

Here, a and b are constants. J is a normalization constant for making the saturation S dimensionless, and is defined as follows. The definition of the constant J is not limited to the following.

  In the first quadrant of each distribution map obtained by such calculation, the secondary color is located in the positive direction of the coordinate axis, and the primary color is located in the 45 degree direction. Further, in the distribution diagram, the negative direction of each coordinate axis is a direction representing a primary color which is a complementary color of the secondary color. Therefore, by using this distribution chart, it becomes easy to determine the primary color to be corrected to approximate the ideal color and the correction amount of the primary color.

  According to such a look-up table creation method, the difference between an ideal color and an actual display color can be intuitively and quantitatively evaluated, and conversion to a reference color can be easily and accurately performed. it can.

It is a block diagram which shows the color evaluation system which concerns on embodiment. It is a perspective view which shows the measurement unit in FIG. It is a figure which shows an XYZ color matching function. It is a flowchart which shows the lookup table creation method which concerns on embodiment. It is a figure which shows the example of the distribution map displayed by the color evaluation system in FIG. It is a figure which shows the example of the distribution map displayed by the color evaluation system in FIG. It is a figure which shows the example of the distribution map regarding a cathode ray tube. It is a figure which shows the example of the distribution map regarding the liquid crystal monitor using a cold cathode tube. It is a figure which shows the example of the distribution map regarding the liquid crystal monitor using three-color LED. It is a figure which shows the relationship between the measuring method of a gamma characteristic, and a color system. It is a figure which shows the relationship between the measuring method of a gamma characteristic, and a RGB color solid. It is a figure which shows the example of 12 types of gamma curves. It is a figure which shows the example of 12 types of gamma curves. It is a figure which shows the example of 12 types of gamma curves. It is a figure which shows typically distribution of the output value in a RGB color solid. It is a block diagram which shows the color evaluation system which concerns on another embodiment.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are denoted by the same reference numerals, and redundant description is omitted.

  First, the function and configuration of the color evaluation system 1 according to the embodiment will be described. As shown in FIG. 1, the color evaluation system 1 includes a color image generation device 11, a display device 12, a measurement unit 13, a matrix storage unit 14, a first calculation unit 15, a second calculation unit 16, a display 17, and a signal conversion unit 20. And a table correction unit 21. The color evaluation system 1 converts a signal (for example, an RGB signal or a YPbPr signal) sent from the color image generation device 11 to the display device 12, and evaluates the color of the pattern displayed on the display device 12 based on the converted signal. Computer system.

  The signal conversion unit 20 is a means for converting a color signal sent from the color image generation device 11 to the display device 12 using a look-up table stored in advance. When the color signal is input, the signal conversion unit 20 reads the lookup table, converts the color signal, and outputs the converted signal to the display device 12. The initial value of the lookup table is set so that the signal from the color image generator 11 is output as it is. This lookup table can be corrected by a table correction unit 21 described later.

  The signal conversion unit 20 estimates an internal correction value of the RGB color solid based on the lookup table, and converts the color signal using the estimation result. Since this estimation process is also related to the gamma characteristic described later, details of the process will be described later.

  The measurement unit 13 is means for measuring and acquiring the wavelength intensity distribution of the light emitted from the display device 12. As shown in FIG. 2, the measurement unit 13 includes an optical fiber 13a, a spectrometer 13b, and an adapter 13c. The spectroscope 13b includes a reflective diffraction grating 13d and a line sensor 13e.

  In the measurement unit 13, light from the display device 12 enters one end surface of the optical fiber 13a, and the light exits from the other end surface of the optical fiber 13a and enters the reflective diffraction grating 13d. The reflective diffraction grating 13d reflects incident light in different directions depending on the wavelength, and the line sensor 13e receives light of each wavelength component. The line sensor 13e outputs a signal corresponding to the intensity of the received light.

  The adapter 13c is a component that keeps the distance between the surface of the display device 12 and one end face of the optical fiber 13a constant. The adapter 13c has a cylindrical shape or a cone-like cylindrical shape, and holds an optical fiber therein. The inner surface of the adapter 13c has a function of preventing intrusion of light from the outside by black coating or the like. With this adapter 13c, the measurement unit 13 can stably measure the wavelength intensity distribution of the light from the display device 12.

  The measurement unit 13 may be a colorimeter that measures tristimulus values (XYZ values) instead of measuring the wavelength intensity distribution. For example, a colorimeter including three color filters having XYZ color matching function transparency and three light receiving elements can be used. A colorimeter using a color filter has the advantage of being a simple device. In the specification of Japanese Patent Application No. 2009-209625, another modification of the measurement unit 13 is described.

  The matrix storage unit 14 is a means for storing matrix data that associates XYZ values or chromaticity xyz obtained from wavelength intensity distributions or tristimulus values with RGB values. The matrix is calculated according to the following theory.

  The relationship between the XYZ value and the RGB value is defined by three expressions: X = aR + bG + cB, Y = dR + eG + fB, and Z = gR + hG + iB. The chromaticity xy is defined by two formulas x = X / (X + Y + Z) and y = Y / (X + Y + Z). As described above, the relationship between the RGB value and the XYZ value is obtained by three independent equations, and the relationship between the chromaticity xyz and the XYZ value is given by a ratio, so the relationship between the RGB value and the chromaticity xyz is independent. Determined by four equations.

  There are two methods for associating the RGB values with the chromaticity xyz: a method for matching with standard values and a method for matching with actual measurement values. When matched with the standard value, the deviation of the display device 12 from the actual standard value can be measured. On the other hand, the maximum performance of the optical display capability of the display device 12 can be easily evaluated by matching the measured values. This is because the maximum saturation is usually set to be larger than the standard value because the spectral distribution differs among individual display devices. That is, the color gamut is slightly larger than the standard value and is often adjusted to the vicinity of the standard value by electrical adjustment.

First, a method for adjusting to the standard value will be described. As color space standards, there are s-RGB, Adobe RGB, and the like. Here, Adobe RGB is described (Adobe is a trademark of Adobe Systems). In Adobe RGB, the maximum saturation red, green, and blue chromaticities (x, y) are (0.64, 0.33), (0.21, 0.71), and (0.15, 0), respectively. .06). White is determined by the color temperature or the like. For example, in the case of D65, it is assumed that the chromaticity (x, y) of white is (0.3127, 0.329). At this time, the relationship (matrix) between RGB values and XYZ values is determined as follows.
R = 1.80397X−0.49925Y−0.30461Z
G = −0.85643X + 1.65762Y + 0.03672Z
B = 0.01188X−0.10458Y + 0.89702Z (3)
If this equation group (3) is inversely transformed, the following relationship (matrix) is obtained.
X = 0.576767R + 0.18556G + 0.18823B
Y = 0.29734R + 0.62737G + 0.07529B
Z = 0.02703R + 0.07069G + 0.99133B (4)
Since the standard value specifies RGB and chromaticity xy with the maximum saturation, it goes without saying that the standard value can be calculated in the same manner even if the standard value is an arbitrary value.

  Next, a method for adjusting to actual measurement values will be described. Since the spectral distribution of the display device varies depending on the type of the device, even if the RGB value of the maximum saturation is displayed, the chromaticity xyz differs for each display device. Therefore, the color image generating device 11 generates the maximum saturation red, green, blue, and white and causes the display device 12 to develop colors. Then, the emitted color is measured with a colorimeter, and an XYZ value is obtained by equation (5) described later. Subsequently, the XYZ value is converted into chromaticity xyz, and a conversion formula (matrix) between RGB and XYZ is obtained. Further, an inverse matrix transformation formula is obtained in the same manner as in the case of standard values. Naturally, in this case, a matrix having different elements from the above matrix is obtained.

  The matrix storage unit 14 stores the matrix data calculated as described above. Hereinafter, in order to simplify the description, it is assumed that matrix data based on actually measured values is stored in the matrix storage unit 14.

  The first calculation unit 15 converts the XYZ values into RGB values using matrix data, calculates the hue and saturation based on the RGB values, and shows a distribution diagram (first distribution) indicating the positions of the hue and saturation This is a means for creating a figure.

ここで、S（λ）は波長強度分布であり、x（λ），ｙ（λ），ｚ（λ）はそれぞれ、図３に示すようなｘ，ｙ，ｚの等色関数であり、Ｋは任意の定数である。なお、測定ユニット１３が上述した測色計の場合には、第１演算部１５は測定ユニット１３によって生成されるデータの三刺激値をＸＹＺ値として用いることができる。 The first computing unit 15 calculates the XYZ value by applying the wavelength intensity distribution measured by the measuring unit 13 to the following equation (5).

Here, S (λ) is a wavelength intensity distribution, x (λ), y (λ), and z (λ) are x, y, and z color matching functions as shown in FIG. Is an arbitrary constant. When the measurement unit 13 is the colorimeter described above, the first calculation unit 15 can use the tristimulus values of the data generated by the measurement unit 13 as XYZ values.

  Subsequently, the first calculation unit 15 calculates the RGB value by applying the XYZ value to the conversion formula (for example, the formula group (3)) indicated by the matrix data read from the matrix storage unit 14. When the wavelength intensity distribution is obtained from the measurement unit 13, the first calculation unit 15 uses the RGB color matching functions r (λ), g (λ), b (λ) to calculate the RGB value from the wavelength intensity distribution. Can also be calculated directly. In this case, x (λ), y (λ), and z (λ) in the above equation (5) may be replaced with r (λ), g (λ), and b (λ), respectively.

  Subsequently, the first calculation unit 15 obtains the hue H and the saturation S by applying the calculated RGB values to the above formulas (1a) and (1b). The constants a and b in the equations (1a) and (1b) are arbitrary, but in the following description, a = b = 1. Note that equation (1c) may be used instead of equation (1b). Further, the first calculation unit 15 may calculate the hue H and the saturation S by applying the RGB values to the above equation (2). The constants a and b in the expression (2) are also arbitrary, but in the following description, a = b = 1. If a <0, the hue turns in the opposite direction. Also, if | a | ≦ 1, b> 1, the region of the color to be measured (for example, the color that humans feel sensitively different, such as the color of human skin) can be substantially enlarged. .

  Subsequently, the first calculation unit 15 creates a distribution diagram showing the positions of the obtained hue H and saturation S, in which the hue is in the declination direction and the saturation is in the radial direction. The illustrated data is output to the display 17. The first calculation unit 15 outputs the calculated RGB values to the table correction unit 21.

  The second calculation unit 16 calculates an RGB value based on the signal input from the color image generation device 11, calculates a hue and saturation based on the RGB value, and shows a distribution map indicating the position of the hue and saturation. This is means for creating a (second distribution diagram).

  The second calculation unit 16 receives the same signal as the signal output from the color image generation device 11 toward the display device 12, and obtains an RGB value from the signal. If the input signal is an RGB signal, the signal is used as it is as an RGB value. If the input signal is a YPbPr signal, the signal is converted into an RGB value by a known method. Subsequently, the second calculation unit 16 calculates the hue H and the saturation S by applying the RGB values based on the input signal to the expressions (1a), (1b), or the expressions (1a) and (1c). At this time, the second calculation unit 16 may calculate the hue H and the saturation S according to Expression (2). Then, the second calculation unit 16 creates a distribution diagram showing the positions of the hue H and the saturation S, in which the hue is in the declination direction and the saturation is in the radial direction, and the distribution map data Is output to the display 17. In addition, the second calculation unit 16 outputs the calculated RGB values to the table correction unit 21.

  In the color evaluation system 1, the first and second distribution diagrams are displayed on the display 17. Note that the display 17 may be omitted, and these distribution maps may be supplied to a display device or a storage device outside the system. In that case, the 1st calculating part 15 and the 2nd calculating part 16 can become an output means. Further, the distribution map creation function of the first calculation unit 15 and the second calculation unit 16 may be omitted in accordance with the omission of the display 17.

  The table correction unit 21 is a means for correcting (creating) the lookup table in the signal conversion unit 20. Since this process is also related to the gamma characteristic described later, details of the process will be described later.

  Hereinafter, the operation of the color evaluation system 1 and the lookup table creation method according to the present embodiment will be described with reference to FIG. As shown in FIG. 4, in the present embodiment, first, the color image generation device 11 outputs a color signal to the signal conversion unit 20 and the second calculation unit 16 (step S11, color image generation step). Subsequent processing is divided into measurement value calculation processing by the first calculation unit 15 and input value calculation processing by the second calculation unit 16.

  Calculation of measured values is as follows. First, the signal conversion unit 20 converts the color signal with reference to the lookup table, and outputs the converted signal to the display device 12 (step S12, conversion step). Subsequently, the measurement unit 13 measures the wavelength intensity distribution of the light from the display device 12 (step S13, measurement step). Subsequently, the RGB value is calculated based on the XYZ values calculated from the wavelength intensity distribution by the first calculation unit 15 and the matrix data read from the matrix storage unit 14 (step S14, first calculation step). Subsequently, the first calculation unit 15 calculates the hue H and the saturation S based on the calculated RGB values (step S15), and creates a first distribution map using the hue H and the saturation S (step S15). S16). Steps S15 and S16 can be said to be the first creation step.

  The input value is calculated as follows. The second computing unit 16 first calculates RGB values based on the signal from the color image generating device 11 (step S17, second calculation step). Subsequently, the second calculation unit 16 calculates the hue H and saturation S based on the RGB values (step S18), and creates a second distribution map using the hue H and saturation S (step S19). ). Therefore, steps S18 and S19 can be said to be the second creation step.

  The created first and second distribution maps are displayed on the display 17 (step S20, output step). Further, the table correction unit 21 corrects the lookup table based on the RGB values calculated by the calculation units 15 and 16 (step S21, correction step). Regardless of FIG. 4, the processing order of steps S20 and S21 is not limited.

  Hereinafter, the distribution diagram will be described. The first and second distribution charts are displayed as shown in FIG. 5, for example. In FIG. 5, the diagram on the left side displays the first and second distribution maps created using the above formulas (1a) and (1b) or the above formulas (1a) and (1c), Hereinafter, this display mode is referred to as format A. Further, the three diagrams in the center are the first and second distribution diagrams created by using the above formula (2) and are displayed in an overlapping manner.

  The diagram on the right side in FIG. 5 is the wavelength intensity distribution obtained by the measurement unit 13. By displaying the wavelength intensity distribution together with the distribution chart as shown in FIG. 5, it is possible to simultaneously observe the influence caused by the spectral distribution unique to the display device 12, and the subtlety of the color value due to the difference in the wavelength intensity distribution of the display devices with different coloring methods Information such as significant differences. Details of the wavelength intensity distribution are described in Japanese Patent Application No. 2009-209625.

  Of course, the result display method is not limited to the example of FIG. For example, the distribution map of format A, the distribution map of format B, and the wavelength intensity distribution may be displayed individually instead of simultaneously, or only one or two of them may be displayed. Further, the first distribution map and the second distribution map may be displayed individually without overlapping.

  FIG. 6 is an enlarged view of a part of FIG. In FIG. 6, reference signs R, G, B, C, M, Y, and W respectively indicate the hue and saturation when red, green, blue, cyan, magenta, yellow, and white are displayed on the display device 12. Indicates the position. A smaller black circle than the others indicates an ideal position of hue and saturation when an intermediate color is displayed on the display device 12, and is calculated by the second calculation unit 16. On the other hand, black squares indicate the positions of hue and saturation when an intermediate color is displayed on the display device 12 and are calculated by the first calculation unit 15.

  In the examples of FIGS. 5 and 6, the gamma value is intentionally increased to clearly show the saturation and hue shift between the measured value and the input value. It can be seen from FIGS. 5 and 6 that the input value and the measured value deviate if the gamma characteristics do not match. Therefore, by measuring the distance of input values and measured values in RGB space or xy space, calculating statistical data such as average values and standard deviations, and comparing the data with appropriately selected values, the measurement unit The degree of 13 color misregistration can also be determined. The color displayed at this time may be random or a specific color. If it is desired to obtain a display device with good color reproducibility in a specific area, the same determination can be made by artificially creating and displaying the color of that area. Arbitrary evaluation can be eliminated if colors are randomly generated.

  In FIG. 6, the white measurement value is deviated from the origin. To match this with the ideal origin, adjust the gamma specification, contrast, etc., and adjust the red and green by a predetermined amount in the positive direction. Only correction is necessary. The above formula (2) may be used to make it clearer in which direction the color misregistration occurs: red, green, or blue. When red, green, and blue are primary colors as in a display device, a distribution map of format B as shown in FIG. 6 is obtained. In the distribution diagram, secondary colors yellow, cyan, and magenta are located on the coordinate axes, and secondary colors complementary colors red, green, and blue are located in the negative direction of each axis. Therefore, it is possible to determine how much excess or deficiency exists for which primary color with respect to a color that is considered to have a color shift. In addition, since the conversion data is known, the correction amount can be easily calculated.

  FIGS. 7 to 9 are distribution diagrams of type A, respectively, relating to a cathode ray tube, a liquid crystal monitor using a cold cathode tube as a backlight, and a liquid crystal monitor using a three-color LED as a backlight. 7 to 9, black circles indicate the positions of the hue H and the saturation S based on the RGB values of the input signal, and are calculated by the second calculation unit 16. On the other hand, the black squares indicate the positions of the hue H and the saturation S converted from the XYZ values of the colors emitted by the display device 12, and are calculated by the first calculation unit 15. The outer curve represents the brightest color (boundary where the spectrum is single and theoretically there is no color outside). The center of each figure is the white point.

とした場合には、赤・緑・青はＲＧＢのいずれか一つが１で他が０なので、その最大彩度は

となる。また、黄・シアン・マゼンタはＲＧＢのいずれか一つが０で他が１なので、その最大彩度は

となる。したがって、赤・緑・青については白色点を除いて１６点が表示されており、黄・シアン・マゼンタについては白色点を除いて１１点が表示されている。他の色については１１〜１６個の点が表示されている。 Each of FIGS. 7 to 9 represents a state in which the red position is set to 0 degree, the hue H is changed at intervals of 15 degrees, and the saturation S is changed from the maximum value 1 by 20 steps. In the above formula (1b)

In the case of red, green and blue, one of RGB is 1 and the other is 0, so the maximum saturation is

It becomes. For yellow, cyan, and magenta, one of RGB is 0 and the other is 1, so the maximum saturation is

It becomes. Therefore, 16 points are displayed for red, green, and blue, excluding the white point, and 11 points are displayed for yellow, cyan, and magenta, excluding the white point. For other colors, 11 to 16 dots are displayed.

  7 to 9, the saturation planes are arranged at substantially equal intervals in the radial direction with white as the center. The interval in the hue direction is slightly widened in the vicinity of red, green, and blue and slightly narrowed in the vicinity of yellow, cyan, and magenta, but can be said to be relatively equal as a whole. In the distribution map of format A, the angle between the primary colors and the angle between the secondary colors are each 120 degrees. The angle between the primary color and the secondary color is 60 degrees. As described above, in the distribution diagram of the present embodiment, the amount of change in saturation is substantially constant, and the measured values are also RGB values with respect to the RGB values that are the input signals of the display device, so the results are very easy to understand. It is displayed in a shape and the amount of deviation can be easily grasped.

  Since the cathode ray tube is of the NTSC system and its color gamut corresponds to s-RGB, as shown in FIG. 7, the RGB input values and the measured values almost coincide. This indicates that the color reproducibility is very good for any color in the cathode ray tube. On the other hand, in a liquid crystal monitor using a cold cathode tube as a backlight, as shown in FIG. 8, a color shift occurs from blue to magenta, and a non-linear behavior is observed at low saturation. Further, in the liquid crystal monitor using the three-color LED for the backlight, as shown in FIG. 9, relatively large color shift and poor adjustment of the gamma characteristic are recognized in the green part and the part from blue to magenta. As one of the causes of color misregistration, in the case of liquid crystal, the influence of crosstalk between adjacent pixels can be considered. From the viewpoint of electrical signals, it is considered that even if R, G, and B are driven independently, adjacent pixels are affected by the color filter position shift and leakage electric field.

  FIG. 10 is a diagram illustrating an example of a pattern in which the hue and saturation of the input RGB signal change in order to quantify such an effect. For red, green, and blue, the intensity is changed without changing the saturation, as indicated by reference signs P1 to P3 in FIG. For example, by changing the intensity in 25 steps, standardizing the values of other intensities with the total intensity of the RGB spectrum of each color at the maximum saturation, or the maximum value of the spectrum when each color is emitted, the input RGB Measured value relative to value. For yellow, cyan, and magenta, the saturation is changed in 25 steps as indicated by reference numerals P4 to P6 in FIG. For example, for yellow, RGB = (255,255,0), (255,255,10),... Is changed, and the color when converted from an XYZ value to an RGB value is used as a measurement value. Further, as indicated by reference numerals P7 to P12 in FIG. 10, with respect to the hue direction having the maximum saturation, one of RGB is fixed to 255 and the other one is fixed to 0, while the remaining one is fixed. One is changed in 25 steps, and the color when converted from XYZ values to RGB values is taken as a measurement value. For example, in the range indicated by the symbol P7, that is, in the range of RGB from (255, 0, 0) to (255, 255, 0), the intensity of green is changed in 25 steps.

  FIG. 11 is a diagram showing each side of the RGB color solid. Reference signs P1 to P12 in FIG. 11 correspond to reference signs P1 to P12 in FIG. That is, the acquisition of the measurement value described with reference to FIG. 10 means that the gamma characteristic of each side of the color solid is measured. Normally, the display performance is measured by changing the intensity of each of the three primary colors. However, when crosstalk occurs, the influence of adjacent pixels cannot be ignored. In particular, in a high-definition small display or large display, this influence becomes a big problem in color reproduction. However, since the adjacent pixels are not colored in the case of a single color, the influence of crosstalk cannot be measured using the gamma characteristics of the single color RGB. According to this embodiment, since the gamma characteristic of each side of the color solid can be measured from the generated color itself, the color development performance of the display device can be evaluated on a macro scale.

  FIG. 12 is a graph of a gamma curve corresponding to the change pattern as shown in FIGS. FIG. 12 shows measured values calculated by the first calculation unit 15 based on a series of change patterns output from the color image generating device 11, and input values calculated by the second calculation unit 16 based on the change patterns. Shows the relationship. In response to the gamma value of the display device 12 being 2.2, the gamma value of the input signal is set to 0.454545. The vertical axis and horizontal axis of each graph are the measured value and the input value, respectively, and the symbols P1 to P12 attached to each graph correspond to the symbols P1 to P12 in FIGS.

  The graphs P1, P5, P8 and P11 show red changes, the graphs P2, P6, P7 and P10 show green changes, and the graphs P3, P4, P9 and P12 show blue changes. ing. For example, the graph of P12 shows the gamma characteristic of blue when red is maximum saturation (255) and green is 0. In this way, 12 types of gamma characteristics can be obtained by measuring the gamma curve of each side of the RGB color solid shown in FIG. As shown in FIG. 12, the measured value is substantially linear with respect to the input signal, but the straight line of the graph is somewhat distorted due to the influence of crosstalk or the like. As described above, according to the present embodiment, the influence of the phenomenon between adjacent pixels on the gamma characteristic can be quantified. Needless to say, if the saturation is constant, the same phenomenon occurs even if the saturation is not the maximum value.

In the following, the theory of the correction method of the lookup table (processing of the table correction unit 21) and the method of estimating the internal correction value of the RGB color solid based on the lookup table (processing of the signal conversion unit 20) will be described. Will be described in detail. When the gamma characteristic peculiar to the display device is γ, the RGB values of the input signal output linearly are R, G, B, and the RGB values of the signal output from the display device are R _out , G _out , B _out , R _out = 255 * (R / 255) ^γ , G _out = 255 * (G / 255) ^γ , B _out = 255 * (B / 255) ^γ When the gamma characteristic γ _in of the input signal itself is γ _in = 1 / γ and the RGB values of the input signal itself are R _in , G _in , B _in , R = 255 * (R _in / 255) ^γin , G = 255 * (G _in / 255) ^γin , B = 255 * (B _in / 255) ^γin Therefore, the following formula group (6) is established.
R _out = 255 * (R _in / 255) ^γγin
G _out = 255 * (G _in / 255) ^γγin
B _out = 255 * (B _in / 255) ^γγin (6)

When γ _in = 1 / γ = 1 / 2.2, R _out = R _in , G _out = G _in , and B _out = B _in , and a signal is linearly output from the display device. This means the twelve types of gamma characteristics shown in FIG. 12, but in actuality, as shown in FIG. This appears as a color shift.

From the above formula group (6), γγ _in = log (R _out / 255) / log (R _in / 255) is obtained. For example, if the measured value is 204 with respect to the input value 200 in the graph of FIG. 12, γ = 2.2 * log (204/255) / log (200/255) = 2.020677 and 1 / γ = 0.49488. Since R _out = 255 * (R / 255) ^γ and R = 255 * (R _out / 255) ^{1 / γ} , in order to set the output value R _out to the same 200 as the input value, R _in = 200 Should correspond to 226. If such association is performed for all points on the gamma curve in FIG. 12, correction values can be obtained for each side of the RGB color solid shown in FIG. The lookup table is a collection of data indicating the association for obtaining the correction value.

Note that γ _in may be a value other than 1 / 2.2. For example, if γ _in = 1, the gamma characteristic of the display device itself is obtained, and a gamma curve as shown in FIG. 13 is obtained. If γ _in = 0.2, then γγ _in = 2.2 * 0.2 = 0.44, and a gamma curve as shown in FIG. 14 is obtained. Of course, the distribution map showing the positions of hue and saturation changes according to γ _in . In the case of FIG. 13, the output value relative to the input value increases in a region where the input value is large, and the measurement error decreases. On the other hand, in the case of FIG. 14, the output value with respect to the input value increases in a region where the input value is small, and the measurement error decreases. Therefore, if the correction values of all sides of the color solid are obtained by combining the examples as shown in FIGS. 13 and 14, the accuracy of the correction values is improved. However, since it is necessary to obtain a plurality of patterns while changing the gamma characteristic of the input value, time is required accordingly.

  FIG. 15 is a diagram schematically showing the distribution of output values on one surface of the RGB color solid shown in FIG. 11, and specifically, a surface including four vertices V7, V4, V2, and V6, that is, B = 255. The distribution in the RG plane is shown. In FIG. 15, the position of the output value (measured value) is indicated by a black circle. The signal conversion unit 20 calculates (estimates) a correction value that can be placed at a predetermined point in the plane with respect to the output value as shown in FIG. 15, and converts the color signal. When each of R, G, and B is represented by 8 bits, it is desirable to obtain 256 correction values on each side. However, even if the number of correction values on each side is smaller than that, interpolation between correction points may be performed. The same effect can be obtained.

Table 1 shows the output values (measured values) of each side of the RGB color solid when γ is about 2.2 for some representative points. The first and second rows of Table 1 are output values on the upper side (side P11) and the lower side (side P5) shown in FIG. Further, the third and fourth rows of Table 1 are output values at sides P1 and P8 of the surface opposite to the surface shown in FIG. Since γ is about 2.2, the smaller the red (R) input value, the greater the distance between points corresponding to the inverse of γ.

  Needless to say, a set of output values is obtained in the same manner for the other sides in FIG. 11, that is, when the input value of green (G) is changed and when the input value of blue (B) is changed. If these 12 sets of output values are corrected using a look-up table, and the correction values inside the RGB color solid are estimated, an accurate correction value for the entire color solid can be obtained by calculating very few correction points. be able to.

As an estimation method, there is a method of calculating a correction value according to the distance from two sides parallel to each other in the RGB color solid. For example, for a certain red (R) input value X, the RGB values of the output signal are (R1, 0, 255), (R2, 255, 255), (R3, 0, 0), (R4, 255, 0). ). Here, R1 to R4 are output values of red (R). In the example of Table 1, when the input value R = 50, R1 = 127, R2 = 120, R3 = 119, and R4 = 124. When the output values of R, G, and B with respect to the reciprocal of γ are represented by R ′, G ′, and B ′, for example, R ′ = 255 * (R / 255) ^{1 / γ} = 255 * (50/255) ^{1 / 2.2} = 121.5955. If the gamma value of each side when the gamma value of the input signal is set to 1 (see FIG. 13) is obtained by the least square method or the like and is calculated as described above using the reciprocal thereof, R ′, G ′, B ′ Can be calculated with higher accuracy.

The correction value inside the color solid is obtained as follows. In the RG plane shown in FIG. 15, R1 ′ = R1 + G ′ * (R2−R1) / 255. Further, the surface facing the RG surface is R2 ′ = R3 + G ′ * (R4−R3) / 255. Therefore, the following formula is established for the interior of the color solid.
R = R2 ′ + B ′ * (R1′−R2 ′) / 255
= R3 + G '* (R4-R3) / 255 + B' *
((R1-R3) + G '* ((R2-R1)-(R4-R3)) / 255) / 255

Similarly, for an input value Y of a certain green (G), RGB values are (0, G1, 255), (255, G2, 255), (0, G3, 0), (255, G4, 0) If given, the following equation holds for the interior of the color solid.
G = G3 + B ′ * (G1-G3) / 255 + R ′ *
((G4-G3) + B '* ((G2-G4)-(G1-G3)) / 255) / 255

Also, RGB values are given as (0, 255, B1), (255, 255, B2), (0, 0, B3), (255, 0, B4) for an input value Z of a certain blue (B). If so, the following equation is established for the interior of the color solid.
B = B3 + R ′ * (B4-B3) / 255 + G ′ *
((B1-B3) + R '* ((B2-B1)-(B4-B3)) / 255) / 255

  In this way, the input value X in consideration of the positional relationship between (X, 0, 0), (X, 255, 0), (X, 255, 255), (X, 0, 255) and Y, Z. By determining the value of R corresponding to B and G in the same manner, the value (correction value) inside the color solid can be estimated from the values (correction values) of each side of the RGB color solid.

Conventionally, an RGB color solid is filled with a cube of a certain size, and the correction amount of each lattice point is used as a lookup table. Therefore, for example, when an 8-bit color space is divided into 16 (M = 16), 16 × 16 × 16 cubic lattice points are required, and the number of lattice points is (M + 1) ³ = 17 ³ = 4913. The number of internal points enclosed by one cube is 4096 points. On the other hand, according to the present embodiment, RGB values are obtained for each side by the number of decomposition points. Therefore, if the resolution is 8 bits, the color from the data of 256 (points) × 12 (sides) = 3072 points is used. The correction value inside the solid is estimated. At this time, it is sufficient if the lookup table has data for obtaining the correction amount on each side of the RGB color solid. Further, in the present embodiment, correction points are arranged on each side, so that it can be estimated more accurately. For example, since the above-described crosstalk is considered to be proportional to the amount of light or the applied electrical signal, the correction value of each side of the color solid that maximizes the crosstalk is used to change the RGB value inside the color solid from the side. If the distance is estimated linearly, the RGB value can be accurately estimated.

  In this way, the lookup table is applied to a signal of an arbitrary color or a randomly determined color output from the color image generating device 11, and the first and second distribution diagrams shown in FIG. 6, FIG. 12, etc. The effectiveness of the lookup table can be confirmed by analyzing the gamma curve shown in FIG. Despite the use of a look-up table, if the gamma characteristic shows non-linearity for reasons other than the above, and a deviation is confirmed in a certain area inside the color solid, the portion where the color deviation occurs is distributed. It is possible to check the figure and make further modifications. Eventually, the input value and the measured value should match within the error range, and the gamma curve should be linear as shown in FIG.

  The present embodiment can also be applied to the case where a normal three-dimensional lookup table is created. In other words, if the changes in hue and saturation are equally spaced and the change in intensity is the same as the change in hue and saturation, the cubic lattice points at regular intervals are measured, and for each lattice point, If a lookup table is created, a corrected value can be obtained.

  It is also possible to easily increase the number of grid points for visually sensitive areas such as skin, sky and sea. Specifically, an area in which color misregistration occurs is specified, the color of that part is generated, and a lookup table for the specific color in the area is created. In this way, the RGB value is estimated based on a lookup table corresponding to each side of the RGB color solid for most colors, and a separate three-dimensional lookup table is created for a specific area and used together. By doing so, the correction value can be obtained very reasonably.

  It is also possible to perform more detailed correction using points inside the color solid. For example, a pattern in which the saturation and intensity are changed along a line segment connecting two vertices having the center of symmetry (128, 128, 128) of the RGB color solid may be created. That is, change patterns are created between vertex V1 and vertex V2, vertex V3 and vertex V4, vertex V5 and vertex V6, and vertex V7 and vertex V8 in FIG. For example, between the vertex V3 and the vertex V4, RGB changes from (0, 255, 0) to (10, 245, 10), (20, 235, 20), ..., (255, 0, 255). Let In this case, it may be considered that a kind of gamma characteristic relating to green was measured while changing the intensity. These four kinds of new characteristics are certain gamma characteristics of red, green, blue, and white when the intensity is changed. Using a total of 16 types of gamma characteristics, which is a combination of the above 12 types and these 4 types, the correction value inside the color solid may be calculated according to the distance from each line segment in the same manner as described above.

  Also, a smaller RGB color solid centered at the center (128, 128, 128) of the RGB color solid may be considered. For example, the following 8 points (64, 64, 64), (64, 64, 192), (64, 192, 64), (192, 64, 64), (64, 192, 192), (192, 64) , 192), (192, 192, 64), (192, 192, 192), a pattern in which the color is changed on the side of the cube apex is substantially a pattern in which the intensity is changed by one color. Thus, 12 types of gamma characteristics with different biases can be obtained. Then, for each side of both the large and small RGB color solids, a correction value on the side is calculated using the lookup table in the same manner as described above, and the correction value inside the color solid is determined according to the distance from each side in the same manner as described above. Is calculated, the correction value inside the three-dimensional object can be obtained with higher accuracy.

  As described above, according to the present embodiment, the measured value is obtained by comparing the RGB value (measured value) calculated based on the measurement result with the RGB value (reference value) calculated based on the input signal. The deviation can be made simple and quantitative. Further, by correcting the lookup table based on the comparison, conversion to a reference color can be performed easily and accurately.

  In addition, it is possible to know intuitively and quantitatively in which direction the color development from the display device 12 is shifted in red, green, and blue. Since the first distribution map is created based on the matrix data, by comparing the first distribution map and the second distribution map, the position of the hue and saturation based on the measurement value (first distribution map). ) And their ideal positions (positions shown in the second distribution chart) can be quantitatively grasped. Further, whether or not the lookup table is functioning correctly is checked based on the distribution chart, and if necessary, the table can be corrected not only automatically but also easily and artificially.

  Next, a color evaluation system 2 according to another embodiment will be described. One of the objects of this embodiment is to evaluate various characteristics of the imaging device using a display device whose performance has already been found. As shown in FIG. 16, the color evaluation system 2 includes an imaging device 18 and an image memory 19, and a color image generation device 11A, a display device 12A, a first calculation unit 15A, a second calculation unit 16A, and The processing content of the table correction unit 21A is different from the color evaluation system 1 in that the processing content of the table correction unit 21A is different from the color image generation device 11, the display device 12, the first calculation unit 15, the second calculation unit 16, and the table correction unit 21. Below, the description regarding the function and structure similar to the color evaluation system 1 is abbreviate | omitted, and especially a different point is demonstrated.

  The display device 12A has a signal conversion function and a lookup table inside. That is, the display device 12A is a device in which the signal conversion unit 20 and the display device 12 in the above embodiment are combined. The imaging device 18 also has a function corresponding to the signal converter 20 and a lookup table. As described above, the arrangement of the signal conversion function and the lookup table may be arbitrarily determined. In the color evaluation system 2, it is assumed that the correction of the lookup table of the display device 12A has already been completed by the method of the above embodiment.

  The imaging device 18 captures an image displayed by the display device 12A, and stores the captured image data in the image memory 19 without being processed. Therefore, the data stored in the image memory 19 represents an image reflecting only the output characteristics of the imaging device 18. The color image generation device 11A reads the imaging data from the image memory 19, and outputs a signal based on the data to the display device 12A and the second arithmetic unit 16A.

  The first computing unit 15A receives the input of the image measurement result based on the imaging data, calculates a first RGB value, and creates a first distribution map. On the other hand, the second calculation unit 16A receives a signal input based on the imaging data, calculates a second RGB value, and creates a second distribution map. The calculation and distribution map creation procedures in the first calculation unit 15A and the second calculation unit 16A are the same as those in the first calculation unit 15 and the second calculation unit 16 described above.

  The created first and second distribution maps are displayed on the display 17 (step S19, output step). As described above, since the output characteristics of the display device 12A are already known, the changed amount indicates the characteristics of the imaging device 18.

  The table correction unit 21A corrects the lookup table in the imaging device 18 based on the first and second RGB values input from the calculation units 15A and 16A as in the above embodiment.

  DESCRIPTION OF SYMBOLS 1,2 ... Color evaluation system 11, 11A ... Color image generator, 12, 12A ... Display apparatus, 13 ... Measuring unit, 13a ... Optical fiber, 13b ... Spectroscope, 13c ... Adapter, 13d ... Reflective diffraction grating, 13e ... Line sensor, 14 ... Matrix storage unit, 15, 15A ... First calculation unit, 16, 16A ... Second calculation unit, 17 ... Display, 18 ... Imaging device, 19 ... Image memory, 20 ... Signal conversion unit, 21 , 21A ... Table correction section.

Claims (11)

A color image generating step in which the color image generating means outputs a color signal to the display device; and
A conversion step of reading a lookup table from the first storage means, and converting the color signal sent from the color image generation means to the display device using the lookup table;
A measurement step of measuring a wavelength intensity distribution of light from the display device or a tristimulus value based on the light;
The matrix data relating the XYZ values or chromaticity xyz obtained from the wavelength intensity distribution or the tristimulus values and the RGB values is read from the second storage means, and the XYZ values obtained in the measurement step are obtained using the matrix data. A first calculation step for converting to a first RGB value;
A second calculating step of calculating a second RGB value based on the color signal input from the color image generating means;
A correction step of comparing the first RGB value and the second RGB value to correct a lookup table in the first storage means;
A lookup table creation method including A first creation step of calculating a first hue and saturation based on the first RGB value, and creating a first distribution map indicating the position of the first hue and saturation;
A second creation step of calculating a second hue and saturation based on the second RGB values, and creating a second distribution map showing the positions of the second hue and saturation;
An output step of outputting the first distribution map and the second distribution map;
Further including
The first distribution chart and the second distribution chart are distribution charts in which hue is declination and saturation is radial.
The lookup table creation method according to claim 1. The matrix data is calculated based on the maximum saturation red, green, blue, and white XYZ values of the display device, or based on a reference XYZ value and a reference color temperature of a predetermined color space. Calculated,
The lookup table creation method according to claim 1 or 2. The color image generating means outputs a selected color or a randomly generated color to the display device, or an image pickup device that outputs the selected color or a randomly generated color from the display device. The color acquired and recorded by the above is output to the display device again.
The lookup table creation method according to any one of claims 1 to 3. The color image generating means includes a pattern in which the intensity of red, green, and blue is changed, a pattern in which the saturation of yellow, cyan, and magenta is changed, and a saturation of 0 degree or more and less than 360 degrees in the hue direction. Output the color of the changed pattern to the display device;
In the correction step, the lookup table is corrected based on at least 12 types of gamma characteristics obtained from the first RGB value and the second RGB value.
The lookup table creation method according to any one of claims 1 to 4. In the correction step, the lookup table is corrected based on a correction value calculated using the at least 12 types of gamma characteristics.
In the conversion step, the color signal is converted by estimating an internal correction amount of the RGB color solid based on the corrected lookup table.
The lookup table creation method according to claim 5. In the converting step, an internal correction amount of the RGB color solid is determined according to a distance from sides parallel to each other in the RGB color solid.
The lookup table creation method according to claim 6. In the measurement step, a colorimeter using a color filter having a transmission spectrum corresponding to an XYZ color matching function, or a spectrocolorimeter that obtains the intensity of light for each wavelength component by separating input light, The wavelength intensity distribution of the light or the tristimulus value is measured,
The lookup table creation method according to any one of claims 1 to 7. The spectrocolorimeter is
An optical fiber having an end face for receiving light;
An adapter for defining a distance between the end face of the optical fiber and the display device;
A spectroscopic element for dispersing light output from the optical fiber;
A plurality of light receiving elements that receive light separated by the spectral element for each wavelength component;
Having
The lookup table creation method according to claim 8. In the first creation step, the hue H and the saturation S are obtained based on the following expressions (1a) and (1b) or the following expressions (1a) and (1c) using the first RGB values. Here, a and b are constants, and MIN and MAX are the maximum value and the minimum value of the RGB values, respectively.
The lookup table creation method according to any one of claims 2 to 9.

Here, I is a normalization constant for making the saturation S a dimensionless quantity, and is defined as follows.

In the first creation step, the hue H and the saturation S are obtained based on the following equation (2) using the first RGB values, where a and b are constants.
The lookup table creation method according to any one of claims 2 to 10.

Here, J is a normalization constant for making the saturation S a dimensionless quantity, and is defined as follows.

Images