JP2015207915A - Image processing apparatus and method thereof - Google Patents

Abstract

PROBLEM TO BE SOLVED: To create a color conversion table corresponding to a subject.SOLUTION: A whole-gamut color chart creation section 14a outputs data of a whole-gamut color chart 23 corresponding to a whole gamut of a signal value of a printer 103 to the printer 103 and outputs the whole-gamut color chart 23. An output color gamut acquisition section 11 acquires data indicating a color gamut of the printer 103 from image data obtained by imaging the whole-gamut color chart 23 with a camera 102. A subject color gamut extraction section 12 extracts a subject color gamut corresponding to a color included in a subject 104 from image data obtained by imaging the subject 104 with the camera 102. A color gamut creation section 13 creates a target color gamut from the subject color gamut. A target color chart creation section 14b creates data of a target color chart on the basis of the data indicating the color gamut of the printer 103 and the target color gamut, outputs the data of the target color chart to the printer 103 and outputs the target color chart. A conversion table creation section 15 creates a color conversion table from image data obtained by imaging the target color chart with the camera 102, and the data of the target color chart.

Description

  The present invention relates to color conversion processing of image data.

  To perform color matching for a printer, create a color chart of multiple colors corresponding to the entire color gamut that the printer can reproduce, and use the color measurement results of the color chart to create a three-dimensional lookup table (3DLUT) for color conversion. Need to create.

  Patent Document 1 describes that a multi-level interpolated 3DLUT is created from a 3DLUT created from the colorimetric results of color charts of a plurality of colors by interpolation calculation. In addition, for important colors, it is described that a color chart in which the assigned values are subdivided is created, and the interpolated 3DLUT is corrected based on the colorimetric results of those color charts to create a 3DLUT with good color reproducibility.

  In Patent Document 2, when correcting the 3DLUT for color conversion, it is necessary to obtain the distance of the color space between the target color and the grid point of the 3DLUT and convert the target color to the desired color according to the distance A method for obtaining the conversion amount of a simple grid point will be described.

  The 3DLUT for color conversion created by the conventional method for the entire color gamut of the printer or the method of Patent Document 1 is created regardless of the image to be printed. On the other hand, image data that is actually printed often uses only a part of the color gamut of the printer.

  In addition, the technique of Patent Document 2 targets the entire color gamut of the printer in the same way as the conventional method and the method of Patent Document 1, and improves the reproducibility of important colors by moving the grid points near the important colors. Plan. For this reason, there is a concern about deterioration of gradation in the vicinity of the important color, and it is good to reproduce the important color pinpoint, but in other cases, the color difference near the important color may be deteriorated.

Japanese Patent Laid-Open No. 11-220630 JP-A-11-205620

  An object of the present invention is to create a color conversion table corresponding to a subject.

  The present invention has the following configuration as one means for achieving the above object.

  The image processing according to the present invention outputs, to the output device, data of a global color chart corresponding to the entire range of signal values of the output device, causes the output device to output the global color chart, and causes the imaging device to output the global color chart. Data indicating the color gamut of the output device is acquired from image data obtained by photographing a vote, a subject color gamut corresponding to a color included in the subject is extracted from image data obtained by photographing the subject by the photographing device, and the subject color gamut The target color gamut is created from the data, the target color chart data is created based on the data indicating the color gamut of the output device and the target color gamut, the target color chart data is output to the output device, and the output The target color chart is output to a device, and the image data obtained by photographing the target color chart by the photographing device and the target color chart data are output. To create a color conversion table from the data.

  According to the present invention, a color conversion table corresponding to a subject can be created, and the color reproduction accuracy of an image of the subject can be improved.

1 is a block diagram illustrating a configuration example of an image processing apparatus according to Embodiment 1. FIG. The figure which shows the example of the color chart which a printer prints. 3 is a flowchart for explaining image processing by the image processing apparatus according to the first embodiment. 3 is a flowchart for explaining image processing by the image processing apparatus according to the first embodiment. FIG. 3 is a diagram illustrating an example of a printer color gamut. FIG. 4 is a diagram illustrating an example of a printer color gamut and a subject color gamut. The figure which shows an example of a target color gamut. 9 is a flowchart for explaining target color gamut creation processing by a color gamut creation unit. The flowchart explaining the creation process of the target color chart by the target color chart creation part. FIG. 3 is a block diagram illustrating a configuration example of an image processing apparatus according to a second embodiment. 9 is a flowchart for explaining image processing by the image processing apparatus according to the second embodiment. 9 is a flowchart for explaining image processing by the image processing apparatus according to the second embodiment. FIG. 4 is a block diagram illustrating a configuration example of an image processing apparatus according to a third embodiment. 10 is a flowchart for explaining image processing by the image processing apparatus according to the third embodiment. 10 is a flowchart for explaining image processing by the image processing apparatus according to the third embodiment.

  Hereinafter, image processing according to an embodiment of the present invention will be described in detail with reference to the drawings.

[Device configuration]
The block diagram of FIG. 1 shows a configuration example of the image processing apparatus 101 of the first embodiment.

  The color chart creating unit 14 includes a global color chart creating unit 14a and a target color chart creating unit 14b. The color chart creation unit 14a creates color chart data (hereinafter, global color chart) 23 corresponding to the entire signal value of the printer 103 (hereinafter, global data), and outputs the global data via the output unit 22 to the printer. Output to 103. The printer 103 is a printer used for printing an image of the subject 104.

For example, when the signal value of the printer 103 is 8 bits for each RGB color, the entire area data is (R, G, B) = (0, 0, 0) (0, 0, 32) ... (255, 255, 224) (255 , 255, 255) corresponding to grid points that divide the signal value range into nine equal parts. The whole area data is a device RGB value of the printer 103. The printer 103 to which the entire area data is input prints a color chart of, for example, 9 ³ = 729 colors corresponding to the data of each grid point by the entire area data. With this color chart, the color reproduction characteristics (color reproduction range) of the printer 103 can be expressed.

  An example of a color chart printed by the printer 103 is shown in FIG. The example in Fig. 2 shows an example of printing a color chart of 729 colors as a color chart of 23 rows and 32 columns (736 cells). Arbitrary data may be printed or printed in the remaining seven cells. It does not have to be.

  The output color gamut obtaining unit 11 inputs image data obtained by photographing the entire color chart 23 from a digital camera (hereinafter referred to as a camera) 102 that is a photographing device via the input unit 21. Then, the average value of the RGB values (hereinafter referred to as RGB average values) of the image data of each color chart of the entire color chart 23 is calculated as data indicating the color gamut of the printer 103 (hereinafter referred to as the printer color gamut).

  The subject color gamut extraction unit 12 inputs image data obtained by capturing the subject 104 to be reproduced from the camera 102 via the input unit 21. Then, data indicating the color included in the subject 104 (hereinafter, subject color gamut) is extracted from the image data of the subject 104.

  Although described in detail later, the color gamut creating unit 13 creates a new color gamut (hereinafter referred to as a target color gamut) from the subject color gamut data.

  When the target color gamut is created, the target color chart creation unit 14b creates new color chart (hereinafter referred to as target color chart) 24 data (hereinafter referred to as target data) from the target color gamut and the printer color gamut and outputs it. The target data is output to the printer 103 via the unit 22. The printer 103 to which the target data is input prints the target color chart 24.

  The conversion table creation unit 15 inputs image data obtained by capturing the target color chart 24 from the camera 102 via the input section 21, and creates a color conversion table from the image data of the target color chart 24 and the target data.

  The image conversion unit 16 performs color conversion on the image data of the subject 104 input from the camera 102 using the created color conversion table, and outputs the color converted image data to the printer 103 via the output unit 22. . The printer 103 to which the color-converted image data is input prints an image of the subject 104 based on the image data.

  The image processing apparatus 101 and its functions according to the embodiment can be realized by supplying an image processing program to be described later to a computer device, and the CPU of the computer device executes the program. The input unit 21 and the output unit 22 are serial bus interfaces such as USB.

[Image processing]
Image processing by the image processing apparatus 101 will be described with reference to the flowcharts of FIGS. 3A and 3B.

  The global color chart creation unit 14a outputs the data (global data) of the global color chart 23 to the printer 103, and causes the printer 103 to print the global color chart 23 (S11).

  When the photographing of the entire color chart 23 by the camera 102 is completed, the output color gamut acquisition unit 11 inputs the image data of the entire area color chart 23 from the camera 102 and calculates the RGB average value of the image data of each color chart (S12). . As a method for calculating the RGB average value, for example, pixel values (RGB values) of a plurality of pixels may be acquired from the color chart area, and an average value of the pixel values may be obtained. By using the average value, it is possible to reduce the influence of noise generated during shooting. The photographed image data is an sRGB value (or AdobeRGB value).

  When the photographing of the subject 104 by the camera 102 is completed, the subject color gamut extraction unit 12 inputs image data of the subject 104 from the camera 102 (S13). The shooting conditions of the subject 104 and the shooting conditions of the entire color chart 23 are preferably the same. The shooting conditions include shooting location, light source type and position, ISO sensitivity, shutter speed, aperture value, and the like. By matching the shooting conditions, sRGB values obtained by shooting the subject 104 and the entire color chart 23 under the same conditions can be obtained, and the device RGB values for reproducing the image of the subject 104 by the printer 103 can be easily calculated.

  Next, the subject color gamut extraction unit 12 extracts a subject color gamut (S14). For extracting the subject color gamut, for example, the sRGB values of all the pixels are mapped to the RGB space. Alternatively, the image data may be subsampled so that the data amount becomes 1/2, 1/3, etc., and the sRGB values of the subsampled image data may be mapped to the RGB space.

  Next, as will be described in detail later, the color gamut creating unit 13 creates a target color gamut from the subject color gamut (S15). When creating the target color gamut, for example, a space including the sRGB values of the subject 104 mapped to the RGB space may be obtained using a convex hull.

  Next, as will be described in detail later, the target color chart creation unit 14b obtains the data (target data) of the target color chart 24 from the RGB average value indicating the printer color gamut calculated by the output color gamut acquisition unit 11 and the target color gamut. Create (S16). Then, the target data is output to the printer 103, and the target color chart 24 is printed on the printer 103 (S17). Note that the target data is a device RGB value of the printer 103.

  When the shooting of the target color chart 24 by the camera 102 is completed, the conversion table creation unit 15 inputs the image data of the target color chart 24 from the camera 102, and the RGB average of the image data of each color chart is the same as the processing in step S12. A value is calculated (S18). Then, a color conversion table is created from the RGB average value of the target color chart 24 and the target data (S19). That is, the conversion table creation unit 15 converts the average value (R3, G3, B3) of the sRGB values acquired from the target color chart 24 into the device RGB values (R2, G2, B2) of the target data. create. Of course, it is preferable that the shooting condition of the target color chart 24 is matched with the shooting condition of the entire color chart 23 as described above.

  Next, the image conversion unit 16 performs color conversion on the image data of the subject 104 input in step S13 using the created color conversion table (S20). Since the color conversion table is created as 3DLUT, if there is no grid point corresponding to the input value (image data of the subject 104), the output value (device RGB value of the printer 103) is calculated by interpolation such as tetrahedral interpolation. Ask for. Then, the color-converted image data (device RGB value) of the subject 104 is output to the printer 103, and the printer 103 prints the image of the subject 104 (S21).

[Create target color gamut]
FIG. 4 shows an example of the printer color gamut. The printer color gamut shown in FIG. 4 is based on the sRGB average value acquired from the image data obtained by photographing the entire color chart 23, and the grid points corresponding to the entire color chart 23 are arranged at positions corresponding to the sRGB average value of the color chart. Shows the state.

  FIG. 5 shows an example of the printer color gamut and the subject color gamut. The printer color gamut is the same as in FIG. 4, but the subject color gamut is a mapping of the sRGB values of image data obtained by photographing the subject 104. Referring to FIG. 5, the subject color gamut is narrower than the printer color gamut, in other words, the color of the subject 104 is distributed in a partial region of the printer color gamut. Therefore, it can be said that creating a color conversion table according to the subject color gamut is very effective in improving the color reproduction accuracy of the subject 104.

  FIG. 6 shows an example of the target color gamut. FIG. 6 (a) shows a target color gamut created from a subject color gamut using a convex hull. FIG. 6B shows a color gamut created using general color gamut mapping, and tends to be wider than the target color gamut. In this way, by creating the target color gamut, it is possible to create a color gamut optimal for reproducing the subject 104.

  Further, it is desirable that the method of cutting the grid inside the color gamut (arrangement of the grid points in the color conversion table) is matched to the density of the pixel values mapped from the image data of the subject 104, for example. That is, more lattice points are arranged in a region where the density of mapped pixel values is high, and the number of lattice points arranged in a region where density is low is relatively reduced.

  The target color gamut creation process (S15) by the color gamut creating unit 13 will be described with reference to the flowchart of FIG.

The color gamut creating unit 13 creates a target color gamut from the subject color gamut using the convex hull (S31), and arranges the lattice points substantially uniformly in the target color gamut (S32). The number of grid points arranged in the target color gamut may be the same as the number of color charts 23 (for example, 9 ³ = 729), but considering that the target color gamut is narrower than the printer color gamut, for example, 7 ³ It may be reduced to = 343.

Next, the color gamut creating unit 13 creates a tetrahedron obtained by dividing a unit cube formed by four adjacent lattice points arranged in the target color gamut (S33), and the pixel values mapped in each tetrahedron Count the number (S34). The inside / outside determination as to whether or not the mapped pixel value exists in the tetrahedron is performed using the following equation.
↑ p4 = s ↑ p1 + t ↑ p2 + u ↑ p3;
if ((s + t + u) ≤ 1 && s ≥ 0 && t ≥ 0 && u ≥ 0)
Pixel value P4 exists in tetrahedron P0P1P2P3;… (1)
Where P4 is the mapped pixel value,
P0, P1, P2, and P3 are the color values of the vertices of the tetrahedron,
↑ p1 is a vector connecting P0 and P1,
↑ p2 is a vector connecting P0 and P2,
↑ p3 is a vector connecting P0 and P3,
↑ p4 is a vector connecting P0 and P4,
s, t, u are linear combination coefficients,
&& is a logical AND operator.

  If the tetrahedron including the pixel value is obtained for all the mapped pixel values by the above-described tetrahedron creation and inside / outside determination, the number of pixel values existing in each tetrahedron can be obtained.

  Next, the color gamut creating unit 13 selects one of the created tetrahedrons (S35), and determines whether or not there is mapping concentration in the selected tetrahedron (hereinafter referred to as the target tetrahedron) (S36). ). For example, the concentration determination method calculates the ratio of the count value of the pixel value existing in the target tetrahedron to the number of pixels (or the number of pixels after sub-sampling) of the image data of the subject 104, and the ratio is a predetermined ratio. What is necessary is just to determine that there is concentration when exceeding.

  When it is determined that the mapping is concentrated in the attention tetrahedron, the color gamut creation unit 13 moves the vertex (grid point) of the attention tetrahedron (S37). The grid point is moved by a method such as moving the grid point closest to the center (or centroid) of the distribution of pixel values mapped in the tetrahedron to the center (or centroid). When concentration is detected in a plurality of tetrahedrons that share lattice points, the lattice points that have already been moved in one tetrahedron do not move, and other lattice points move other lattice points, etc. Take action.

  Next, the color gamut creating unit 13 determines whether or not concentration determination has been performed for all tetrahedrons (S38), and if there is an undetermined tetrahedron, the process returns to step S35, and the undetermined tetrahedron is determined. Select the body as the tetrahedron of interest. If there is no undetermined tetrahedron, the target color gamut creation process is terminated.

[Create target color chart]
The target color chart creation processing (S16) by the target color chart creation section 14b will be described with reference to the flowchart of FIG.

  The target color chart creation unit 14b creates a device RGB → sRGB table indicating the relationship from the device RGB value to the sRGB value based on the entire area data which is the device RGB value and the sRGB value indicating the printer color gamut acquired in step S12. (S41).

  Next, the target color chart creating unit 14b selects a grid point in the target color gamut (S42), and displays the color value (sRGB value) of the selected grid point (hereinafter referred to as the target grid point) in the device RGB → sRGB table. Reverse interpolation is performed as an input value (S43). Then, the device RGB value calculated by the reverse interpolation operation is assigned to the target data of the target color chart 24 (S44).

  Next, the target color chart creating unit 14b determines whether or not target data has been created for all grid points (S45). If there is a grid point for which target data has not been created, the process returns to step S42, and a tetrahedron for which target data has not been created is selected as the target grid point. If there is no grid point for which the target data has not been created, the creation process of the target color chart 24 is terminated.

[Modification]
In the above, the example in which the sRGB value (or AdobeRGB value) of the captured image data is used as it is when the color gamut creating unit 13 creates the target color gamut has been described, but another color coordinate system may be used. . For example, photographing may be performed in the sRGB mode that is the normal mode of the camera 102, the photographed image data may be converted into CIELAB by the following conversion formula, and each process may be performed on CIELAB. Note that description will be made assuming that each RGB color has 8 bits.

● sRGB → CIEXYZ conversion formula
The conversion from sRGB to CIEXYZ is performed by the following equation.
R '= R / 255;
G '= G / 255;
B '= B / 255;
if (R '≤ 0.04045)
R "= R '/ 12.92;
else
R "= {(R '+ 0.055) /1.055} ^γ ;
if (G '≤ 0.04045)
G "= G '/ 12.92;
else
G "= {(G '+ 0.055) /1.055} ^γ ;
if (B '≤ 0.04045)
B "= B '/ 12.92;
else
B "= {(B '+ 0.055) /1.055} ^γ ;
X = 0.4124 x R "+ 0.3576 x G" + 0.1805 x B ";
Y = 0.2126 x R "+ 0.7152 x G" + 0.0722 x B ";
Z = 0.0193 x R "+ 0.1192 x G" + 0.9505 x B ";… (1)
Where γ = 2.4.

● CIEXYZ → CIELAB conversion formula
Conversion from CIEXYZ to CIELAB is performed by the following equation.
L * = 116.0 × f (Y / Yn)-16;
a * = 500 × {f (X / Xn)-f (Y / Yn)};
b * = 200 × {f (Y / Yn)-f (Z / Zn)};… (2)
Where XnYnZn is the XYZ value of the white point of D50 (95.045, 100.000, 108.892),
t = X / Xn or Y / Yn or Z / Zn,
if (t> 0.008856) f (t) = t ^1/3 ,
if (t ≦ 0.008856) f (t) = 7.787 × t + 16.0 / 116.0.

  When photographing a subject such as a cultural property to create a duplicate, it is necessary to reproduce subtle gradation changes. Regardless of the image to be printed, a color conversion table created from the entire printer color gamut can be used to reproduce a wide color gamut. In many cases, only part of the printer color gamut is used.

  Using the color conversion table for the color gamut (subject color gamut) corresponding to the colors included in the image to be printed improves the reproducibility of the gradation, and the subtleties required when creating duplicates such as cultural assets. It is possible to reproduce various gradation changes.

  In this way, by extracting the subject's color gamut, creating the target color gamut including the subject color gamut, and creating the color conversion table corresponding to the target color gamut, the accuracy of the subject's color and gradation changes can be reproduced. Can be improved. Further, it is not necessary to increase the number of color charts to be measured when creating the color conversion table, and the color conversion table for the subject color gamut can be efficiently created.

  The image processing according to the second embodiment of the present invention will be described below. Note that the same reference numerals in the second embodiment denote the same parts as in the first embodiment, and a detailed description thereof will be omitted.

  In the first embodiment, an example in which the camera 102 is used to extract and create a color gamut has been described. However, a measurement device such as a spectral radiance meter or a spectrophotometer can also be used to extract or create a color gamut.

  A block diagram of FIG. 9 shows a configuration example of the image processing apparatus 101 of the second embodiment. The difference from the configuration of the first embodiment is that a measuring device 105 is connected to the input unit 21 for measuring the color chart and a measurement value acquiring unit 17 is added.

  Image processing by the image processing apparatus 101 according to the second embodiment will be described with reference to the flowcharts of FIGS. 10A and 10B.

  Similar to the first embodiment, after the printing of the entire color chart 23 (S11) and the calculation of the RGB average value indicating the printer color gamut (S12), the measurement value acquisition unit 17 receives the entire area color chart from the measuring device 105. Input the measured value of 23 (S101). Then, an R1G1B1 → Lab table showing the relationship from the RGB average values (R1, G1, B1) to the measured values (L, a, b) is created (S102).

  Next, after the input of the image data of the subject 104 (S13) and the extraction of the subject color gamut (S14), as in the first embodiment, the color gamut creation unit 13 uses the R1G1B1 → Lab table, The sRGB value of the subject color gamut is converted into an Lab value (S103). Then, using the convex hull, a target color gamut including the pixel value of the subject 104 mapped in the Lab space is created (S104). The details of creating the target color gamut are the same as those in FIG.

  Next, the target color chart creating unit 14b performs device RGB indicating the relationship from the device RGB value to the Lab value based on the entire area data (device RGB value) and the measurement value (Lab value) of the measuring device 105 indicating the printer color gamut. → A Lab table is created (S105). Similarly to steps S42 to S45 in FIG. 8, the target color chart 24 of the target color chart 24 is subjected to reverse interpolation using the color value (Lab value) of the grid point of the target color gamut as the input value of the device RGB → Lab table. Target data is calculated (S106).

  Although not shown in FIG. 10, the processing of steps S17 to S21 in the first embodiment shown in FIG. 3B is thereafter performed. That is, printing of the target color chart 24 (S17), calculation of the RGB average value of the image data of the target color chart 24 (S18), creation of a color conversion table (S19), color conversion of the image data of the subject 104 (S20), The image of the subject 104 is printed (S21).

  In this way, the R1G1B1 → Lab table is created from the captured image data of the entire area color chart 23 and the measurement result, and the color of the subject 104 is converted into the Lab value using the R1G1B1 → Lab table, and the target color gamut in the Lab space. Create As a result, a target color gamut that is closer to the color observed by a human can be acquired, and the reproduction accuracy of the subject color and gradation change can be improved.

  Hereinafter, image processing according to the third embodiment of the present invention will be described. Note that the same reference numerals in the third embodiment denote the same parts as in the first and second embodiments, and a detailed description thereof will be omitted.

  In the first and second embodiments, the printer 103 is taken as an example of the image output device, and the example in which the image of the subject 104 is printed by the printer 103 has been described. An image of the subject 104 can be displayed on the monitor using a monitor as the image output device.

  A block diagram of FIG. 11 shows an example of the configuration of the image processing apparatus 101 of the third embodiment. The difference from the configuration of the first embodiment is that a monitor 106 is connected instead of the printer 103 as an output destination of the image of the subject 104, and the output unit 22 is a video interface such as HDMI (registered trademark) or DisplayPort (trademark). The output unit 25 is changed.

  Image processing by the image processing apparatus 101 according to the third embodiment will be described with reference to the flowcharts of FIGS. 12A and 12B.

  When the photographing of the subject 104 by the camera 102 is completed, the subject color gamut extraction unit 12 inputs the image data of the subject 104 from the camera 102 (S51), and extracts the subject color gamut (S52). The extraction of the subject color gamut may be performed by mapping the pixel values of all the pixels or mapping the pixel values of the subsampled image data as in the first embodiment.

  Next, the global color chart creation unit 14a outputs the data (global data) of the global color chart 26 to the monitor 106 via the output unit 25, and displays the global color chart 23 on the monitor 106 (S53). The monitor 106 is a monitor used for displaying an image of the subject 104. Note that the whole area data is a device RGB value of the monitor 106.

The monitor 106 to which the entire area data is input displays a color chart of, for example, 9 ³ = 729 colors corresponding to the data of each grid point by the entire area data. With this color chart, the color reproduction characteristics (color reproduction range) of the monitor 106 can be expressed.

  When the photographing of the color chart 26 by the camera 102 is completed, the output color gamut acquisition unit 11 inputs the image data of the color chart 26 from the camera 102, and the RGB average of the image data of each color chart is input as in the first embodiment. A value is calculated (S54). As in the first embodiment, it is preferable that the shooting conditions of the subject 104 and the shooting conditions of the entire color chart 26 are the same.

  Next, the output color gamut acquisition unit 11 (or the subject color gamut extraction unit 12) compares the RGB average value representing the monitor color gamut with the subject color gamut to determine whether the subject color gamut is included in the monitor color gamut. Is determined (S55). If the subject color gamut is not included in the monitor color gamut, the output color gamut acquisition unit 11 controls the output characteristics of the monitor 106 via the output unit 25 (S56), and the process returns to step S54. The control of the output characteristics may be an adjustment that increases the dynamic range of the brightness of the monitor 106, such as increasing the brightness of the monitor 106 by a predetermined amount.

  When the process returns to step S54, a message such as “Please re-shoot the entire color chart” is displayed on the monitor 106. Further, the user may adjust the brightness of the monitor 106 in accordance with a message such as “Please increase the brightness of the monitor and re-shoot the entire color chart” displayed on the monitor 106.

  When the output color gamut acquisition unit 11 determines that the subject color gamut is included in the monitor color gamut, the color gamut creation unit 13 creates a target color gamut from the subject color gamut using the convex hull (S57). ). The details of creating the target color gamut are the same as those in FIG.

  Next, the target color chart creation unit 14b creates data (target data) of the target color chart 27 from the RGB average value indicating the monitor color gamut calculated by the output color gamut acquisition unit 11 and the target color gamut (S58). Then, the target data is output to the monitor 106, and the target color chart 27 is displayed on the monitor 106 (S59). The target data is a device RGB value of the monitor 106. The details of creating the target color chart are the same as those in FIG.

  When the shooting of the target color chart 27 by the camera 102 is completed, the conversion table creation unit 15 inputs the image data of the target color chart 27 from the camera 102, and the RGB average value of the image data of each color chart as in the first embodiment. Is calculated (S60). Then, a color conversion table is created from the RGB average value of the target color chart 27 and the target data (S61). That is, the conversion table creation unit 15 converts the average value (R3, G3, B3) of the sRGB values acquired from the target color chart 27 into the device RGB values (R2, G2, B2) of the target data. create. Needless to say, it is preferable that the shooting conditions of the target color chart 27 match the shooting conditions of the entire color chart 26 as described above.

  Next, the image conversion unit 16 performs color conversion on the image data of the subject 104 input in step S51 using the created color conversion table (S62). Since the color conversion table is created as 3DLUT, if there is no grid point corresponding to the input value (image data of the subject 104), the output value (device RGB value of the monitor 106) is obtained by interpolation such as tetrahedral interpolation. Ask for. Then, the color-converted image data (device RGB value) of the subject 104 is output to the monitor 106, and the image of the subject 104 is displayed on the monitor 106 (S63).

  When displaying the image of the subject 104 on the monitor 106, as in the first embodiment, the subject color gamut is extracted, the target color gamut including the subject color gamut is created, and the color conversion table corresponding to the target color gamut is created. By doing so, it is possible to improve the reproduction accuracy of the subject color and gradation change. Further, it is not necessary to increase the number of color charts to be measured when creating the color conversion table, and the color conversion table for the subject color gamut can be efficiently created.

  The combination of Example 2 and 3 is also possible, and by using the measurement value of the measuring instrument 105, the target color gamut closer to the color observed by human beings is acquired, and the reproduction accuracy of the subject color and gradation change is improved. Can be improved.

  In each of the above-described embodiments, an example in which an RGB space or a CIELAB space is used as a color space has been described. However, other color spaces (for example, a CIEXYZ space, a CIELUV space, a CIECAM02 space, etc.) can also be used. Data exchange between the image processing apparatus 101 and the camera 102, printer 103, measuring instrument 105, or monitor 106 may be performed via a recording medium such as a USB memory.

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

  11… Output color gamut acquisition unit, 12… Subject color gamut extraction unit, 13… Color gamut creation unit, 14… Color chart creation unit, 15… Conversion table creation unit

Claims (15)

First color chart creating means for outputting data of a global color chart corresponding to the entire range of signal values of the output device to the output device and causing the output device to output the global color chart;
Obtaining means for obtaining data indicating a color gamut of the output device from image data obtained by photographing the entire color chart by a photographing device;
Extracting means for extracting a subject color gamut corresponding to a color included in the subject from image data obtained by photographing the subject by the photographing device;
Color gamut creating means for creating a target color gamut from the subject color gamut;
Create target color chart data based on the data indicating the color gamut of the output device and the target color gamut, output the target color chart data to the output device, and output the target color chart to the output device A second color chart creation means
An image processing apparatus comprising: image data obtained by photographing the target color chart by the photographing apparatus; and table creating means for creating a color conversion table from the target color chart data.   2. The image processing apparatus according to claim 1, further comprising conversion means for color-converting image data obtained by photographing the subject using the color conversion table and outputting the color-converted image data to the output device.   3. The image processing apparatus according to claim 1, wherein the color gamut creating unit creates the target color gamut from the subject color gamut using a convex hull.   4. The image processing apparatus according to claim 1, wherein the extraction unit maps the pixel value of the image data of the subject to a color space and extracts the subject color gamut.   4. The extraction unit according to claim 1, wherein the extraction unit subsamples the image data of the subject, maps a pixel value of the image data after the subsampling to a color space, and extracts the subject color gamut. An image processing apparatus according to one item.   5. The color gamut creating unit arranges grid points substantially evenly in the target color gamut, and changes the arrangement of the grid points according to the density of pixel values mapped in the color space. 5. The image processing apparatus described in 5.   The second color chart creating means creates a table indicating a relationship from the data of the entire color chart to the data indicating the color gamut of the output device, and displays the color values of the grid points of the target color gamut. 7. The image processing apparatus according to claim 1, wherein target color chart data corresponding to the grid points is calculated by an interpolation calculation using the input value of.   Furthermore, it has a measurement value acquisition means for acquiring a measurement value obtained by measuring the color gamut of the entire area by a measurement apparatus and creating a first table indicating a relationship from the data indicating the color gamut of the output device to the measurement value. The image processing apparatus according to claim 1. The color gamut creation means converts the pixel value of the subject color gamut into the color space of the measurement value using the first table, creates the target color gamut in the color space of the measurement value,
The second color chart creating means creates a second table indicating a relationship from the data of the entire color chart to the measurement value, and displays the color values of the grid points of the target color gamut in the second table. 9. The image processing apparatus according to claim 8, wherein data of a target color chart corresponding to the grid point is calculated by an interpolation calculation using an input value of.   10. The image processing apparatus according to claim 1, wherein the output device is a printer.   10. The image processing apparatus according to claim 1, wherein the output device is a monitor.   Further, it is determined whether or not the subject color gamut is included in the color gamut of the output device, and if the subject color gamut is not included in the color gamut of the output device, the output characteristics of the monitor are controlled. 12. The image processing apparatus according to claim 11, further comprising means. Output the data of the entire color chart corresponding to the entire range of the signal value of the output device to the output device, let the output device output the global color chart,
Obtaining data indicating the color gamut of the output device from image data obtained by photographing the entire color chart by a photographing device;
Extracting a subject color gamut corresponding to a color included in the subject from image data obtained by photographing the subject with the photographing device;
Create a target color gamut from the subject color gamut,
Create target color chart data based on the data indicating the color gamut of the output device and the target color gamut, output the target color chart data to the output device, and output the target color chart to the output device Let
An image processing method for creating a color conversion table from image data obtained by photographing the target color chart by the photographing apparatus and data of the target color chart.   13. A program for causing a computer to function as each unit of the image processing apparatus according to claim 1.   15. A computer-readable recording medium on which the program according to claim 14 is recorded.