JP2006197366A - Image processing unit and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technique for determining an optimum color space, for performing color gamut compression in a color space, and for preventing saturation from extremely dropping, or gradient from deteriorating in color matching between imaging apparatuses having different color reproduction ranges in consideration of a difference in color gamut shapes or gray lines between the imaging apparatuses. <P>SOLUTION: A color space to be used when second data are subjected to the color gamut compression to data of the color in the color gamut of a printer is determined, based on first data showing a color in the color gamut of the printer and second data showing a color in the color gamut of a monitor (S207). The second data is subjected to the color gamut compression to the data of the color in the color gamut of the printer in the determined color space (S208). <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a technique for gamut compressing a color within a certain color reproduction range to a color within a different color reproduction range.

  Generally, the color gamut shape of a device that handles a color image varies from device to device. For example, since the monitor performs color reproduction by additively mixing the colors of the three primary colors of red (R), green (G), and blue (B), the monitor color gamut depends on the type of phosphor used. Depends on.

  On the other hand, the color gamut of the printer differs depending not only on the ink used but also on the type of paper. FIG. 4 is a diagram showing the color gamut of the sRGB monitor and the color gamut of the inkjet printer. The colors in the color space shown in the figure and the colors in the CIELAB color space have a relationship represented by the following equations (1) and (2).

L * = L * (1)
C * = ((a *) ² + (b *) ² ) ^1/2 (2)
As described above, when one color gamut is smaller than the other color gamut, it is impossible to accurately reproduce one color information depending on an image. For example, when an image on a monitor is output by a printer, the color gamut of the printer is smaller than that of the monitor, so colors outside the printer gamut cannot be reproduced as they are. Therefore, in such a case, it is necessary to perform color processing that brings out the color gamut into the color gamut while keeping the original image information as much as possible. In this way, pushing a color that cannot be physically reproduced into the color gamut by some processing is generally called color gamut compression.
JP 2000-253267 A

  For example, when color reproduction from a monitor to a printer is considered, a color gamut compression algorithm as shown in FIGS. 12A, 12B, and 12C has been proposed. FIG. 12 is a diagram for explaining color gamut compression.

  However, as shown in FIG. 4, in the color gamut of the ink jet printer, the saturation peak is shifted in the lightness direction in the low lightness direction as compared with the monitor color gamut. In other words, the color gamut of the monitor and the color gamut of the ink jet printer are not similar to each other, and the simple color gamut compression algorithm as shown in FIGS. In some cases, the image quality is greatly deteriorated, such as a decrease in image quality or deterioration in gradation.

  Thus, even when a simple compression algorithm as shown in FIG. 12 is used, in order to perform color gamut compression without causing a large deterioration in image quality, both color gamut shapes are more similar. It is necessary to perform color gamut compression in the color space.

  On the other hand, as shown in FIG. 19, it is also known that when color gamut compression is performed, the color of one gray line and the other gray line are different. It is known that this gray line color difference causes not only a reduction in gray reproduction but also a reduction in reproducibility of the entire low-saturation part by performing color gamut compression.

  On the other hand, in the case of the hue shown in FIG. 4, the color gamut of the inkjet printer has a saturation peak that is shifted in the lightness direction to the low lightness direction compared to the monitor color gamut, so color reproduction from the monitor to the printer is considered. In this case, the color reproducibility in the high brightness and high saturation regions is not good.

  In general, in color gamut compression, a high chroma color that cannot be reproduced in the color gamut compression destination is pushed into the color gamut compression destination color among the color gamut compression source colors, resulting in a decrease in reproducibility in the high chroma portion.

  The present invention has been made in view of such problems, and in consideration of differences in color gamut shapes between devices and differences in gray lines, in color matching between image devices having different color reproduction ranges, It is an object of the present invention to provide a technique for discriminating an optimal color space, performing color gamut compression in the color space, and preventing an extreme decrease in saturation and gradation.

  In addition, in consideration of differences in the color gamut shape between devices, color matching between image devices with different color gamuts in a color space where the gray line of one device is closer to the gray line of the other device Another object is to improve the gray reproduction and the color reproducibility of the low saturation part by performing the area compression.

  In order to achieve the object of the present invention, for example, an image processing apparatus of the present invention comprises the following arrangement.

That is, using the first color gamut data indicating the first color gamut and the second color gamut data indicating the second color gamut different from the first color gamut, Determining means for determining a color space to be used when gamut mapping color data to color data in the first gamut;
In the color space determined by the determining means, the color gamut mapping means for gamut mapping the color data in the second color gamut to the color data in the first color gamut is provided.

  In order to achieve the object of the present invention, for example, an image processing method of the present invention comprises the following arrangement.

That is, using the first color gamut data indicating the first color gamut and the second color gamut data indicating the second color gamut wider than the first color gamut, Determining a color space to be used when gamut mapping the color data to the color data in the first gamut;
A color gamut mapping step of mapping color data in the second color gamut to color data in the first color gamut in the color space determined in the determination step.

  With the configuration of the present invention, in consideration of the difference in color gamut shape and gray line between devices, color matching between image devices with different color reproduction ranges is performed, and the optimum color space is determined. Color gamut compression can be performed to prevent extreme reduction in saturation and gradation.

  In addition, with the configuration of the present invention, in consideration of the difference in color gamut shape between devices, in color matching between image devices having different color reproduction ranges, the gray line of one device and the gray line of the other device are By performing color gamut compression in a closer color space, it is possible to improve gray reproduction and color reproducibility of the low saturation portion.

  Hereinafter, the present invention will be described in detail according to preferred embodiments with reference to the accompanying drawings.

[First Embodiment]
<Image processing device and its peripheral equipment>
FIG. 1 is a block diagram illustrating a functional configuration of the image processing apparatus according to the present embodiment. As shown in the figure, an image display device 2 and an image output device 3 are connected to the image processing device 1. As the image display device 2, a CRT, a liquid crystal screen, or the like can be applied. As the image output apparatus 3, an apparatus such as a printer or a copying machine that records images or characters on a recording medium such as paper or OHP is applicable.

  Hereinafter, each part which comprises the image processing apparatus 1 is demonstrated. An image display unit 4 generates an image signal to be output to the image display device 2. An image processing unit 5 performs a gradation conversion process for outputting the color displayed on the image display device 2 to the image output device 3. Reference numeral 6 denotes an optimum color space discriminating unit that discriminates an optimum color space for color gamut compression (gamut mapping). A color gamut shape evaluation unit 7 calculates an evaluation value used by the optimum color space determination unit 6 to determine the color space. A gray evaluation unit 8 calculates an evaluation value used by the optimum color space determination unit 6 to determine a color space. A color gamut compression processing unit 9 performs color gamut compression on the L * -C * plane in the CIELAB color space.

  A color matching LUT creation unit 10 creates a color matching LUT between colors displayed on the image display device 2 and colors output from the image output device 3. An image output unit 11 generates a signal to be output to the image output device 3. 12 is a data buffer for temporarily storing data for data processing, 13 is a monitor profile storage unit for storing a monitor profile of the image display device 2 and the like, and 14 is a printer profile for the image output device 3 and the like. A printer profile storage unit 15 is a UI (user interface) unit for a user to input various operations using the image processing apparatus 1. Reference numeral 16 denotes a stage before outputting an image signal to the image output apparatus 3, and a color conversion processing unit that performs color conversion processing on the image signal. Reference numeral 17 denotes an operation performed by the user for setting color reproduction in the image processing apparatus 1. A color reproduction setting unit.

  FIG. 10 is a block diagram showing a basic configuration of the image processing apparatus 1. In the present embodiment, a computer such as a general PC (personal computer) or WS (workstation) is used as the image processing apparatus 1.

  In the figure, reference numeral 1001 denotes a CPU, which controls the entire computer using programs and data stored in a RAM 1002 and a ROM 1003 and executes each process described below performed by the image processing apparatus 1.

  A RAM 1002 includes an area for temporarily storing programs and data loaded from the external storage device 1005 and a work area used when the CPU 1001 executes various processes.

  Reference numeral 1003 denotes a ROM which stores setting data and a boot program for the computer.

  Reference numeral 1004 denotes an operation unit, which includes a mouse and a keyboard, and can input various instructions to the CPU 1001. In FIG. 1, the UI unit 15 and the color reproduction setting unit 17 are one function of the operation unit 1004.

  Reference numeral 1005 denotes an external storage device, which is a large-capacity information storage device such as a hard disk drive device, which is a program or data for causing the CPU 1001 to execute an OS (Operating System) or each process described later performed by the image processing apparatus 1. Are stored in the RAM 1002 under the control of the CPU 1001 and are processed by the CPU 1001.

  Reference numeral 1006 denotes an I / F that functions as an interface for connecting the image display device 2 to the computer.

  Reference numeral 1007 denotes an I / F that functions as an interface for connecting the image output apparatus 3 to the computer.

  Reference numeral 1008 denotes a bus connecting the above-described units.

  Note that, as described above, a general computer is applied as the image processing apparatus 1 in the present embodiment. However, the present invention is not limited to this. For example, each unit illustrated in FIG. 1 is configured with dedicated hardware. Also good.

<Overall processing>
Next, color gamut compression processing performed by the image processing apparatus 1 will be described with reference to FIG. Note that programs and data for causing the CPU 1001 to execute the processing according to the flowchart of FIG. Can be executed.

  FIG. 5 is a diagram showing a display example of a GUI (Graphical User Interface) displayed on the display screen of the image display device 2. When the user operates the operation unit 1004 and inputs various operation instructions using the GUI, various setting instructions to be described later can be input. An instruction to the CPU 1001 for the color gamut compression processing described below is made by operating the GUI shown in FIG.

  First, the GUI in FIG. 5 will be described. When the user operates the pull-down 502 or 503 by operating the operation unit 1004 (for example, by operating the mouse to move the mouse cursor to the pull-down menu 502 or 503 and clicking there), the output device and the output paper are set. be able to. When the “automatic” button is selected in the area 504 for color adjustment and the LUT creation button 512 is instructed, processing according to the flowchart shown in FIG. 2 is started.

  When the “manual” button is selected in the area 504, the setting button 506 is enabled (can be designated), and whether gray reproducibility is emphasized, color reproducibility is prioritized, or each emphasis level is weighted. It can be set by three buttons in the area 505 whether to manually set the value. In order to emphasize gray reproducibility, the “gray reproducibility emphasis” button is designated. In order to emphasize color reproducibility, the “color reproducibility emphasis” button is designated. Further, when the user wants to manually set the level of importance of gray reproducibility and color reproducibility, a “manual adjustment” button is instructed.

  Here, when the “manual adjustment” button is instructed and the setting button 508 is instructed, the slider bar 510 in the area 509 can be moved to the left and right, so gray reproducibility is more important than color reproducibility. If it is desired to move the slider bar 510 to the left side, the slider bar 510 may be moved to the right side when the color reproducibility is more important than gray can be reproduced. When the slider bar 510 is moved to the leftmost side, it is the same as when the “gray reproducibility emphasis” button is instructed. When the slider bar 510 is moved to the rightmost side, the “color reproducibility emphasis” button is displayed. Is the same as when

  When the “OK” button 507 is instructed after the movement of the slider bar 510 is finished, and the LUT creation button 512 is instructed, the processing according to the flowchart of FIG. 2 is started.

  When the LUT creation button 512 is instructed, the CPU 1001 first selects an output device (referred to as a printer here) set by the pull-down menus 502 and 503 and a profile Pon (hereinafter referred to as a printer profile) corresponding to the output paper. The data is loaded from the external storage device 205 to the RAM 1002 (step S201). In this embodiment, the printer profile Pon corresponds to the profile of the image output apparatus 3.

  The printer profile Pon includes data indicating the relationship between the digital data RGB sent to the image output device 3 and the colorimetric data L * a * b * resulting from the output from the image output device 3 based on the digital data RGB. ing. Specifically, L * a * b * data (Lab value data) is included for each of 9 levels of RGB data (total 729 colors). This colorimetric data is data indicating the characteristics of the image output device 3, and the gradation characteristics and color gamut can be obtained from the colorimetric data.

  Next, the monitor profile Mon is loaded from the external storage device 205 to the RAM 1002 (step S202). In the present embodiment, this monitor profile corresponds to the profile of the image display device 2. This monitor profile includes CIELAB colorimetric data for nine levels of RGB (total 729 colors), and table data of CIELAB data for RGB values is stored.

  Next, the color reproduction condition (matching method) set by the GUI is acquired (step S203). Here, the color reproduction condition means a weight value for gray reproducibility and a weight value for color reproducibility, which are set as follows.

  That is, when the “automatic” button is designated in the area 504, the weight value for gray reproducibility and the weight value for color reproducibility are made the same. This is the same as when the previous slider bar 510 is moved to the center position.

  Further, when the “Manual” button is designated in the area 504 and the “Gray reproducibility priority” button is designated in the area 505, the weight value for gray reproducibility and the weight value for color reproducibility are calculated. The ratio is 2: 1. Further, when a “manual” button is designated in the area 504 and a “color reproducibility priority” button is designated in the area 505, the weight value for gray reproducibility and the weight value for color reproducibility are calculated. The ratio is 1: 2. Further, when the “Manual” button is designated in the area 504 and the “Manual Adjustment” button is designated in the area 505, the ratio between the weight value for gray reproducibility and the weight value for color reproducibility is calculated. The ratio depends on the position of the slider bar 510.

  Returning to FIG. 2, next, it is evaluated whether or not the gray line in the color gamut of the color gamut compression source and the color gamut of the color gamut compression destination has close chromaticity on the hue plane. Is calculated (step S204). Details of the processing in step S204 will be described later.

  Next, it is evaluated whether or not the shape of the color gamut of the color gamut compression source and the shape of the color gamut of the color gamut compression destination are similar, and the evaluation value is calculated (step S205). Details of the processing in step S205 will be described later.

  Next, using the evaluation value (gray line evaluation value) calculated in step S204, the evaluation value (color gamut shape evaluation value) calculated in step S205, and the color reproduction condition (weight value) acquired in step S203, the user Calculates an evaluation value for determining an appropriate color space as a color space satisfying the color adjustment specified by (step S206). Specifically, the gray line evaluation value Eg_a after the weighting is added by adding the weight of the color reproduction condition acquired in step S203 to the gray line evaluation value Eg and the color gamut shape evaluation value dk calculated for each color space, and after the weight addition. An overall evaluation value that is a product of the color gamut shape evaluation value dk_a is calculated. This comprehensive evaluation value is calculated in two color spaces, CIELAB and IPT.

  Next, among the total evaluation values obtained for each color space, the color space having the smallest total evaluation value is set as a color space used in the color gamut compression processing described later (step S207). The gamut compression source color data is subjected to gamut compression that maintains the hue angle of the color space determined in step S207 and performs compression only in the lightness and saturation direction (step S208). As the color gamut compression method, for example, the conventional method described above as shown in FIGS. 12A, 12B, and 12C can be applied, but the method is not limited to this. The compression source color data here is color data in the color gamut of the image output device 3, and the compression destination color gamut indicates the color gamut of the image output device 3.

  Finally, the calculation result of the L * a * b * value after color gamut compression in step S209 for each of nine stages of RGB (729 colors) is created as table data (LUT) (step S209).

<Calculation of color gamut shape evaluation value>
FIG. 3 is a flowchart showing details of the processing in step S205. Hereinafter, the details of the processing in step S205, that is, whether the shape of the color gamut of the color gamut compression source and the shape of the color gamut of the color gamut compression destination are similar or not are evaluated, and the evaluation value is calculated. Processing to be performed will be described.

  First, the color gamut outermost contour data Po generated from the colorimetric data stored in the printer profile data Pon is extracted (step S301). Next, the color gamut outermost contour data Mo is extracted from the monitor profile data Mon (step S302). Next, by using the printer color gamut outermost data Po shown in the Lab color space and the monitor color gamut outermost data Mo shown in the Lab color space, the color gamut shape and color The degree of similarity with the shape of the color gamut of the gamut compression destination is evaluated, and the evaluation value in the Lab color space is calculated (step S303). Details of the processing in step S303 will be described later.

  Next, the printer color gamut outermost data Po is converted into the IPT color space (step S304). Here, a method for converting CIELAB data to the IPT color space will be briefly described with reference to FIG. FIG. 11 is a diagram showing formula groups used for converting the printer color gamut outermost contour data Po to the IPT color space.

  Convert CIELAB data to XYZ (D50) using the conversion formula described in Publication CIE No. 15.2 (1986) and JIS Z8729 (Color Display Method-L * a * b * Color System) To do. Further, the converted XYZ (D50) is converted into XYZ (D65) using the Bradford conversion formula. Next, using (Equation 11-1), it is converted into a cone response LMS, and after the gamma processing of (Equation 11-2), it is converted into the IPT color space by matrix transformation of (Equation 11-3). By using the above conversion formula, CIELAB data can be converted into IPT color space data. In the present embodiment, the IPT color space studied by RIT is used as the other color space, particularly in the color space rich in the linearity of the hue line. In addition, in the CIE (International Commission on Illumination) The color appearance models CAM97s and CAM02 under consideration may be used, or a plurality of them may be used simultaneously, and the present invention is not limited to this. Needless to say, it may be changed according to the required accuracy and purpose.

  Returning to FIG. 3, next, the monitor color gamut outermost data Mo is converted into the IPT color space by the same method (step S305).

  Next, using the monitor color gamut outermost data and the printer color gamut outermost data converted into the IPT color space in step S304 and step S305, the color gamut shape of the color gamut compression source and the color gamut of the color gamut compression destination The degree of similarity to the shape of the image is evaluated, and an evaluation value in the IPT color space is calculated (step S306). The process in step S306 is performed in the same manner as the process in step S303.

<Evaluation of color gamut shape>
FIG. 6 is a flowchart showing details of the processing in step S303. Hereinafter, the details of the processing in step S303, that is, the color gamut compression source color and the color gamut compression destination color using the printer color gamut outermost data Po and the monitor color gamut outermost data Mo. A process for evaluating the degree of similarity with the shape of the area and calculating the evaluation value will be described.

  First, the value held by the variable k used in the following process is initialized to 0 (step S601). Next, L * -C * plane data of the printer color gamut outermost data Po and the monitor color gamut outermost data Mo is acquired (step S602). Details of this processing will be described with reference to FIG. FIG. 7 is a diagram showing the printer color gamut outermost data Po and the monitor color gamut outermost data Mo on the CIELAB a * -b * plane.

  First, since the value held by the variable k is 0, at this time, L * -C * plane data of Po and Mo color gamuts are extracted at a hue angle of 0 ° (701 in FIG. 7). Next, since the value held by the variable k is incremented by 1, k = 1 is obtained. At this time, the L * -C * plane data of the Po and Mo color gamuts at a hue angle of 45 ° (702 in FIG. 7) are obtained. Extract. Thus, every time the value held by the variable k is incremented by 1, L * -C * plane data of 45 ° is acquired. In this embodiment, L * -C * plane data with a hue angle of 45 ° is acquired. However, the present invention is not limited to this.

  Next, the value held by the variable n used in the following processing is initialized to 0 (step S603). Next, the saturation ratio Cn between the monitor color gamut outermost data Po and the printer color gamut outermost data Mo is calculated (step S604). Details of this processing will be described in detail with reference to FIGS. 8 and 9 are diagrams for explaining the details of the processing in step S604.

  When the value held by the variable k is 0, the saturation ratio C0 is the intersection Mx between the line segment 801 and the monitor color gamut outermost contour, the intersection Px between the line segment 801 and the printer color gamut outermost contour, and the line segments 801 to 807. Can be obtained by the following equation using the position Lst of the rotation axis.

C0 = (Px−Lst) / (Mx−Lst) (3)
Then, the value held by the variable n is incremented by 1, and it is checked whether or not n <7 (step S605). If n <7, the process returns to step S604. Next, since k = 1, the saturation ratio C1 is the intersection Mx between the line segment 802 and the monitor color gamut outermost line, the line segment 802, and the printer color gamut maximum. Using the intersection point Px with the outline and the position Lst of the rotation axis of the line segment 801, it is obtained according to the above equation (3). Similarly, saturation ratios are obtained for the line segments 803, 804, 805, 806, and 807. Therefore, in the check process in step S605, C0 to C7 have already been obtained when n ≧ 7. FIG. 9 shows the intersection Mx, the intersection Px, and the position Lst when the value held by the variable k is a certain value.

  Returning to FIG. 6, when n ≧ 7, the process proceeds from step S605 to step S606, and the average deviation dk of the saturation ratio Cn at a certain hue angle is calculated (step S606). In order to calculate the average deviation dk, first, the average value of the saturation ratio Cn is calculated according to the following equation.

Mc = (C0 + C1 + C2 + C3 + C4 + C5 + C6 + C7) / 8 (4)
Thereafter, the average deviation dk is calculated according to the following equation.
An average value of the saturation ratio Cn is calculated.

dk = (| C0-Mc | + | C1-Mc | + | C2-Mc |
+ | C3-Mc | + | C4-Mc | + | C5-Mc |
+ | C6-Mc | + | C7-Mc |) / 8 (5)
In the present embodiment, the value held by the variable n is changed from 0 to 6, and as a result, the saturation ratio is obtained for each of the seven line segments. However, the number is not limited to this number.

  Returning to FIG. 6, next, the value held by the variable k is incremented by one, and as a result, it is checked whether or not k <8 (step S607). As a result of the check, if k <8, the process returns to step S602, and the subsequent processes are repeated.

  On the other hand, if k ≧ 8, the process proceeds from step S607 to step S608, an average value of average deviations in all hue angles is calculated, and the calculation result is used as an evaluation value for color gamut shape evaluation (step S608). . That is, the average deviation calculated when k = 0, the average deviation calculated when k = 1, and the average deviation calculated when k = 7 are obtained, and this is calculated as the color gamut shape evaluation. The evaluation value of

  In the present embodiment, the similarity evaluation of the color gamut shape is evaluated by taking the average deviation of the saturation ratio on the L * -C * plane. However, the present invention is not limited to this.

<Gray line evaluation value calculation>
FIG. 15 is a flowchart showing details of the process in step S204. Hereinafter, the details of the processing in step S204, that is, whether or not the gray line in the color gamut compression source color gamut and the color gamut compression destination color gamut have close chromaticity on the hue plane, A process for calculating the evaluation value will be described.

  First, gray line data Pgl is read from the printer profile Pon (step S1501). Here, the gray line data is color measurement data when the digital data RGB values are all the same, and in this embodiment, there are 9 levels of RGB (total 729 colors). It is included in the data Pon.

  Next, the read gray line data Pgl is converted into data in the IPT color space (step S1502). The technique for converting CIELAB data to the IPT color space is as described above.

  Next, the gray line data Mgl is loaded from the monitor profile Mon into the RAM 1002 (step S1503), and converted into data MGL in the IPT color space in the same manner (step S1504).

  Next, an evaluation value eg for evaluating the difference between the printer gray line data Pgl in the Lab color space and the monitor gray line data Mgl in the Lab color space is calculated (step S1506). Details of the evaluation value eg calculation process will be described with reference to FIGS.

  FIG. 13 is a diagram illustrating a hue plane (a * -b * plane) on the CIELAB color space. FIG. 14 is a diagram illustrating a calculation formula for the evaluation value eg.

The evaluation value eg for evaluating the gray line difference is an a * b * value when the digital data RGB values are the same as shown in (Equation 16-1) shown in FIG. 14 (the monitor gray line is a * _mi , b * _Mi and printer gray line take a difference of a * _pi and b * _pi ).

  Returning to FIG. 15, in step S1506, the difference between the monitor gray line data MGL in the IPT color space and the printer gray line data PGL in the IPT color space is obtained as an evaluation value EG. The method for calculating the evaluation value EG is the same as that in step S1505, and is omitted here.

  Therefore, in step S206, the evaluation value obtained in step S303 and the evaluation value eg obtained in step S1505 are respectively weighted (by the previously set weight value), and the product of the weighted results (comprehensive evaluation in the CIELAB color space). Value), the evaluation value obtained in step S306 and the evaluation value EG obtained in step S1506 are respectively weighted (with the previously set weight value), and the product of the weighted results (total in the IPT color space) In step S207, the color space having the smaller total evaluation value is determined as the color space used for color gamut compression.

  As described above, according to the present embodiment, in color matching between image devices having different color reproduction ranges, color gamut compression is performed in an optimal color space in consideration of differences in color gamut shapes and gray lines between devices. By doing so, it is possible to prevent extreme saturation and deterioration of gradation, reflect the user's intention in the color gamut compression method, and provide a user interface with a high degree of freedom in color gamut adjustment Can do.

  In the present embodiment, the number of grid points of the color matching LUT created in step S209 is set to 9, but the present invention is not limited to this, and it goes without saying that the number may be changed according to the accuracy and purpose to be obtained.

  The GUI used in this embodiment has the configuration shown in FIG. 5, but is not limited to such a configuration. That is, a GUI that allows the user to select a menu format may be used. Also, a GUI that directly inputs a keyword may be used. In other words, any configuration that allows the user's desired settings to be made.

  In this embodiment, the gray line evaluation value is obtained regardless of the set weighting. However, for example, when the OK button 507 and the LUT creation button 512 are instructed after the slider bar 510 is moved to the right end, the gray reproducibility is improved. Since the weight value is 0, even if the gray line evaluation value is obtained, it is not finally used. Therefore, in such a case, the gray line evaluation value calculation process may be omitted. Also, a check box for determining whether or not to calculate the gray line evaluation value may be provided in the GUI so that the user can select it.

[Second Embodiment]
FIG. 16 is a block diagram illustrating a functional configuration of the image processing apparatus according to the present embodiment. In this figure, the same parts as those in FIG. In the figure, reference numeral 1601 denotes an original color storage unit which stores data of an original color ORc which is a color displayed on the image display device 2. Specifically, the original color ORc is CIELAB data of 9 levels of RGB (total 729 colors), and is stored in the original color storage unit 1601 as table data of CIELAB data for RGB values. In the following description, points not particularly mentioned are the same as those in the first embodiment.

  Next, color gamut compression processing performed by the image processing apparatus 1 will be described with reference to FIG. 17 showing a flowchart of the processing. Note that programs and data for causing the CPU 1001 to execute the processing according to the flowchart of FIG. 10 are stored in the external storage device 1005, and by loading these into the RAM 1002, the CPU 1001 uses these to execute each processing described later. Can be executed.

  FIG. 20 is a diagram illustrating a display example of a GUI (graphical user interface) displayed on the display screen of the image display device 2. When the user operates the operation unit 1004 and inputs various operation instructions using the GUI, various setting instructions to be described later can be input.

  First, the GUI shown in FIG. When the user operates the operation unit 1004 to instruct the pulldown 2002 or 2003 (for example, by operating the mouse to move the mouse cursor to the pull-down menu 2002 or 2003 and clicking there), the user sets the output device or output paper. be able to. In addition, the user operates the operation unit 104 (for example, using a keyboard) and inputs a file name of an output file generated by the following processing in the area 2005. The user can select a color reproduction mode by instructing a pull-down menu in the area 2004.

  Then, when the profile creation button 2006 is instructed, processing according to the flowchart shown in FIG. 17 is started. That is, when the profile creation button 2006 is instructed, the CPU 1001 detects this and starts processing according to the flowchart of FIG. 17 described below based on the previously set contents.

  When the profile creation button 2006 is instructed and detected, the CPU 1001 first outputs a profile Pon (hereinafter referred to as a printer profile) corresponding to the output device (here, a printer) and output paper set by the pull-down menus 2002 and 2003. Is loaded from the external storage device 205 to the RAM 1002 (step S1701). In this embodiment, the printer profile Pon corresponds to the profile of the image output apparatus 3. This printer profile Pon is the same as that used in the first embodiment.

  Next, only the data on the gray line (gray line data) is extracted from the printer profile Pon and stored in a predetermined area on the RAM 1002 (step S1702). As described above, the gray line data is colorimetric data when the values of the digital data RGB are all equal. In this embodiment, as in the first embodiment, nine colors are included in the print profile data 729 colors. Includes gray line data.

  Next, by performing gray line evaluation between the image display device 2 and the image output device 3, a color space used in a color gamut compression process described later is determined (step S1703) and set (step S1704). Details of the processing in step S1703 will be described later.

  The color gamut compression source color data is subjected to color gamut compression that maintains the hue angle of the color space determined in step S1704 and performs compression only in the lightness and saturation direction (step S1705). As the color gamut compression method, for example, the conventional method described above as shown in FIGS. 12A, 12B, and 12C can be applied, but the method is not limited to this.

  Finally, the calculation result of the L * a * b * value after color gamut compression in step S1705 for each of nine stages of RGB (729 colors) is created as table data (LUT) (step S1706).

<Gray line evaluation value calculation>
FIG. 18 is a flowchart showing details of the processing in step S1703. Hereinafter, details of the processing in step S1703, that is, processing for discriminating a color space used in the color gamut compression processing by performing gray line evaluation between the image display device 2 and the image output device 3 will be described.

  First, gray line data Pgl is read from the printer profile Pon (step S1801).

  Next, the read gray line data Pgl is converted into data in the IPT color space (step S1802). The technique for converting CIELAB data to the IPT color space is as described above.

  Next, the gray line data Mgl is loaded from the original color ORc data into the RAM 1002 (step S1803), and similarly converted to data MGL in the IPT color space (step S1804).

  Next, an evaluation value eg for evaluating the difference between the printer gray line data Pgl and the monitor gray line data Mgl is calculated (step S1805). Details of the evaluation value eg calculation processing are the same as those in the first embodiment.

  Next, a difference between the gray line data MGL of the monitor after conversion into the IPT color space and the gray line data PGL of the printer after conversion into the IPT color space is obtained as an evaluation value EG (step S1806). Since the method for calculating the evaluation value EG is the same as that in step S1805, it is omitted here.

  Next, the evaluation value eg is compared with the evaluation value EG. When eg <EG, the CIELAB color space is determined as the color space used in the following color gamut compression, and when eg> EG, the IPT color is determined. The space is determined as a color space used in the following color gamut compression (step S1807).

  As described above, according to this embodiment, in consideration of the difference in color gamut shape between devices, in color matching between image devices having different color reproduction ranges, the gray line of one device and the gray line of the other device. By performing color gamut compression in a color space closer to the gray space, it is possible to improve gray reproduction and improve color reproducibility of the low saturation portion.

  In the present embodiment, the number of grid points of the color matching LUT created in step S1706 is set to 9. However, the present invention is not limited to this, and it is needless to say that the number may be changed according to the accuracy and purpose to be obtained.

  The GUI used in this embodiment has the configuration shown in FIG. 20, but is not limited to such a configuration. That is, a GUI that allows the user to select a menu format may be used. Also, a GUI that directly inputs a keyword may be used. In other words, any configuration that allows the user's desired settings to be made.

[Other Embodiments]
In the above embodiment, the Lab color space and the IPT color space are used as the color space, but other color spaces such as the Luv color space and the sRGB color space may be used. The number of color spaces to be evaluated is not limited to two, and may be three or more.

  In the above embodiment, the color gamut compression process has been described. However, any color gamut mapping process such as a color gamut expansion process can be applied.

  Also, an object of the present invention is to supply a recording medium (or storage medium) in which a program code of software that realizes the functions of the above-described embodiments is recorded to a system or apparatus, and a computer (or CPU or CPU) of the system or apparatus. Needless to say, this can also be achieved when the MPU) reads and executes the program code stored in the recording medium. In this case, the program code itself read from the recording medium realizes the functions of the above-described embodiment, and the recording medium on which the program code is recorded constitutes the present invention.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an operating system (OS) running on the computer based on the instruction of the program code. It goes without saying that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

  Furthermore, after the program code read from the recording medium is written into a memory provided in a function expansion card inserted into the computer or a function expansion unit connected to the computer, the function is based on the instruction of the program code. It goes without saying that the CPU or the like provided in the expansion card or the function expansion unit performs part or all of the actual processing and the functions of the above-described embodiments are realized by the processing.

  When the present invention is applied to the recording medium, program code corresponding to the flowchart described above is stored in the recording medium.

It is a block diagram which shows the function structure of the image processing apparatus which concerns on 1st Embodiment. 3 is a flowchart of color gamut compression processing performed by the image processing apparatus 1; It is a flowchart which shows the detail of the process in step S205. It is the figure which showed the color gamut of an sRGB monitor and the color gamut of an inkjet printer. 3 is a diagram showing a display example of a GUI (Graphical User Interface) displayed on the display screen of the image display device 2. FIG. It is a flowchart which shows the detail of the process in step S303. FIG. 6 is a diagram illustrating printer color gamut outermost data Po and monitor color gamut outermost data Mo on the a * -b * plane of CIELAB. It is a figure explaining the detail of the process in step S604. It is a figure explaining the detail of the process in step S604. 1 is a block diagram showing a basic configuration of an image processing apparatus 1. FIG. It is a figure which shows the formula group used in order to convert printer color gamut outermost data Po into IPT color space. It is a figure explaining color gamut compression. It is a figure which shows the hue plane (a * -b * plane) on CIELAB color space. It is a figure which shows the calculation formula of evaluation value eg. It is a flowchart which shows the detail of the process in step S204. It is a block diagram which shows the function structure of the image processing apparatus which concerns on 2nd Embodiment. 3 is a flowchart of color gamut compression processing performed by the image processing apparatus 1; It is a flowchart which shows the detail of the process in step S1703. It is a figure which shows two different color gamuts. 3 is a diagram showing a display example of a GUI (Graphical User Interface) displayed on the display screen of the image display device 2. FIG.

Claims (7)

Color data in the second color gamut using the first color gamut data indicating the first color gamut and the second color gamut data indicating the second color gamut different from the first color gamut. Determining means for determining a color space used when color gamut mapping to color data in the first color gamut;
An image processing apparatus comprising: a color gamut mapping unit configured to perform color gamut mapping of color data in the second color gamut to color data in the first color gamut in the color space determined by the determination unit. The determining means includes
Using the first color gamut data and the second color gamut data, the chromaticity in the hue plane between the gray line of the first color gamut and the gray line of the second color gamut is approximated. A first calculating means for determining the thickness;
Second calculation means for obtaining a similarity of the color gamut shape between the first color gamut and the second color gamut using the first color gamut data and the second color gamut data;
According to the calculation results by the first and second calculation means, a color space used when color gamut mapping of the color data in the second color gamut to the color data in the first color gamut is determined. The image processing apparatus according to claim 1. Furthermore,
With setting means to set the weight value for each of gray line reproducibility and color reproducibility,
The determination means weights each of the calculation result by the first calculation means and the calculation result by the second calculation means with a weight value set by the setting means, and calculates a product of each calculation result after weighting by 2 Each color space is obtained, and the color space having the smallest product value is determined as a color space used when the second data is color-gamut mapped to the color data in the first color gamut. The image processing apparatus according to claim 2.   The determination unit determines a color space used for color gamut mapping based on a gray line evaluation value based on a gray line of a first color gamut and a gray of the second color gamut. Item 6. The image processing apparatus according to Item 1. Colors in the second color gamut using the first color gamut data indicating the first color gamut and the second color gamut data indicating the second color gamut wider than the first color gamut. A determining step for determining a color space to be used when gamut mapping data to color data in the first gamut;
An image processing method comprising: a color gamut mapping step of mapping color data in the second color gamut to color data in the first color gamut in the color space determined in the determination step.   A program causing a computer to execute the image processing method according to claim 5.   A computer-readable storage medium storing the program according to claim 6.

Images