JP5116866B2 - Color processing apparatus, color processing method, and program - Google Patents

Description

  The present invention relates to a color processing apparatus and a color processing method, and more particularly to a color processing apparatus and a color processing method for creating a color conversion table by mapping between color gamuts.

  In recent years, there have been increasing opportunities to output images acquired by digital cameras, scanners, and the like using printers. Images acquired by these digital cameras and scanners are temporarily stored as RGB color space data of the input device. However, since this RGB color space depends on the device, it is converted into color space data such as the standard color space sRGB color space or AdobeRGB color space and stored. The color reproduction range (color gamut) of the sRGB color space is shown on the xy chromaticity diagram of FIG. In FIG. 22, a triangular area Rs indicated by a dotted line represents an sRGB color gamut. A horseshoe-shaped region Rv indicated by a solid line represents a human visible range, and a curved region Rp indicated by a broken line represents a color gamut of a general printer. As shown in FIG. 22, since the sRGB color gamut Rs and the printer color gamut Rp are different in color gamut, for example, when an sRGB image is output by a printer, the sRGB color gamut Rs is corrected to correct the difference in color gamut. It is necessary to perform processing for associating the color signal value with the color signal value of the printer. This association process is called color gamut mapping.

  Hereinafter, with reference to FIG. 23, color gamut mapping will be described using color conversion processing of an RGB image as an example. In the following description, sRGB is described as an example of the input color space. First, in step S1M, a perceptual color space value of the pixel value RGB of the sRGB image is calculated. Examples of the perceived color space value include CIELAB, CIEUV, and CIECAM02. In the following description, the color value Jab in the CIECAM02 color space is used as the perceptual color space value. Next, in step S2M, a conversion is performed on the color value Jab so that the color value Jab falls within the color gamut of the output device in the perceptual color space. The process of associating the input color value with the output color value in step S2M is generally called color gamut mapping. Finally, in step S3M, the mapped color value is converted into a device value R′G′B ′ of the output device.

  As a method of color gamut mapping performed in step S2M, various methods such as convergence point mapping and minimum color difference mapping have been proposed so far.

  For example, according to the convergence point mapping method, the input color value is maintained for the input color value in the output color gamut. On the other hand, for input color values outside the output color gamut, a convergence point PF within the output color gamut is set as shown in FIG. 24, and a line segment connecting the convergence point and the input color value is assumed. The input color value is moved between the point and the intersection. As a specific example, the maximum saturation point in an arbitrary hue of the input gamut is moved along the same hue to a predetermined point of the hue of the output gamut, and the color value inside the input gamut of the hue is output. A method for nonlinearly compressing the color values within the color gamut is disclosed (for example, see Patent Document 1). According to such a method, the hue of the color value of the input color gamut can be stored and reproduced with the color value of the output color gamut.

  Further, according to the color difference minimum mapping method, the input color value in the output color gamut is still maintained. On the other hand, for input color values outside the output color gamut, as shown in FIG. 25, there is a point Pin ′ at which the three-dimensional distance between the input color value and the output color gamut is minimum, that is, the color difference before and after mapping. The input color value is pasted to the point where it becomes the minimum. As a specific example, when mapping an input color value outside the output color gamut, a method is disclosed in which the input color value is pasted to a point that is vertically lowered from the input color value to the surface of the output color gamut (for example, , See Patent Document 2). According to such a method, when an input color value is output, it can be reproduced with a color value that is perceptually closest to the input color value.

JP 2001-036757 A JP 2005-117096 A

  The conventional color gamut mapping is effective for realizing good color reproduction when the color gamut of the output device is smaller than the color gamut of the input device. However, depending on the color gamut shape of the input color space or the output color space, the hue (gradation) may be expressed in an inverted manner when expressed by the perceptual color space value.

  FIG. 26 shows an example of hue inversion. In FIG. 26, a solid line represents an input color gamut boundary connecting the maximum saturation points between Cyan, Blue, and Magenta of the input device, and points P1, P2, P3, and P4 are on the input color gamut boundary. Represents a grid point. As shown in FIG. 26, in this input color gamut, the hue is clearly inverted in the section from the points P1 to P4. For this reason, for example, when an out-of-gamut color is pasted to the surface of the output color gamut using the convergence point mapping, the areas of P1-P2, P2-P3, and P3-P4 are displayed. Mapping on the same surface of the output color gamut. Therefore, the gradation after mapping may be broken, and a pseudo contour may be generated in the output image, which may cause significant image quality degradation.

  SUMMARY An advantage of some aspects of the invention is that it provides a color processing device and a color processing method that prevent occurrence of hue inversion due to color gamut mapping.

As a means for achieving the above object, the color processing apparatus of the present invention comprises the following arrangement. That is, color gamut acquisition means for acquiring an input color gamut and an output color gamut;
A dividing unit that divides the color gamut into a sub-grid smaller than a lattice on a device-dependent color space corresponding to the color gamut in at least one of the input color gamut and the output color gamut;
Inversion detection means for detecting an inversion region in which the hue is inverted in the partial grid;
Area correction means for allocating grid points in the inversion area detected by the inversion detection means on a line connecting two grid points sandwiching the inversion area while maintaining the ratio of the distance between the grid points in the inversion area When,
Gamut mapping means for mapping an input color value in the input color gamut into the output color gamut using the input color gamut and the output color gamut after the correction by the area correction unit. .

  According to the present invention configured as described above, it is possible to prevent occurrence of hue inversion due to color gamut mapping.

It is a block diagram which shows the structure of the color processing apparatus in one Embodiment which concerns on this invention. It is a flowchart which shows the process outline | summary in the color processing apparatus of this embodiment. It is a figure which shows the color gamut data example in this embodiment. It is a flowchart which shows the data acquisition process in this embodiment. It is a flowchart which shows the inversion detection process in this embodiment. It is a figure which shows the example of the partial grid | lattice in this embodiment. It is a figure which shows the example of a search line in this embodiment. It is a figure which shows the example of a search lattice point in the hue-saturation plane in this embodiment. It is a figure which shows the example of the conversion table of the grid point number and the number of intersections in this embodiment. It is a flowchart which shows the area | region correction process in this embodiment. It is a figure which shows the example of a movement of the hue inversion lattice point in this embodiment. It is a flowchart which shows the color gamut mapping process in this embodiment. It is a figure which shows the example of determination inside and outside the color gamut in this embodiment. It is a block diagram which shows the structure of the color processing apparatus in 2nd Embodiment. It is a flowchart which shows the process outline | summary in the color processing apparatus of 2nd Embodiment. It is a figure which shows the example of UI screen in 2nd Embodiment. It is a flowchart which shows the data acquisition process in 2nd Embodiment. It is a flowchart which shows the inversion detection process in 2nd Embodiment. It is a figure which shows the example of the search lattice point in 2nd Embodiment, a convergence point, and an intersection. It is a flowchart which shows the display process in 2nd Embodiment. It is a figure which shows the example of a warning display in 2nd Embodiment. It is a figure which shows the relationship of a general color gamut. It is a figure which shows the flow of the color gamut mapping of a general RGB image. It is a figure which shows the example of general convergence point mapping. It is a figure which shows the example of a general color difference minimum mapping. It is a figure which shows the example of the gradation deterioration in a general hue inversion area | region.

  Hereinafter, the present invention will be described in detail based on preferred embodiments with reference to the accompanying drawings. The configurations shown in the following embodiments are merely examples, and the present invention is not limited to the illustrated configurations.

<First Embodiment>
FIG. 1 is a block diagram showing a hardware configuration for realizing the color processing apparatus according to the present embodiment. In the color processing apparatus 1 shown in FIG. 1, 101 is a data acquisition unit that acquires gamut data, 102 is an inversion detection unit that detects a hue inversion region of the gamut acquired by the data acquisition unit 101, and 103 is an inversion detection unit 102. This is an area correction unit that corrects the inversion area detected in (1). Reference numeral 104 denotes a color gamut mapping unit that maps the color gamut corrected by the region correction unit 103. Reference numeral 105 denotes a color space value conversion unit that converts the color gamut mapped by the color gamut mapping unit 104 into the color space value of the output device. It is. Reference numeral 106 denotes an output unit that outputs the color space value converted by the color space value conversion unit 105, 107 denotes a color gamut data holding unit that holds color gamut data read by the data acquisition unit 101, and 108 denotes data that is being calculated. Is a buffer memory for temporarily storing

<< Process overview >>
In the color processing apparatus 1 of the present embodiment, a color conversion table for converting an input color space value (RGB) into an output color space value (Jab) is created. Hereinafter, processing in the color processing apparatus 1 will be described with reference to FIG. FIG. 2 is a flowchart showing color conversion table creation processing in the color processing apparatus 1.

  First, in step S <b> 1, the data acquisition unit 101 acquires the input color gamut and output color gamut held in the color gamut data holding unit 107 and stores them in the buffer memory 108.

  Here, the color gamut data is shown as a correspondence table describing pairs of perceptual color space values corresponding to each color signal value of the device as shown in FIG. 3, for example. For example, printer color gamut data is created as follows. First, the color signal values R, G, and B of the printer are each divided into a plurality of slices such as 5 slices or 9 slices, the RGB values at the lattice points of each slice are input to the printer, and the color chart is printed on a predetermined sheet. To do. Next, the printed color chart is measured by a colorimeter to obtain an XYZ value, and a perceptual color space value Jab is calculated from the XYZ value by a conversion formula of CIECAM02. In the present embodiment, color gamut data is created by storing the Jab value calculated in this way and the device RGB value in pairs. Detailed processing contents in the data acquisition unit 101 will be described later.

  Next, in step S2, the inversion detection unit 102 detects the hue inversion region of the input color gamut and the output color gamut acquired in step S1. Detailed processing contents in the inversion detection unit 102 will be described later.

  Next, in step S3, the area correction unit 103 corrects the hue inversion area detected in step S2. Detailed processing contents in the area correction unit 103 will be described later.

  In step S4, the color gamut mapping unit 104 maps the input color gamut corrected in step S3 to the output color gamut after correction. Detailed processing contents in the color gamut mapping unit 104 will be described later.

  In step S5, the color space value conversion unit 105 converts the color value after mapping in step S4 into a color space value of the output device, for example, an RGB value. The conversion of the perceptual color space value is performed using, for example, an LUT representing a relationship between the device color space value and the CIECAM02 value, a conversion matrix, or the like. When the LUT is used, conversion is performed using a known technique such as tetrahedral interpolation or cube interpolation.

  In step S6, the output unit 106 outputs a color conversion table in which the RGB values of the input color gamut data acquired in step S1 and the converted color space values converted in step S5 are combined.

<< Operation in Data Acquisition Unit 101 >>
Hereinafter, the operation of the data acquisition unit 101 in step S1 will be described in detail with reference to FIG. FIG. 4 is a flowchart showing data acquisition processing in the data acquisition unit 101.

  First, in step S101, the data acquisition unit 101 assigns an initial value 1 to a counter i indicating either input color gamut data or output color gamut data, and initializes it. In step S102, the grid point number in the lowest row of the i-th color gamut data held in the color gamut data holding unit 107 is read, and this is set as the number N of grid points in the i-th color gamut. In step S103, an initial value 1 is substituted into a counter j indicating a lattice point, and initialization is performed. In step S104, the grid point number, RGB value, and Jab value of the j-th grid point of the color gamut data held in the color gamut data holding unit 107 are sequentially read and written in the buffer memory 108. In step S105, 1 is added to the counter j. In step S106, it is determined whether all grid point numbers, RGB values, and Jab values have been acquired. For this determination, the number N of grid points is used. If the counter j is N or less, that is, if all the color gamut data has not been acquired, the process returns to step S104, and if the counter j exceeds N, that is, the color gamut. If all the data has been acquired, the process proceeds to step S107.

  In step S107, 1 is added to the counter i. In step S108, it is determined whether or not the color gamut data of the input color gamut and the output color gamut have been acquired. When the counter i is 2 or less, that is, when the gamut data has not been acquired, the process returns to step S102 to acquire the next gamut data. On the other hand, when the counter i exceeds 2, that is, when the gamut data is acquired for both the input gamut and the output gamut, the processing in the data acquisition unit 101 is terminated.

  Through the above processing, the input color gamut data and the output color gamut data are acquired in the data acquisition unit 101.

<< Operation in Reversal Detection Unit 102 >>
Hereinafter, the operation of the inversion detection unit 102 in step S2 will be described in detail with reference to FIG. FIG. 5 is a flowchart showing inversion detection processing in the inversion detection unit 102.

  In step S <b> 201, the inversion detection unit 102 first initializes the counter i by assigning an initial value 1. In step S202, the gamut data of the i-th gamut (the grid point numbers, RGB values, and Jab values of all grid points) is acquired from the buffer memory 108. In step S203, the number of partial grids (details will be described later) is calculated from the number of grid points of the color gamut data acquired in step S202 and set to N.

  In the present embodiment, when detecting the inversion area and correcting the area, the RGB grid is divided in a nested manner, and processing is performed for each grid. In general, nesting refers to a state in which smaller containers are sequentially placed in a box-shaped container. Therefore, the inside of each box must be hollow, but in this embodiment, it is assumed that there are grid points inside each grid. Hereinafter, each lattice is referred to as a partial lattice.

  FIG. 6 shows an example of a partial grid in the present embodiment. In FIG. 6, the black circles indicate lattice points, and the first partial lattice is composed of all lattice points included in a hexahedron having lattice points P1, P2, P3, P4, P5, P6, P7, and P8 as vertices. . The second partial grid is composed of all grid points included in a hexahedron having apexes at grid points P9, P10, P11, P12, P13, P14, P15, and P16. In the case of a 5-slice lattice as shown in FIG. 6, the first partial lattice is composed of all 125 lattice points, and the second partial lattice is composed of 27 lattice points that are nested inside. In general, in the case of an N-slice lattice, assuming that the step size of each slice is N steps, the value V that can be taken by the R, G, B values of the lattice points of the j-th partial lattice is given by the following equation (1). Can be represented.

V = min (N _step × (x−1), 255) (1)
Note that min (a, b) in equation (1) is a function that compares a and b and returns the smaller value. J and x satisfy the following expressions (2) and (3), respectively.

j ≦ x ≦ N− (j−1) (2)
1 ≦ j ≦ (N−1) / 2 (3)
Further, assuming that the number of bits of the device RGB value is n, the step width N _step can be expressed by the following equation (4) using the number of slices N.

N _step = 2 ⁿ / (N-1) (4)
In general, in the case of an N slice lattice, there are (N−1) / 2 partial lattices, and the number of lattice points of the j-th partial lattice can be expressed as (N−j + 1) ³ .

Returning to FIG. 5, in step S204, the inversion detection unit 102 substitutes the initial value 1 for the counter j and initializes it. In step S205, the j-th partial grid is extracted from the color gamut data acquired in step S202. In step S206, the number of search lines (details will be described later) included in the partial lattice extracted in step S205 is calculated and set to N _L.

  In this embodiment, when detecting a hue inversion region of a partial grid, a set is formed by several grid points, and the presence or absence of hue inversion at each grid point is recorded while searching for each grid point included in the set. I will do it. Hereinafter, the lattice points included in this set are referred to as search lattice points. A line connecting the search grid points in the search order is hereinafter referred to as a search line. FIG. 7 shows an example of a search line. In FIG. 7, each of the lattices 7 a to 7 g is configured with lattice points whose R, G, and B values satisfy the following expressions (5), (6), and (7).

V _i = N _step × j (5)
When 1 ≦ i ≦ N−1, 1 ≦ j ≦ i + 1 (6)
When N ≦ i ≦ 2N−3, i−N + 2 ≦ j ≦ N (7)
Here, N _step is the step size of the lattice expressed by the following equation (8), where n is the number of bits of the R, G, and B values.

N _step = 2 ⁿ / (N-1) (8)
If the minimum value that can be taken by the RGB values of the grid points included in each grid is V _min and the maximum value is V _max , the search line indicated by the thick line in FIG. Composed. However, the point 6 is returned to the point 1 after the point 6.

Point 1: (V _max , V _min , V _min )
Point 2: (V _max , V _max , V _min )
Point 3: (V _min , V _max , V _min )
Point 4: (V _min , V _max , V _max )
Point 5: (V _min , V _min , V _max )
Point 6: (V _max , V _min , V _max )
In general, there are 2N-3 search lines as described above in the case of an N-slice partial lattice.

  Returning to FIG. 5, in step S207, the inversion detection unit 102 substitutes the initial value 1 for the counter k and initializes it. In step S208, the search grid points on the kth search line are extracted from the partial grid acquired in step S205 in the search order, and are written in the buffer memory 108. The search lattice points are written into the buffer memory 108 in the order of extraction. In step S209, the hue angle h and saturation C of the search grid point extracted in step S208 are calculated and written in the buffer memory 108. The hue angle h is calculated by Equation (9) using the a and b values of the lattice points, and the saturation C is calculated by Equation (10).

In step S210, the grid point number of the grid point having the smallest hue angle h calculated in step S209 among the search grid points extracted in step S208 is set to _kmin . Then, in step S211, in order from the searched k _min-th search grid point in step S210, the hue - plots the search grid points on chroma, connecting the search grid points adjacent to each other in line. In step S212, based on the graph created in step S211, it is detected whether the hue of each search lattice point is inverted.

  Here, the hue inversion detection method in the present embodiment will be described using the hue-saturation plane shown in FIG. In FIG. 8, the horizontal axis represents hue and the vertical axis represents saturation. Points P1 to P7 represent some search grid points on the search line. First, a straight line perpendicular to the hue axis is defined through each search grid point, and the number of intersection points is calculated by obtaining the intersection with the graph connecting the search grid points. Here, the obtained intersections are shown as points Q1 to Q4 in FIG. For example, points Q1 and Q2 represent the intersections of the perpendicular line l3 passing through the point P3 and the graph. Accordingly, the number of intersections between the perpendicular l3 and the graph is a total of three points including the search grid point P3 in addition to the points Q1 and Q2. In this way, the number of intersections between the perpendicular line passing through each search grid point and the graph is obtained, and the number of intersection points is associated with each search grid point number and written to the buffer memory 108. An example of the intersection number correspondence table showing the correspondence between the grid point numbers and the number of intersection points is shown in FIG. As shown in FIG. 9, the grid point number is written in the first column, and the corresponding intersection number is written in the second column. When the number of intersections is 2 or more, it indicates that the hues of the search grid points and other search grid points are reversed. Therefore, the hue inversion at the grid points is represented by the intersection number correspondence table. Can be detected.

Returning to FIG. 5, the inversion detection unit 102 adds 1 to the counter k in step S <b> 213. In step S214, it is determined whether or not the processing has been completed for all the search lines in the partial grid. For this determination, N _L set in step S206 is used. If the counter k is less than N _L , that is, if the processing has not been completed for all search lines, the process returns to step S208. On the other hand, if the counter k exceeds N _L , that is, if the processing has been completed for all the search lines, the process proceeds to step S215.

  In step S215, 1 is added to the counter j, and in step S216, it is determined whether or not the processing has been completed for all the partial grids. For this determination, N set in step S203 is used. If the counter j is less than N, that is, if the processing has not been completed for all the partial grids, the process returns to step S205. On the other hand, if the counter j exceeds N, that is, if the processing has been completed for all the partial grids, the process proceeds to step S217.

  In step S217, 1 is added to the counter i. In step S218, it is determined whether or not the processing has been completed for all the color gamuts. Since there are two color gamuts in this embodiment, the input color gamut and the output color gamut, this determination is made by comparing the counter i with the number of color gamuts 2. If the counter i is less than 2, that is, if the processing for both the input color gamut and the output color gamut has not ended, the process returns to step S202. On the other hand, when the counter i exceeds 2, that is, when the processing is completed for both the input color gamut and the output color gamut, the processing in step S2 is terminated.

  As described above, the inversion detection unit 102 detects the hue inversion at the grid point based on the number of intersections between the line segment connecting the search grid points on the hue-saturation plane and the perpendicular line passing through the search grid points. This is a detection method using the fact that two or more intersections at the lattice point appear when the positional relationship of the lattice point is reversed.

  Further, since the hue inversion detection process is performed not only on the surface of the color gamut but also on the grid points inside the color gamut, the hue inversion of the grid points inside the color gamut can also be detected.

  In addition, since the hue inversion detection process is performed on the lattice points, even slight hue inversion in the color gamut can be detected. This is because the color gamut is composed of grid points and at the same time the grid points are singular points of the color gamut. This is a detection method utilizing the fact that hue inversion can be detected.

  In addition, since the detection process is performed only on the lattice points, hue inversion can be detected with a minimum search cost. Therefore, for example, it is possible to detect the hue inversion faster than the method of searching for the hue in increments of 1.

<< Operation in Region Correction Unit 103 >>
Hereinafter, the operation of the region correction unit 103 in step S3 will be described in detail with reference to FIG. FIG. 10 is a flowchart showing region correction processing in the region correction unit 103.

  In the processing of steps S301 to S308, the area correction unit 103 reads the color gamut data from the buffer memory 108, extracts the partial grid from the color gamut data, and then acquires the grid point on the search line included in the partial grid. To do. Since the above processing is the same processing as steps S201 to S208 shown in FIG. 5 in the above-described inversion detection unit 102, detailed description thereof is omitted here.

  Also, in steps S313 to S318, a process end determination for the search line in the partial grid, a process end determination for the partial grid, and a process end determination for the color gamut are performed. These processes are also the same as steps S213 to S218 shown in FIG. 5 in the above-described inversion detection unit 102, and thus detailed description thereof is omitted. Hereinafter, processing from steps S309 to S312 that is different from the processing of the inversion detection unit 102 will be described.

  In step S309, the area correction unit 103 acquires the intersection number correspondence table (FIG. 9) written in the buffer memory 108 in step S212 of FIG. 5 described above. In step S310, the grid point number of the search grid point located at the boundary of the hue inversion region is acquired based on the intersection number correspondence table. According to the intersection number correspondence table shown in FIG. 9, search lattice points having two or more intersection points are search lattice points having lattice point numbers 3 to 5, and therefore the search lattice point is a hue inversion region. I understand. Hereinafter, a search lattice point adjacent to the hue inversion region is referred to as a boundary lattice point. In the case of FIG. 9, the search grid points with grid point numbers 2 and 6 are the boundary grid points. These two search lattice points are set as one set and stored in the buffer memory 108 for each set.

  In step S311, the inter-grid point distance is calculated and written to the buffer memory 108 for the search lattice point in the hue inversion region sandwiched between the boundary lattice points acquired in step S310. Here, if i is a natural number, the distance d i between the i-th search lattice point and the i + 1-th search lattice point is calculated by the following equation (11). In equation (11), Ji, ai, and bi represent J, a, and b values of the i-th search lattice point.

  Next, in step S312, the search lattice point of the hue inversion region is moved according to the ratio of the distance between lattice points calculated in step S311. In the present embodiment, the hue inversion lattice point is moved to a point that internally divides between a set of boundary lattice points by the ratio of the distance between lattice points of the hue inversion lattice point. An example of the movement of the hue inversion lattice point is shown in FIG. FIG. 11 is a diagram showing search lattice points and moved points on the ab plane. Assuming that the search grid points are P1 to P7 and the points after the search grid points are moved are P'3 to P'5, each of the moved grid points has the grid point number of one of the boundary grid points as the other grid point. If the lattice point number is e, it can be expressed by equation (12). At this time, mi and ni can be expressed as shown in equations (13) and (14), respectively. O represents the origin of the ab plane.

  The Jab value of the hue inversion grid point of the color gamut data is rewritten by the Jab value after the movement obtained using the above equation (12). Through the above processing, the hue inversion region of the color gamut can be corrected.

  As described above, the region correcting unit 103 maintains the ratio of the distance between the lattice points of the hue inversion region, and moves the hue inversion lattice point between the boundary lattice points at both ends sandwiching the hue inversion region. Correct the hue inversion of the color gamut.

<< Operation in Color Gamut Mapping Unit 104 >>
Hereinafter, the operation of the color gamut mapping unit 104 in step S4 will be described in detail with reference to FIG. FIG. 12 is a flowchart showing color gamut mapping processing in the color gamut mapping unit 104 of the present embodiment.

  First, in step S401 and step S402, the color gamut mapping unit 104 acquires the input color gamut data and the output color gamut data corrected in step S312 of FIG. In step S403, the number of grid points is acquired from the input color gamut data acquired in step S401 and set to N. In step S404, the data area of the color conversion table is secured in the buffer memory 108. This color conversion table shows the correspondence between the color space values R, G, and B of the input device and the J, a, and b values after mapping the J, a, and b values corresponding to the color space values to the output color gamut. This is to save the date.

  In step S405, a point in the output color gamut, for example, (50, 0, 0) is set as the convergence point. In step S406, the initial value 1 is substituted into the counter i to be initialized. In step S407, the i-th grid point of the input color gamut is acquired, and in step S408, the RGB value of the input grid point is written in the color conversion table secured in step S404. In step S409, it is determined whether the input grid point exists outside the output color gamut. This color gamut inside / outside determination is performed based on the positional relationship between the triangles forming the output color gamut surface and the straight line connecting the input grid point and the convergence point. FIG. 13 shows an example of color gamut inside / outside determination in the present embodiment. As shown in FIG. 13, assuming that the vertices of the triangle formed by the lattice points on the surface of the output color gamut are B, C, and D, the convergence point set in step S405 is A, and the input lattice point is P, a straight line A point on the AP is represented by the following equation (15).

  Here, when the J, a, and b values of the point X are represented by (Jx, ax, bx), s, t, and u are calculated by Expression (16).

  At this time, if the point P exists inside the tetrahedron ABCD, the following equations (17) and (18) are established.

s + t + u ≦ 1 (17)
0 ≦ s, 0 ≦ t, 0 ≦ u (18)
If Expressions (17) and (18) are established, it is determined that the input grid point exists in the output color gamut, and the process proceeds to Step S412. On the other hand, if Expressions (17) and (18) do not hold, it is determined that the input grid point exists outside the output color gamut, and the process proceeds to Step S410.

  In step S410, the intersection of the straight line passing through the input grid point and the convergence point and the output color gamut surface is calculated, and in step S411, the Jab value of the intersection calculated in step S410 is the color secured in step S404. Write to the i-th row of the conversion table.

  In step S412, the Jab value of the input grid point acquired in step S407 is written in the i-th row of the color conversion table secured in step S404.

  In step S413, 1 is added to the counter i. In step S414, it is determined whether or not processing has been completed for all grid points in the input color gamut. For this determination, N set in step S403 is used. If the counter i is less than N, that is, if the processing has not been completed for all grid points, the process returns to step S407. On the other hand, if the counter i exceeds N, that is, if the processing has been completed for all grid points, the processing in step S4 is terminated.

  As described above, the color gamut mapping unit 104 stores the color values of input grid points in the output color gamut. On the other hand, for input grid points outside the output color gamut, the input color gamut is mapped to the output color gamut by pasting it to the intersection of the line segment connecting the input grid point and the convergence point and the output color gamut surface.

<< Effects of Present Embodiment >>
As described above, according to the present embodiment, when creating a color conversion table for converting input color space values to output color space values, the color gamut of the input device is automatically mapped to the color gamut of the output device. be able to. Furthermore, the grid constituting the color gamut is divided into partial grids, and for each search line of each partial grid, adjacent grid points on the hue-saturation plane are connected by line segments, passing through each grid point and using the hue axis. The grid point where the hue is inverted can be detected by the number of intersections between the vertical straight line and the line segment. If the hue is inverted, the ratio of the distance between the lattice points of the hue inversion lattice point is maintained on the straight line connecting the boundary lattice points sandwiching the hue inversion lattice point, and the hue inversion lattice point is By moving, mapping that prevents hue inversion can be performed.

Second Embodiment
Hereinafter, a second embodiment according to the present invention will be described. . Also in the second embodiment, a color conversion table for converting an input color space value to an output color space value is created, and this is characterized in that a confirmation operation by the user intervenes. Also in the second embodiment, hue inversion in the color gamut is detected, but a method different from that of the first embodiment described above is used as this detection method.

  FIG. 14 is a block diagram illustrating a hardware configuration that implements the color processing apparatus according to the second embodiment. In the color processing apparatus 2 shown in the figure, 201 is a UI (user interface) unit that receives input from the user, 202 is a data acquisition unit that acquires color gamut data, and 203 is the hue of the color gamut acquired by the data acquisition unit 202. It is an inversion detection unit that detects an inversion area. Reference numeral 204 denotes a display unit that displays a message that allows the user to select whether or not to correct the inversion area detected by the inversion detection unit 203, and 205 denotes an area correction unit that corrects the inversion area detected by the inversion detection unit 203. It is. Reference numeral 206 denotes a color gamut mapping unit that maps the color gamut corrected by the region correction unit 205. Reference numeral 207 denotes a color space value conversion unit that converts the color gamut mapped by the color gamut mapping unit 206 into the color space value of the output device. It is. Also, 208 is an output unit that outputs the color space value converted by the color space value conversion unit 207, 209 is a color gamut data holding unit that holds color gamut data read by the data acquisition unit 202, and 210 is each piece of data that is being calculated. Is a buffer memory for temporarily storing

<< Process overview >>
Hereinafter, processing in the color processing apparatus 2 of the second embodiment will be described with reference to FIGS. 15 and 16. FIG. 15 is a flowchart illustrating conversion table creation processing in the color processing apparatus 2, and FIG. 16 is a diagram illustrating a display example of the UI unit 201 that realizes setting of color conversion table creation conditions.

  The color conversion table in the second embodiment is created based on the color conversion table creation conditions set on the display screen shown in FIG. In FIG. 16, 1P is a UI that functions as a setting screen. 2P is an input color gamut acquisition unit that acquires input color gamut data, and 3P is an output color gamut acquisition unit that acquires output color gamut data. Here, for example, when the input gamut data and the output gamut data are acquired by specifying a file path for a memory (for example, an external storage device) in which the input gamut data and the output gamut data to be processed are stored. To do. Reference numeral 4P denotes a color gamut display unit that displays a color gamut and hue inversion grid points. Reference numeral 5P denotes an OK button, which is a button for confirming various designated data as data used for processing after various inputs are completed.

  When creating the color conversion table, first, in step S21 shown in FIG. 15, the data acquisition unit 202 determines whether or not the OK button 5P in the UI unit 201 is pressed. If this is not pressed, the user input is awaited, but if the OK button 5P is pressed, the process proceeds to step S22.

  In step S22, the data acquisition unit 202 determines the input color gamut and output color gamut held in the color gamut data holding unit 209 based on the input color gamut and output color gamut conditions set on the screen of FIG. Is stored in the buffer memory 108. Detailed processing contents in the data acquisition unit 202 will be described later.

  Next, in step S23, the inversion detection unit 203 detects hue inversion grid points of the input color gamut and output color gamut acquired in step S22. The detailed processing contents in the inversion detection unit 203 will be described later.

  Next, in step S24, the display unit 204 determines whether or not a hue inversion grid point has been detected in step S23. A method for determining whether or not hue is reversed will be described later together with specific processing contents of the display unit 204. If a phase inversion lattice point is detected, the process proceeds to step S25. If not detected, the process proceeds to step S28.

  In step S25, the display unit 204 displays a message indicating that the image quality is deteriorated due to the hue reversal, and allows the user to select whether or not to correct the reversal area, as will be described later.

  In step S26, the selection result in step S25 is determined as will be described later. If correction of the inversion area is selected, the process proceeds to step S27, and if not selected, the process proceeds to step S28.

  In step S27, the area correction unit 205 corrects the hue inversion area detected in step S23. Since this correction method is the same as step S3 in the first embodiment described above, description thereof is omitted.

  In step S28, the color gamut mapping unit 206 maps the input color value of the input color gamut to the output color gamut. That is, the input color value to be mapped can be corrected in step S27 or not corrected. Since this mapping method is the same as step S4 in the first embodiment described above, description thereof is omitted.

  In step S29, the color space value conversion unit 207 converts the color value after mapping in step S28 into a color space value of the output device, for example, an RGB value. Since this conversion method is the same as step S5 in the first embodiment described above, description thereof is omitted. In step S30, the output unit 208 outputs a color conversion table based on the converted color space value converted in step S29. Since this output method is the same as step S6 in the first embodiment described above, description thereof is omitted.

  << Operation in Data Acquisition Unit 202 >>

  Hereinafter, the operation of the data acquisition unit 202 in step S22 will be described in detail with reference to FIG. FIG. 17 is a flowchart showing data acquisition processing in the data acquisition unit 202.

  First, in step S501, the data acquisition unit 202 acquires the file path of the input color gamut data set in the input color gamut acquisition unit 2P shown in FIG. In step S502, the input color gamut data held in the file path acquired in step S501 is read from the color gamut data holding unit 209 and written in the buffer memory 210. In step S503, the file path of the output color gamut data set in the output color gamut acquisition unit 3P is acquired. In step S504, the output color gamut data held in the file path acquired in step S503 is read from the color gamut data holding unit 209 and written in the buffer memory 210.

<< Operation in Reverse Detection Unit 203 >>
Hereinafter, the operation of the inversion detection unit 203 in step S23 will be described in detail with reference to FIG. FIG. 18 is a flowchart showing inversion detection processing in the inversion detection unit 203. 18 are the same as steps S201 to S203 of FIG. 5 showing the inversion detection process in the first embodiment described above, and thus the description thereof is omitted.

When the inversion detection unit 203 completes the initialization of the counter i, the acquisition of the color gamut data of the i-th color gamut, and the setting of the number N of partial grids in steps S601 to S603, in step S604, A point, for example, (50, 0, 0) is set as the convergence point. In step S605, the initial value 1 is substituted into the counter j to be initialized. In step S606, the j-th partial grid is extracted from the color gamut data acquired in step S602. In step S607, the number of grid points on the color gamut surface of the partial grid extracted in step S606 is calculated and set to N _s .

Here, if the number of lattice points in the color gamut is N and i is a natural number, the number of lattice points of the i-th partial lattice is expressed by the following equation (19). Accordingly, the number N _s of lattice points on the color gamut surface of the i-th partial lattice is expressed by the following equation (20).

  Next, in step S608, the initial value 1 is substituted into the counter k to be initialized. In step S609, J, a, and b values for the kth lattice point on the color gamut surface are acquired from the partial lattice extracted in step S606. In step S610, the lattice point and the convergence point set in step S604 are obtained. The equation of the straight line connecting is calculated. In step S611, the intersection point between the color gamut surface of the partial grid and the straight line is calculated, and the obtained number of intersection points is written in the buffer memory 210.

  Here, FIG. 19 shows an example of a straight line connecting a lattice point and a convergence point, a color gamut surface of a partial lattice, and an intersection thereof. In FIG. 19, the lattice point on the surface of the color gamut of the partial lattice is Pi (where i = 1,..., 8), the convergence point is PF, and the straight line connecting the lattice point and the convergence point (from PF in FIG. Let Qj (where j = 1,..., 4) be the intersection of the radially extending broken line) and the color gamut surface. At this time, there are two or more intersections including the lattice point itself on the straight line in the hue inversion region, and only the lattice point itself exists on the straight line in the region where the hue is not inverted. Therefore, it can be determined whether or not each grid point is hue-inverted based on the number of intersection points.

Returning to FIG. 18, the inversion detection unit 203 adds 1 to the counter k in step S612. In step S613, it is determined whether or not processing has been completed for all grid points in the partial grid. For this determination, N _s set in step S607 is used. If the counter k is less than N _s , that is, if the processing has not been completed for all grid points, the process returns to step S609. On the other hand, if the counter k exceeds N _s , that is, if the processing has been completed for all the search lines, the process proceeds to step S614.

  In addition, since the process of step S614-S617 is the same as that of step S215-S218 shown in FIG. 5 by 1st Embodiment mentioned above, description is abbreviate | omitted.

  As described above, the inversion detection unit 203 of the second embodiment divides the color gamut into partial grids, obtains a straight line connecting the lattice points constituting the surface of the partial grid and the convergence point, and the straight line and the partial grid are obtained. The intersection with the surface of the color gamut is calculated, and the hue inversion of each grid point is detected based on the number of intersections. This is a detection using the fact that two or more intersections between the straight line connecting the grid point and the convergence point and the color gamut surface appear when the grid points constituting the color gamut surface of the partial grid are reversed. Is the method.

  Further, by performing the hue inversion detection process not only on the surface of the color gamut but also on the grid points inside the color gamut, the hue inversion of the grid points inside the color gamut can also be detected.

  Further, since the hue inversion detection process is performed on the lattice points, it is possible to detect even slight hue inversion in the color gamut. This is because the color gamut is composed of grid points and at the same time the grid points are singular points of the color gamut. The fact that hue inversion can be detected is utilized.

  Further, since the detection process is performed only on the lattice points, the hue inversion can be detected with a minimum search cost, and the hue inversion can be detected at high speed.

<< Operation in Display Unit 204 >>
Hereinafter, the operation of the display unit 204 in step S25 will be described in detail with reference to FIG. FIG. 20 is a flowchart illustrating display processing in the display unit 204 according to the second embodiment.

  First, in step S701, the display unit 204 assigns an initial value 0 to the inversion flag F and initializes it. This inversion flag F is a flag for determining whether or not hue inversion has occurred at the lattice points of the color gamut, and is used when warning the user of the possibility of hue inversion in step S708 to be described later. In the second embodiment, when the inversion flag F is 0, it indicates that there is no inversion, and when F is 1 or more, it indicates that there is inversion.

  In step S702, the number of intersections at each lattice point is acquired from the buffer memory 210. In step S703, the presence / absence of hue inversion at each lattice point is determined based on the number of intersections. If the number of intersections exceeds 1, that is, if hue inversion has occurred at the lattice points, the process proceeds to step S704. On the other hand, if the number of intersections is 1 or less, that is, if hue inversion has not occurred at the lattice point, the process proceeds to step S706.

  In step S704, 1 is added to the inversion flag F, and in step S705, the grid points are plotted on the ab plane of the color gamut display unit 4P of the UI unit 201.

  In step S706, it is determined whether or not processing has been completed for all grid points. If it has been completed, the process proceeds to step S707. If it has not been completed, the process returns to step S702.

In step S707, the substitutes an initial value 0 to the correction flag F _c, initialized. The correction flag F _c is a flag for determining whether or not to correct the hue inversion region, and is set by the user's determination in step S709 described later.

  In step S708, the presence / absence of an inversion area is determined based on the inversion flag F. If the inversion flag F exceeds 0, that is, if an inversion area exists, the process proceeds to step S709. On the other hand, when the inversion flag F is 0 or less, that is, when the inversion area does not exist, the process of step S25 is ended.

  In step S709, a warning message is displayed to the user to select whether to correct the reverse area. For example, as shown in FIG. 21, the warning to the user informs that there is a possibility that image quality deterioration due to the inversion area may occur because the hue inversion area exists in the color gamut, and corrects the color gamut. A message box is displayed with a content that prompts the user to select whether or not to do so. This message box includes a “Yes” button 1Q and a “No” button 2Q for obtaining the user's judgment.

In step S710, it is determined which of the “Yes” button 1Q or the “No” button 2Q is pressed on the message box displayed in step S709. If "YES" button 1Q is pressed, after setting 1 to the correction flag F _c proceeds to step S711, but the process ends in step S25, if the "No" button 2Q is pressed, it The process of step S25 ends.

  As described above, the display unit 204 determines whether or not hue inversion has occurred based on the number of intersections of each grid point set in step S23. If hue inversion has occurred at the grid point, the user can visually know the hue inversion region by plotting the grid point on the color gamut display unit 4P of the UI unit 201. Furthermore, the user can be warned of the possibility of image quality degradation due to hue inversion, and the user can select whether or not to correct the hue inversion area.

  As described above, according to the second embodiment, when creating a color conversion table for converting input color space values to output color space values, the color gamut of the input device is automatically mapped to the color gamut of the output device. This can be performed based on conditions set by the user. Further, hue inversion of the color gamut can be detected at the time of mapping, and the user can be notified of the possibility of image quality degradation due to the hue inversion.

  In addition to the notification, a selection button that allows the user to select whether or not to correct the inversion area is provided, so that the user can select whether or not to execute the correction process. Furthermore, since the display unit that displays the hue inversion area on the ab plane is provided, the user can visually grasp in which area the hue inversion has occurred.

<Modification>
In each of the above-described embodiments, the description has been made using the CIECAM02 color space. However, any color space may be used as long as it is a perceptual color space such as CIELAB, CIEUV, and CIECAM97s.

  Further, in the inversion detection units 102 and 203 and the area correction units 103 and 205, the search lattice points are searched in the order of points 1 to 6 as described in step S206 in FIG. It is not limited. For example, the search may be started from the point 2, searched in the order of points 3, 4, 5, 6, 1, and finally returned to the point 2.

  In the area correction units 103 and 205, when correcting the hue inversion area, the hue inversion grid point is moved on a straight line connecting the boundary grid points at both ends sandwiching the hue inversion grid point. However, the present invention is not limited to this example. For example, the hue inversion lattice point and the boundary lattice point may be moved between two lattice points sandwiching the hue inversion lattice point and the boundary lattice point. Further, the movement destination of the hue inversion grid point need not be limited to a straight line. For example, a quartic function passing through a boundary grid point and two grid points sandwiching the boundary grid point is defined, and It is good also as a movement destination on a curve. By moving on the curve in this way, the gradation at the boundary between the correction area and the non-correction area can be smoothly connected.

  Further, in the inversion detection units 102 and 203 and the color gamut mapping units 104 and 206, an example is shown in which the J, a, and b values of the convergence point are set to (50, 0, 0). Any coordinates within the color gamut are acceptable. Preferably, the white point of the output color gamut, that is, the point of (R, G, B) = (255, 255, 255) and the black point, that is, the point of (R, G, B) = (0, 0, 0). A convergence point is set at the midpoint of. Further, the gray of the input color gamut or the output color gamut, that is, the point of (R, G, B) = (128, 128, 128), the center of the input color gamut, the center of the output color gamut, etc. A point near the center may be a convergence point.

  Further, the color gamut mapping units 104 and 206 store the color values of the input grid points in the output color gamut, and connect the input grid points to a predetermined convergence point for the input grid points outside the output color gamut. The method of pasting at the intersection of the line segment and the output color gamut surface has been described. However, the present invention is not limited to this example. For example, the lightness of the input grid point may be maintained and pasted to the surface of the output color gamut, and the three-dimensional distance of the CIECAM02 color space before and after the mapping of the input grid point may be minimized. It may be pasted on the output color gamut surface. Further, it is not necessary to completely store colors in the output color gamut, and mapping may be performed so as to map to preferable colors both inside and outside the output color gamut. Further, a masking method using a conversion matrix that associates the color values of the first color space and the color values of the second color space may be used.

  Moreover, each structure shown by each embodiment mentioned above is mutually combinable, unless it deviates from the meaning of this invention.

<Other embodiments>
Although the embodiment has been described in detail above, the present invention can take an embodiment as a system, apparatus, method, program, storage medium (recording medium), or the like. Specifically, the present invention may be applied to a system composed of a plurality of devices (for example, a host computer, an interface device, an imaging device, a web application, etc.), or may be applied to a device composed of a single device. good.

  In the present invention, a software program for realizing the functions of the above-described embodiments is supplied directly or remotely to a system or apparatus, and the computer of the system or apparatus reads and executes the supplied program code. Is also achieved. The program in this case is a program corresponding to the flowchart shown in the drawing in the embodiment.

  Accordingly, since the functions of the present invention are implemented by computer, the program code installed in the computer also implements the present invention. In other words, the present invention includes a computer program itself for realizing the functional processing of the present invention.

  In that case, as long as it has the function of a program, it may be in the form of object code, a program executed by an interpreter, script data supplied to the OS, or the like.

  Recording media for supplying the program include the following media. For example, floppy disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card, ROM, DVD (DVD-ROM, DVD- R).

  As a program supply method, the following method is also possible. That is, the browser of the client computer is connected to a homepage on the Internet, and the computer program itself (or a compressed file including an automatic installation function) of the present invention is downloaded to a recording medium such as a hard disk. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from a different homepage. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention on a computer is also included in the present invention.

  In addition, the program of the present invention is encrypted, stored in a storage medium such as a CD-ROM, distributed to users, and key information for decryption is downloaded from a homepage via the Internet to users who have cleared predetermined conditions. It is also possible to make it. That is, the user can execute the encrypted program by using the key information and install it on the computer.

  Further, the functions of the above-described embodiments are realized by the computer executing the read program. Furthermore, based on the instructions of the program, an OS or the like running on the computer performs part or all of the actual processing, and the functions of the above-described embodiments can also be realized by the processing.

  Further, the program read from the recording medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, and then executed, so that the program of the above-described embodiment can be obtained. Function is realized. That is, based on the instructions of the program, the CPU provided in the function expansion board or function expansion unit can perform part or all of the actual processing.

Claims (7)

Color gamut acquisition means for acquiring an input color gamut and an output color gamut;
A dividing unit that divides the color gamut into a sub-grid smaller than a lattice on a device-dependent color space corresponding to the color gamut in at least one of the input color gamut and the output color gamut;
Inversion detection means for detecting an inversion region in which the hue is inverted in the partial grid;
Area correction means for allocating grid points in the inversion area detected by the inversion detection means on a line connecting two grid points sandwiching the inversion area while maintaining the ratio of the distance between the grid points in the inversion area When,
Gamut mapping means for mapping an input color value in the input color gamut into the output color gamut using the input color gamut and the output color gamut after the correction by the area correction unit. Color processing device.   The inversion detection means plots a plurality of grid points constituting a color space on a hue-saturation plane, and performs hue inversion according to the number of intersections between line segments connecting the grid points and perpendicular lines passing through the grid points. The color processing apparatus according to claim 1, wherein the color processing apparatus detects the color processing apparatus.   The inversion detection means detects hue inversion by the number of intersection points between the color gamut surface of the partial grid, and the line segment connecting the grid point of the color gamut surface and the convergence point set in the output color gamut. The color processing apparatus according to claim 1.   The color processing apparatus according to claim 1, wherein the area correction unit moves a grid point in the inversion area between grid points that sandwich the inversion area. Informing means for informing the user of the inversion area detected by the inversion detection means;
An operation means for inputting a user instruction indicating whether correction by the area correction means is possible,
The area correcting unit, when a user instruction indicating a correction-friendly by the operation means is inputted, the color processing apparatus according to any one of claims 1 to 4, characterized in that to correct the inversion region. A color processing method performed by a color processing apparatus,
A color gamut acquisition step for acquiring an input color gamut and an output color gamut;
A division step of dividing the color gamut into a partial grid smaller than a grid on a device-dependent color space corresponding to the color gamut in at least one of the input color gamut and the output color gamut;
An inversion detection step for detecting an inversion region in which the hue is inverted in the partial grid,
An area correction step for allocating grid points in the inversion area detected in the inversion detection step on a line connecting two grid points sandwiching the inversion area while maintaining a ratio of the distance between the grid points in the inversion area When,
A color gamut mapping step of mapping an input color value in the input color gamut into the output color gamut using the input color gamut and the output color gamut after the correction in the region correction step; Color processing method. A computer program that, when executed on a computer, causes the computer to function as each unit included in the color processing device according to any one of claims 1 to 5 .

Images