JP2006081024A - Color processing apparatus and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To acquire accurate color region in the analysis when accurate acquisition of color region is very important for the mapping and it is required to analyze the device characteristic for selection of the mapping method. <P>SOLUTION: The color distribution data indicating a set of the RGB value for designating the color on the RGB color space and the L*a*b* value (measured color value) indicating reproduced color at the printing time is read (S302), a coefficient of B spline body for calculation of color region and the basic function are calculated (S303) using the color distribution data, and the color region data is generated using the B spline body (S304). <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a color processing apparatus and method, and for example, relates to calculation of a color gamut.

  In recent years, with the spread of personal computers and workstations, desktop publishing (DTP) and digital image management have become widely used. In a computer system with a color monitor and a color printer for DTP, color images are created, edited, and processed on the monitor, the output image is checked by preview, and the color printer outputs the color image . Alternatively, an image photographed by a digital camera is displayed on a color monitor or output by a color printer after color adjustment. At that time, the user strongly desires that the color image on the monitor and the output image of the printer coincide perceptually.

  However, in the color reproduction technique, it is difficult to achieve perceptual matching between the color image and the output image of the printer for the following reason.

  A color monitor of a CRT expresses a color image by emitting light of a specific wavelength using a phosphor. On the other hand, a color printer absorbs light of a specific wavelength using ink or the like, and expresses a color image by the remaining reflected light. Due to such a difference in image display form, the color gamuts of both differ greatly. Furthermore, even color monitors have different color gamuts with liquid crystal, electron gun CRT, and plasma. Of course, color printers also have different color gamuts due to differences in paper quality and differences in the amount of ink used. Therefore, in the colorimetric sense, the color of the image on the color monitor and the output image of the color printer, or the output images of the color printer output by multiple printer models and multiple paper quality, are completely It is impossible to match. Therefore, when a human perceives a color image on each display / output medium, a large difference is perceived between the images.

  Therefore, there exists a gamut mapping technique that absorbs the difference in perception of color images between display / output media having different color gamuts and performs perceptual matching of color images. The gamut mapping technique maps a certain color gamut into another color gamut using a uniform color system. As an example of the gamut mapping technique, a method of compressing the color gamut toward one point on the achromatic color axis, a method of performing linear mapping such as affine transformation in the lightness-saturation dimension, and the like are known. Furthermore, a technique for applying a one- to three-dimensional mapping over a plurality of stages as in JP-A-2001-94799, or a gradation representing a color change as a curve expression as in JP-A-2002-33929 There is a technology that realizes the resulting gamut mapping.

  It is very important to obtain the color gamut accurately when performing these mappings. In selecting a mapping method, it is necessary to analyze the characteristics of the device, and it is required to obtain an accurate color gamut in the analysis.

Japanese Patent Laid-Open No. 2001-94799 JP 2002-33929 A

  The present invention solves the above-described problems individually or collectively, and an object thereof is to accurately calculate a color gamut.

  Another object is to calculate the color gamut smoothly.

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

  In calculating the color gamut of a predetermined color system, the present invention sets a multiple sum operation using a piecewise polynomial having the same multiplicity as the number of dimensions of the first color system as a basis function, The coefficient of the piecewise polynomial is obtained based on data indicating a combination of a plurality of color signal values of the color system of the first color system and a plurality of color signal values of the second color system, which is a colorimetric result for the color signal values. The color gamut of the second color system corresponding to the color gamut of the first color system is calculated using the multiple sum operation.

  Further, when calculating the color gamut of a predetermined color system, a multiple sum operation is set with a piecewise polynomial having the same multiplicity as the number of dimensions of the first color system as a basis function, and the first table Based on data indicating a combination of a plurality of color signal values of the color system and a plurality of color signal values of the second color system that are the colorimetric results for these color signal values, a plurality of colors of the second color system A coefficient of the piecewise polynomial corresponding to a curved surface approximating a sequence of signal values or a curved surface connecting the plurality of color signal values, and using the multiple sum operation, the color gamut of the first color system The color gamut of the second color system corresponding to is calculated.

  According to the present invention, the color gamut can be accurately calculated.

  In addition, the color gamut can be calculated smoothly.

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

[Constitution]
FIG. 1 is a block diagram illustrating a configuration example of a color processing apparatus according to an embodiment.

  In FIG. 1, a CPU 101 is described later via a system bus (and PCI bus) 114 using the main memory 102 as a work memory according to a program stored in a main memory 102 or a hard disk drive (HDD) 105 including ROM and RAM. Various processes and controls to be described later are executed by controlling the configuration to be performed.

  A general-purpose parallel interface (I / F) 103 such as SCSI interfaces the HDD 105 with the system bus 114. The graphic accelerator 106 interfaces the color monitor 107 and the system bus 114. The USB controller 108 interfaces the color printer 109 and the system bus 114. The keyboard / mouse controller 110 interfaces the input device such as the keyboard 111 and the mouse 112 with the system bus 114. Note that the HDD 105, keyboard 111 and mouse 112 may be interfaced with the system bus 114 by a serial bus interface such as USB controller 108 or IEEE 1394 instead of the SCSI I / F 103 and keyboard / mouse controller 110. A network interface (I / F) 104 interfaces a local area network (LAN) 113 with a system bus.

[Analysis of color gamut]
A series of operations for calculating and analyzing the color gamut using the color distribution data in the above configuration will be described.

  First, a color gamut analysis application stored in the HDD 105 is activated by a user operation and a command from the CPU 101. Subsequently, the initial profile and initial edited color data stored in the HDD 105 are transferred to the main memory 102 via the SCSI I / F 103 and the system bus 114 based on the command of the CPU 101 in accordance with the processing of the color gamut analysis application. Is done. The user interface of the color analysis tool shown in FIG. 2 is displayed on the color monitor 107 by the color gamut analysis application.

  The user interface shown in FIG. 2 includes a distribution data reading button 201 for instructing reading of color distribution data, a color gamut storage button 202 for instructing storage of color distribution data, and a three-dimensional display area 203 of the color gamut. There are an operation area 204 for instructing an operation for the stored color gamut, and an end button 208 for instructing the end of the color gamut analysis application.

  The operation area 204 includes a list box 205 for selecting a stored color gamut, a check box 206 for turning on / off the three-dimensional display of the color gamut selected in the list box 205, and a color gamut selected in the list box 205. There is a color gamut deletion button 207 for deleting from the storage area of the main memory 102.

  When the user clicks (or presses) the distribution data reading button 201 with the mouse 112 or the like and instructs to read the color distribution data, the color distribution data is transferred to the HDD according to the command of the CPU 101 according to the processing of the color gamut analysis application. The data is transferred from 105 to the main memory 102 via the SCSI I / F 103 and the system bus 114.

  The color gamut analysis application calculates a color gamut from the color distribution data stored in the main memory 102, and displays the calculated color gamut in a three-dimensional display area 203 in a pseudo three-dimensional manner. Here, when the user presses the color gamut storage button 202, the color gamut displayed in a pseudo three-dimensional manner is stored (saved) in the main memory 102.

  The user operates the list box 205 to select the operation target color gamut from the color gamut stored (saved) in the main memory 102, and sets the three-dimensional display of the selected color gamut using the check box 206. . The color gamut in which the check box 206 is turned on is displayed in a superimposed manner on other objects being displayed in the three-dimensional display area 203.

  When the user presses the end button 208, the color gamut analysis application releases all data storage areas and work areas used for processing, and ends the processing.

[Color Gamut Analysis Application Operation]
Next, the color analysis application operation will be described. FIG. 3 is a state transition diagram for explaining the operation of the color analysis application.

  First, initialization such as securing various memory areas necessary for operation is performed (S301), and color distribution data is read from the HDD 105 and stored in the main memory 102 (S302). The color distribution data stored in the main memory 102 is a color distribution that indicates a set of RGB values that specify colors in the RGB color space and L * a * b * values (colorimetric values) that represent the reproduced colors at the time of printing. It has a data structure as shown in FIG. 4 consisting of data and the total number of color distribution data. The total number of color distribution data is described at the beginning, and then a set of RGB values and L * a * b * values is described for the total number of color distribution data.

  Next, using the color distribution data stored in the main memory 102, the coefficient and basis function for the B spline body for color gamut calculation are calculated by the process described later (S303), and the B spline body is converted according to the process described later. Using this, color gamut data is created and stored in the main memory 102 (S304), and 3D object data for pseudo three-dimensional display is calculated from the color gamut data according to the processing described later (S305). The process waits (S306).

  When the color distribution data reading button 201 shown in FIG. 2 is pressed in the user operation waiting state (S306), a dialog for the user to specify the color distribution data file to be read is displayed, and the color distribution data file is specified. Then, it is determined whether or not the specified color distribution data file can be opened. If it can be opened, the color distribution data file is read and stored in the main memory 102, and whether or not the format of the color distribution data file is correct. Is determined (S307). If the format is open and correct, the process proceeds to step S303. If the format is not open or illegal, the message is displayed and the process returns to step S306.

  When the color gamut storage button 202 shown in FIG. 2 is pressed, the 3D object data of the color gamut stored in the main memory 102 is saved in a predetermined area of the main memory 102 (or HDD 105) (S308), and the process proceeds to step S306. Return.

  When the color gamut selection list box 205 shown in FIG. 2 is operated, the number corresponding to the selected color gamut is stored in a predetermined area of the main memory 102 (S309), and the process returns to step S306.

  When the check box 206 shown in FIG. 2 is operated, the display of the 3D object data of the color gamut corresponding to the selected color gamut number stored in the main memory 102 is set to ON or OFF (S310), Return to S306.

  When the color gamut deletion button 207 shown in FIG. 2 is pressed, the 3D object data of the color gamut corresponding to the selected color gamut number stored in the main memory 102 is deleted from the main memory 102 (or HDD 105) ( S311), the process returns to step S306.

  When a mouse operation in the 3D display area 203 shown in FIG. 2 is detected, zoom-in, zoom-out, and rotation processing of the 3D object displayed in the 3D display area 203 is performed according to the user's mouse operation (S312 ), The process returns to step S306.

  When the end button 208 shown in FIG. 2 is pressed, an end operation such as memory release is performed, and then the color analysis application operation ends.

[Setting of B-spline body for color gamut calculation (S303)]
Next, the coefficient and basis function calculation process (S303) of the B-spline body for color gamut calculation will be described. For the following description, the formula of the B-spline body for color calculation will be described in advance. A B-spline body for color gamut calculation is defined by equation (1).
λ = Σ _i Σ _j Σ _k cλ _ijk N _ri (rr) N _gj (gg) N _bk (bb)
a = Σ _i Σ _j Σ _k ca _ijk N _ri (rr) N _gj (gg) N _bk (bb)… (1)
b = Σ _i Σ _j Σ _k cb _ijk N _ri (rr) N _gj (gg) N _bk (bb)
Where rr, gg, and bb are RGB values
λ, a, b are L * a * b * values
N _r is the basis function in the R-axis direction
N _g is the basis function in the G-axis direction
N _b is the basis function in the B-axis direction
cλ _ijk , ca _ijk , cb _ijk are coefficients
Suffixes i, j, k attached to N _r , N _g , N _b are
Basis function number in the basis for each axis

  FIG. 5 is a flowchart for explaining the calculation processing (S303) of the coefficient and basis function of the B-spline body for color gamut calculation.

First, from the color distribution data represented by the data structure shown in FIG. 4, the correspondence between RGB values and L * a * b * values is acquired for all sets (S501). Thereafter, the correspondence between the RGB value and the L * a * b * value, the RGB value of the i-th editing color as rr _i , gg _i , bb _i , and the L * a * b * value as λ _i , a _i , b _This is described as _i .

Next, a basis function of the B-spline body is calculated and stored in the main memory 102 (S502). For example, if the basis functions N _r , N _g , and N _b are all third-order B-spline bases and the number of nodes is 4, all of the four-node bases ξ0 to ξ3 as shown in FIG. Become a function. Incidentally, FIG. 6 shows the basis functions N _r of R axis. In the following, the basis functions will be described as B-spline bases with three positions of four nodes.

  Next, each coefficient of the B-spline body is calculated using the calculated basis function and the distribution data indicating the correspondence between the RGB value and the L * a * b * value acquired from the color distribution data shown in FIG. (S503). This process is performed by solving the matrix equation f = MC using LU decomposition for each of the L * component, the a * component, and the b * component, and calculating each coefficient. Hereinafter, the coefficient calculation by the above equation will be described in detail.

First, the s-row t-column component m _st of the matrix M is calculated as follows.
m _st = N _ri (rr _s ) N _gj (gg _s ) N _bk (bb _s )… (2)
Where t = 25 (i-1) + 5 (j-1) + k
i, j, k are integers from 1 to 5

  Note that the relationship between t and i, j, k varies depending on the number of nodes and the order of basis functions. For example, in the case of a six-node B-base spline at the third position, the relationship is t = 49 (i-1) +7 (j-1) + k.

Next, calculation of the coefficients cλ _ijk , ca _ijk , and cb _ijk will be described. First, in order to calculate the coefficient cλ _ijk , the s row component fλ _s of the column vector fλ is calculated as follows to determine the column vector fλ.
fλ = [λ ₁ , λ ₂ ,…, λ ₁₂₄ , λ ₁₂₅ ]
cλ = [cλ ₁₁₁ , cλ ₁₁₂ ,…, cλ ₁₁₅ , cλ ₁₂₁ ,
…, Cλ ₁₅₅ , cλ ₂₁₁ ,…, cλ ₅₅₄ , cλ ₅₅₅ ]… (3)
fλ = M ・ cλ

Next, in order to calculate the coefficient ca _ijk , the following matrix equation is solved using LU decomposition.
fa = [a ₁ , a ₂ ,…, a ₁₂₄ , a ₁₂₅ ]
ca = [ca ₁₁₁ , ca ₁₁₂ ,…, ca ₁₁₅ , ca ₁₂₁ ,
…, Ca ₁₅₅ , ca ₂₁₁ ,…, ca ₅₅₄ , ca ₅₅₅ ]… (4)
fa = M ・ ca

Next, in order to calculate the coefficient cb _ijk , the following matrix equation is solved using LU decomposition.
fb = [b ₁ , b ₂ ,…, b ₁₂₄ , b ₁₂₅ ]
cb = [cb ₁₁₁ , cb ₁₁₂ ,…, cb ₁₁₅ , cb ₁₂₁ ,
…, Cb ₁₅₅ , cb ₂₁₁ ,…, cb ₅₅₄ , cb ₅₅₅ ]… (5)
fb = M ・ cb

  The calculated coefficient is stored in the main memory 102 (S504).

[Generate 3D objects (S305)]
Assuming that the surface of the RGB cube is the color gamut boundary, the six faces constituting the color gamut are calculated as the color gamut as follows.

● R = 0 plane λ = Σ _j Σ _k cλ _1jk N _gj (gg) N _bk (bb)
a = Σ _j Σ _k ca _1jk N _gj (gg) N _bk (bb)… (6)
b = Σ _j Σ _k cb _1jk N _gj (gg) N _bk (bb)
● R = 255 plane λ = Σ _j Σ _k cλ _5jk N _gj (gg) N _bk (bb)
a = Σ _j Σ _k ca _5jk N _gj (gg) N _bk (bb)… (7)
b = Σ _j Σ _k cb _5jk N _gj (gg) N _bk (bb)
● G = 0 plane λ = Σ _i Σ _k cλ _i1k N _ri (rr) N _bk (bb)
a = Σ _i Σ _k ca _i1k N _ri (rr) N _bk (bb)… (8)
b = Σ _i Σ _k cb _i1k N _ri (rr) N _bk (bb)
● G = 255 plane λ = Σ _i Σ _k cλ _i5k N _ri (rr) N _bk (bb)
a = Σ _i Σ _k ca _i5k N _ri (rr) N _bk (bb)… (9)
b = Σ _i Σ _k cb _i5k N _ri (rr) N _bk (bb)
● B = 0 plane λ = Σ _i Σ _j cλ _ij1 N _ri (rr) N _gj (gg)
a = Σ _i Σ _j ca _ij1 N _ri (rr) N _gj (gg)… (10)
b = Σ _i Σ _j cb _ij1 N _ri (rr) N _gj (gg)
● B = 255 plane λ = Σ _i Σ _j cλ _ij5 N _ri (rr) N _gj (gg)
a = Σ _i Σ _j ca _ij5 N _ri (rr) N _gj (gg)… (11)
b = Σ _i Σ _j cb _ij5 N _ri (rr) N _gj (gg)
As described above, the surface of the color gamut can be calculated by using the coefficient of the formula of the B spline body as it is as the coefficient of the formula of the B spline surface. The calculated six B-spline surfaces are stored in the main memory 102 as surface data. Then, the surface data stored in the main memory 102 is read and converted to smooth shading display data for 3D object data.

  In this way, the color gamut can be calculated accurately and smoothly. Furthermore, as long as the appropriate number of RGB values and L * a * b * values can be obtained, even if no L * a * b * values on the surface of the RGB color gamut can be obtained, nonlinear operations are performed from the correspondence. It becomes possible to estimate the color gamut. Since this non-linear operation reflects the trend of color gamut change, the calculated color gamut is highly accurate.

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

  In the second embodiment, the color gamut calculation process in step S304 and the 3D object generation process in step S305 are changed, and the color gamut expression by the triangular patch is performed.

  FIG. 7 is a flowchart showing the color gamut calculation process (S304).

  First, an initialization operation such as securing a working memory area and initializing variables is performed (S701), one triangular patch is selected according to an appropriate order, and RGB values of three vertices are acquired (S702). Here, the RGB values at the three vertices are located at the color gamut boundary in the RGB color space, that is, at the surface of the RGB cube.

Next, the base function and coefficient value of the B-spline body for color gamut calculation are acquired from the main memory 102, and the RGB values at the three vertices are converted into L * a * b * values using the following equation (S703).
λ = Σ _{i = 1} ⁵ Σ _{j = 1} ⁵ Σ _{k = 1} ⁵ cλ _ijk N _ri (rr) N _gj (gg) N _bk (bb)
a = Σ _{i = 1} ⁵ Σ _{j = 1} ⁵ Σ _{k = 1} ⁵ ca _ijk N _ri (rr) N _gj (gg) N _bk (bb)… (12)
b = Σ _{i = 1} ⁵ Σ _{j = 1} ⁵ Σ _{k = 1} ⁵ cb _ijk N _ri (rr) N _gj (gg) N _bk (bb)
Where rr, gg, and bb are RGB values
λ, a, b are L * a * b * values
N _r is the basis function in the R-axis direction
N _g is the basis function in the G-axis direction
N _b is the basis function in the B-axis direction
cλ _ijk , ca _ijk , cb _ijk are coefficients
Suffixes i, j, k attached to N _r , N _g , N _b are
Basis function number in the basis for each axis

  Next, the calculated L * a * b * values of the three vertices are stored in a predetermined address of the main memory 102 in the data structure shown in FIG. 8 (S704). The total number of triangular patches is described at the beginning of the data structure shown in FIG. 8, and then a set of L * a * b * values at the three vertices of each triangular patch is described as color gamut data for the total number of triangular patches. .

  Next, it is determined whether or not the color gamut has been calculated for all the triangular patches (S705), and if not completed, the processing from step S702 to S704 is repeated. When the calculation of the color gamut is completed, an end operation such as release of the working memory is performed (S706).

  In the subsequent 3D object generation process in step S305, the color gamut data of the triangular patch stored in the main memory 102 is read and converted into polygon data for 3D object data. Accordingly, the color gamut displayed in the pseudo three-dimensional display in the three-dimensional display area 203 shown in FIG. 2 can recognize the patch boundary as shown in FIG.

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

  In the first embodiment, in the setting process of the B spline body for color gamut calculation in step S303, the B spline body is determined so as to interpolate between a plurality of color signal values described in the color distribution data. In Example 3, a B-spline body is set so that a curved surface that approximates the sequence of the plurality of color signal values (or a curved surface connecting the plurality of color signal values is smoothed). Hereinafter, the flowchart of FIG. 5 which is a difference will be described.

  First, as in the first embodiment, the correspondence between RGB values and L * a * b * values is acquired for all sets from the color distribution data represented by the data structure shown in FIG. 4 (S501).

  Next, after appropriately determining the nodes, a basis function is calculated based on the nodes and stored in the main memory 102 (S502). As a method for determining a node, the number of nodes and coordinates may be determined in advance, or the node may be determined based on a change in L * a * b * value. However, in the following description, each basis function will be described as a four-node three-position B-spline basis.

  Next, using the calculated basis function and the distribution data indicating the correspondence between RGB values and L * a * b * values obtained from the color distribution data shown in FIG. Then, each coefficient of the B spline body is calculated so that the sum of the distances of the colors described in the color distribution data is minimized (S503). This process is performed by solving the matrix equation f = MC for each of the L * component, the a * component, and the b * component using LU decomposition. Hereinafter, the coefficient calculation by the above equation will be described in detail.

First, the s-row t-column component m _st of the matrix M is calculated as follows.
m _st = Σ _x (N _ri (rr _x ) N _gj (gg _x ) N _bk (bb _x )
・ N _rl (rr _x ) N _gm (gg _x ) N _bn (bb _x )}… (13)
Here, s = 25 (i-1) + 5 (j-1) + k holds between i, j, and k with respect to s.
t = 25 (l-1) + 5 (m-1) + n between l, m and n with respect to t

  The above relationship varies depending on the number of nodes and the order of basis functions.

Next, in order to calculate the coefficient cλ _ijk , the s row component fλ _s of the column vector fλ is calculated as follows to determine the column vector fλ.
fλ _s = Σ _x N _ri (rr _x ) N _gj (gg _x ) N _bk (bb _x ) ・ λ _x … (14)

Again, as before, s = 25 (i-1) + 5 (j-1) + k holds between s, i, j, and k, but this relationship is related to the number of nodes and basis functions. It depends on the order of. Then, using LU decomposition, the following matrix equation is solved to calculate the coefficient cλ _ijk .
cλ = [cλ ₁₁₁ , cλ ₁₁₂ ,…, cλ ₁₁₅ , cλ ₁₂₁ ,
…, Cλ ₁₅₅ , cλ ₂₁₁ ,…, cλ ₅₅₄ , cλ ₅₅₅ ]… (15)
fλ = M ・ cλ

Next, in order to calculate the coefficient ca _ijk , the s row component fa _s of the column vector fa is calculated as follows to determine the column vector fa.
fa _s = Σ _x N _ri (rr _x ) N _gj (gg _x ) N _bk (bb _x ) ・ a _x … (16)

After this, the following matrix equation is solved using LU decomposition.
ca = [ca ₁₁₁ , ca ₁₁₂ ,…, ca ₁₁₅ , ca ₁₂₁ ,
…, Ca ₁₅₅ , ca ₂₁₁ ,…, ca ₅₅₄ , ca ₅₅₅ ]… (17)
fa = M ・ ca

Next, in order to calculate the coefficient cb _ijk , the s row component fb _s of the column vector fb is calculated as follows to determine the column vector fb.
fb _s = Σ _x N _ri (rr _x ) N _gj (gg _x ) N _bk (bb _x ) ・ b _x … (18)

After this, the following matrix equation is solved using LU decomposition.
cb = [cb ₁₁₁ , cb ₁₁₂ ,…, cb ₁₁₅ , cb ₁₂₁ ,
…, Cb ₁₅₅ , cb ₂₁₁ ,…, cb ₅₅₄ , cb ₅₅₅ ]… (19)
fb = M ・ cb

  The calculated coefficient is stored in the main memory 102 (S504).

[Modification]
Replacement of B-spline basis functions with other piecewise polynomials in solid representation In the first, second, and third embodiments, examples of using B-splines as basis functions in solid representation have been described. However, as a basis function, any piecewise function such as rational B spline, non uniform rational B spline, Bezier, rational Bezier, etc. can be used. Since it is more desirable that the locality of the basis function exists, the embodiment has been described using the most typical B-spline.

● Color space to be used In Examples 1, 2, and 3, there is no restriction on the color space, and CMYK color space, L * a * b * color space, JCH color space, XYZ color space, xy color space, etc. can be used. it can. Further, the present invention can be applied to ink color separation, and a 6-dimensional color space obtained by adding light cyan and light magenta to CMYK, and an 8-dimensional color space obtained by adding red ink and green ink can also be used. Further, the color space given to the equation and the color space calculated from the equation may be the same color space.

Color Gamut Representation In the second embodiment, the triangular patch is used for the color gamut representation, but this can be extended to the polygon representation.

[Other embodiments]
Note that the present invention can be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, and a printer), and a device (for example, a copying machine and a facsimile device) including a single device. You may apply to.

  Also, an object of the present invention is to supply a storage medium (or recording medium) on which a program code of software that realizes the functions of the above-described embodiments is recorded to a system or apparatus, and the computer (or CPU or Needless to say, this can also be achieved by the MPU) reading and executing the program code stored in the storage medium. In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code 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 storage 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 determined based on the instruction of the program code. Needless to say, the CPU of 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 storage medium, the storage medium stores program codes corresponding to the flowcharts described above.

A block diagram showing a configuration example of a color processing apparatus of an embodiment, The figure which shows the user interface which the gamut analysis application displays, State transition diagram explaining the operation of the color analysis application, A diagram showing the data structure of color distribution data, A flowchart for explaining the calculation processing of the coefficient and basis function of the B-spline body for color gamut calculation, A diagram representing a B-spline basis function, Flowchart showing the color gamut calculation processing of Example 2, The figure which shows the data structure of the triangular patch data expressing a color gamut, FIG. 6 is a diagram illustrating a pseudo three-dimensional display of a color gamut in the second embodiment.

Claims (10)

A color processing method for calculating a color gamut of a predetermined color system by an image processing apparatus,
Set the multiple sum operation with a piecewise polynomial of the same multiplicity as the number of dimensions of the first color system as a basis function,
Based on the data indicating the combination of the plurality of color signal values of the first color system and the plurality of color signal values of the second color system that are the colorimetric results for the color signal values, Find the coefficient
A color processing method comprising: calculating a color gamut of the second color system corresponding to the color gamut of the first color system using the multiple sum operation. A color processing method for calculating a color gamut of a predetermined color system by an image processing apparatus,
Set the multiple sum operation with a piecewise polynomial of the same multiplicity as the number of dimensions of the first color system as a basis function,
Based on the data indicating the combination of the plurality of color signal values of the first color system and the plurality of color signal values of the second color system that are the colorimetric results for the color signal values, Obtaining a coefficient of the piecewise polynomial corresponding to a curved surface approximating a plurality of signal values of the color system or a curved surface connecting the plurality of color signal values;
A color processing method comprising: calculating a color gamut of the second color system corresponding to the color gamut of the first color system using the multiple sum operation.   3. The color gamut calculation according to claim 1, wherein the color gamut is calculated by calculating a color gamut boundary of the second color system corresponding to a color gamut boundary of the first color system. Color processing method.   The calculation of the color gamut is to calculate the color gamut as a color gamut expression using a plurality of points obtained by converting a plurality of points located at the color gamut boundary of the first color system to the second color system. 3. The color processing method according to claim 1, wherein the color processing method is performed.   5. The color processing method according to claim 4, wherein the color gamut expression is a triangular patch expression or a polygon expression.   6. The color processing method according to claim 1, further comprising generating a pseudo three-dimensional display object corresponding to the boundary of the color gamut.   7. A program that controls an image processing device to realize the color processing according to claim 1.   8. A recording medium on which the program according to claim 7 is recorded. An image processing apparatus for calculating a color gamut of a predetermined color system,
Setting means for setting a multiple sum operation using a piecewise polynomial of the same multiplicity as the number of dimensions of the first color system as a basis function;
Based on the data indicating the combination of the plurality of color signal values of the first color system and the plurality of color signal values of the second color system that are the colorimetric results for the color signal values, An arithmetic means for obtaining a coefficient;
A color processing apparatus comprising: calculating means for calculating a color gamut of the second color system relative to a color gamut of the first color system using the multiple sum operation. An image processing apparatus for calculating a color gamut of a predetermined color system,
Setting means for setting a multiple sum operation using a piecewise polynomial of the same multiplicity as the number of dimensions of the first color system as a basis function;
Based on the data indicating the combination of the plurality of color signal values of the first color system and the plurality of color signal values of the second color system that are the colorimetric results for the color signal values, An arithmetic means for obtaining a coefficient of the piecewise polynomial corresponding to a curved surface approximating a plurality of signal values of a color system or a curved surface connecting the plurality of color signal values;
A color processing apparatus comprising: calculating means for calculating a color gamut of the second color system corresponding to the color gamut of the first color system using the multiple sum operation.

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