JP2002344758A - Data processing method, data processor, data processing program, and computer-readable recording medium with the data processing program recorded thereon - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a data processing method, with which a prescribed number of data are estimated from a small number of data so as to easily generate a highly accurate three-dimensional lookup table. SOLUTION: Data by N-gradation each in 7 colors, comprising primary colors CMY, secondary colors BRG and a ternary color K are measured and the resulting data, XYZ data, are inputted to a data processing unit (S401). The inputted XYZ data are subjected to matrix conversion into RGB data (S403). Respective transmission coefficients ϕ for all the converted data are calculated (S405), and a desired color value is calculated, by using the transmission coefficients ϕ(S407). Since the desired color value is calculated by using products of the transmission coefficients of the primary colors, the color values regarding the combinations of the transmission coefficients by N-gradation each of the primary colors can be obtained. Thus, finally (N×N×N) sets of color values are calculated.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a data processing method, a data processing apparatus, a data processing program, and a computer-readable recording medium on which the program is recorded, and more particularly to a method for creating an LUT from a small number of data. The present invention relates to a data processing method, a data processing device, a data processing program, and a computer-readable recording medium storing the program, which can calculate a desired number of data.

[0002]

2. Description of the Related Art Conventionally, as a method for converting input image data expressed in a certain color space into output image data in a different color space, data is directly converted using a look-up table (hereinafter abbreviated as "LUT"). A conversion method is known.

For example, when an input image read by a scanner is output by an output device such as a printer, X
A look-up table in which data represented in the YZ space and data represented in the CMY space are recorded in association with each other is referred to, and the data is directly converted from the XYZ data to the CMY data.

Using an LUT, it is possible to convert input image data into appropriate output image data with extremely high accuracy.

The LUT used here is a table of output image data corresponding to input image data.
For example, data in the XYZ color space corresponding to the data corresponding to the positions of the lattice points in the CMY color space represented in three dimensions are registered. The number of grid points is (N × N × N) in the case of N gradations. Therefore, LU
In the case of creating T, color values for each of (N × N × N) points in order to directly register input color space data (XYZ data) and output color space data (CMY data) You need to get Usually, a method of actually measuring a color chart is used to obtain a color value.

[0006]

However, the above-described LUT has a drawback that the operation of measuring data is very complicated. That is, generally, CMY
Since the number of gradations required for the color space is about 10, approximately 10 × 10 × 10 = 1000 lattice points, that is, the number of data is registered in the LUT. Therefore, it was necessary to measure the color value for each of the huge number of points.

Therefore, when creating an LUT, a method for obtaining a large amount of data with as few grid points as possible by estimating a color is considered. As a color estimation method, for example, the Neugebauer method or the like can be used. This method is
This is a method of estimating a color based on color data of primary colors, secondary colors, and tertiary colors of color materials and an area ratio. However, it is necessary to obtain the area ratio of the color material, which is relatively complicated, and the accuracy of the Lab color difference is about 10 which is not very good.

The present invention has been conceived in view of such circumstances, and has as its object to easily create a high-precision three-dimensional lookup table by estimating a predetermined number of data from a small number of data. It is an object of the present invention to provide a data processing method, a data processing device, a data processing program, and a computer-readable recording medium recording the program.

[0009]

According to an aspect of the present invention, there is provided a three-dimensional lookup system for recording data of a first color space and data of a second color space in association with each other. The data processing method for creating a table includes: an acquiring step of acquiring data of a second color space corresponding to data of N gradations of M (M ≧ 3) colors in a first color space; A first calculation step of calculating the transmittance of the reference white color in the first color space for the N gradations of each of the M colors using the obtained data; A second calculation step of calculating desired data in the second color space using data in the second color space corresponding to the reference white, wherein the desired data is M types in the first color space. Given of the colors Represented using the product of transmittance for each type of color, the second calculation step, 3
It is characterized in that (N × N × N) desired data is obtained by calculating a combination of transmittances for N gradations of each type of color.

According to the present invention, (M × N) pieces of data in the second color space corresponding to data for N gradations of M colors in the first color space are obtained. (If the first gradation of each color is the same data, the number of data is (M × N−
(M-1)). Then, using the obtained data, the transmittances of the colors for the reference white in the first color space are calculated for the N gradations of each of the M colors. Here, the transmittance for a certain gradation of a certain color means the ratio of the data of the second color space for a certain gradation of a certain color to the data of the second color space for the reference white. .

Then, desired data in the second color space is calculated using the calculated transmittance and data in the second color space corresponding to the reference white. The desired data is
It is represented using the product of the transmittance of each of three predetermined colors in the first color space. Therefore, the desired data can be easily and appropriately estimated without obtaining the area ratio of the color and the like.

The desired data is calculated with respect to the combinations of the transmittances for the N gradations of the three colors, so that (N × N × N) data can be finally obtained. . Therefore, (M × N) (or (M × N
− (M−1))), it is possible to easily obtain (N × N × N) pieces of data necessary for creating a three-dimensional lookup table.

Therefore, it is possible to provide a data processing method capable of easily creating a high-precision three-dimensional lookup table by estimating a predetermined number of data from a small number of data.

[0014] Preferably, the three predetermined colors are primary colors serving as references in the first color space. Since the three predetermined colors are primary colors serving as references in the first color space, it is possible to calculate desired data appropriately and easily based on the primary colors.

Preferably, the M types of colors include a secondary color in addition to the three types of primary colors in the first color space, and the second calculation step includes the first color calculated by the first calculation step. A first correction coefficient calculating step of obtaining a first correction coefficient using the transmittance of the secondary color and the secondary color;
And a first correction step of performing a correction by multiplying the product of the transmittances of the three types of colors by the correction coefficient of the three colors.

According to the present invention, the M types of colors include the secondary colors in addition to the three types of primary colors in the first color space.
Then, a first correction coefficient using the transmittance of the primary color and the secondary color is obtained, and the correction is performed by multiplying the correction coefficient by the product of the transmittance of each of the three colors. Since the correction is also performed using the transmittance of the secondary color, as the desired data, an error is reduced, and data with higher accuracy is calculated.

Preferably, the M kinds of colors further include a tertiary color in the first color space, and the second calculating step includes:
A second correction coefficient calculation step of obtaining a second correction coefficient using the transmittance of the primary color and the tertiary color calculated in the first calculation step, and three types of the obtained second correction coefficient. A second correction step of performing a correction by multiplying the product of the transmittances of the respective colors. The first correction coefficient calculation step and the second correction coefficient calculation step are performed for the data of the first area of the first color space. Desired data is calculated in one correction step, and desired data is calculated in a second correction coefficient calculation step and a second correction step for data in a second area of the first color space.

According to the present invention, the M colors further include the tertiary colors in the first color space. Then, a second correction coefficient using the transmittance of the primary color and the tertiary color is obtained, and the correction is performed by multiplying the product of the transmittance of each of the three colors. It should be noted that desired data is calculated using the correction coefficient based on the secondary color for the data of the first area of the first color space, and the data of the second area, which is the other area, is calculated. , Desired data is calculated using a correction coefficient for the tertiary color.

For this reason, for example, in a region where the mixing ratio of three types of primary colors is high, data calculation using a correction coefficient based on a tertiary color is performed, and in other regions, a correction coefficient based on a secondary color is calculated. For example, it is possible to calculate highly accurate data with less error according to the characteristics of each color, for example, by using the calculated data.

Preferably, the second color space is CIE-XY
Z color space, and the first calculation step is that the acquired C
The data in the IE-XYZ color space is converted into the data in the RGB color space, the respective transmittances are calculated using the converted data, and the data conversion method is based on the RGB color space calculated in the second calculation step. Desired data of CIE-X
The method further includes an inverse conversion step of converting the data into data in the YZ color space.

According to the present invention, the second color space is CIE
-XYZ color space, and the acquired data in the CIE-XYZ color space is converted into data in the RGB color space. CIE stands for Commission Internationale de I'Eclaira
ge (International Commission on Illumination), and XYZ are tristimulus values of color. Then, the respective transmittances are calculated using the converted RGB color space data. Desired data obtained as data in the RGB color space is CIE
-Inversely converted to data in XYZ color space.

In order to calculate the transmittance and use it to obtain desired data, it is more appropriate to handle RGB data than to CIE-XYZ data. Therefore, the CIE-XYZ data is first converted to RGB data. Therefore, CIE-XY obtained by a general color value measuring device or the like
By directly using the data in the Z color space, desired data can be appropriately acquired.

Preferably, the acquiring step acquires (M × K) pieces of data in the second color space corresponding to data of M kinds of K (K <N) gradations in the first color space. , By performing an interpolation operation using the obtained data, data corresponding to the data of N gradations is obtained.

According to the present invention, (M × K) pieces of data in the second color space corresponding to data of M types of K (K <N) gradations in the first color space are obtained. And
Using the obtained data, an interpolation calculation of the data of K gradations is performed, and the data corresponding to the data of N gradations (M ×
N) pieces of data are obtained. Therefore, a desired (N × N) necessary for creating a look-up table based on a smaller number of data (M × K) is used.
× N) data can be easily calculated.

According to another aspect of the present invention, a data processing apparatus for creating a three-dimensional look-up table for recording data of a first color space and data of a second color space in association with each other includes: Acquiring means for acquiring data of the second color space corresponding to data of N gradations of M (M ≧ 3) types of colors in the first color space, and a first method using the acquired data. A first calculating means for calculating the transmittance of the color for the reference white in the color space of N colors for each of the M types of colors, and a second color space corresponding to the calculated transmittance and the reference white. Second calculating means for calculating desired data in the second color space using the data, wherein the desired data is a predetermined three of the M colors in the first color space. Expressed using the product of transmittance for each The second calculation means obtains (N × N × N) desired data by calculating a combination of transmittances for N gradations of each of the three types of colors. .

According to the present invention, (M × N) pieces of data in the second color space corresponding to data for N gradations of M colors in the first color space are obtained. Then, using the acquired data, the transmittances of the colors for the reference white in the first color space are calculated for the N gradations of each of the M types of colors. Then, the desired data in the second color space is calculated using the calculated transmittance and the data in the second color space corresponding to the reference white. The desired data is represented using the product of the transmittance of each of the three predetermined colors in the first color space. Therefore, the desired data can be easily and appropriately estimated without obtaining the area ratio of the color and the like.

Since the desired data is calculated for the combinations of the transmittances for the N gradations of the three colors, (N × N × N) data are finally obtained. Become. Therefore, it is possible to easily obtain (N × N × N) data necessary for creating a three-dimensional lookup table only by obtaining (M × N) data.

Therefore, by estimating a predetermined number of data from a small number of data, it is possible to provide a data processing apparatus capable of easily creating a high-precision three-dimensional lookup table.

According to still another aspect of the present invention, there is provided a data processing method for creating a three-dimensional lookup table for recording data of a first color space and data of a second color space in association with each other. The data processing program to be executed by the computer is M (M ≧ M) in the first color space.
3) Acquisition step of acquiring data of the second color space corresponding to data of N gradations of the types of colors, respectively, and transmission of the color to the reference white in the first color space using the acquired data. A first calculation step of calculating the rate for N gradations of each of the M colors, and a second color space using the calculated transmittance and data of the second color space corresponding to the reference white color And a second calculation step of calculating desired data in the first color space. The desired data is obtained by multiplying the transmittance of each of three predetermined colors among the M colors in the first color space by the product. In the second calculation step, (N × N × N) pieces of desired data are obtained by calculating a combination of transmittances for N gradations of each of the three types of colors. It is characterized by the following.

Therefore, by estimating a predetermined number of data from a small number of data, it is possible to provide a data processing program capable of easily creating a high-precision three-dimensional lookup table.

According to still another aspect of the present invention, a computer-readable recording medium records the above-described data processing program.

Therefore, a computer-readable recording medium on which a data processing program capable of easily creating a high-precision three-dimensional lookup table by estimating a predetermined number of data from a small number of data is provided. Can be provided.

[0033]

Embodiments of the present invention will be described below in detail with reference to the drawings.

The data processing method according to the embodiment of the present invention can be realized by executing a data processing program on a computer such as a personal computer or a workstation.

FIG. 1 shows a computer, which is an example of a data processing apparatus 100 according to the present embodiment, having a color value measuring device 20.
It is a figure showing an example connected to 0. Here, the color value data sent from the color value measuring device 200 is taken into the data processing device 100 and is appropriately processed there.

Referring to FIG. 1, data processing device 100
Is a main body 11, a magnetic tape device 13, a CD-ROM
(Compact Disc-Read Only Memory) device 17 and CR
A display device 12, such as a T, a keyboard 15, and a mouse 16
And a modem 19. A magnetic tape 14 is mounted on the magnetic tape device 13, and a CD-ROM 18 is mounted on the CD-ROM device 17. The main body 11 of the data processing apparatus 100 and the color value measuring device 200 are
Etc. are connected via an interface 50.

FIG. 2 shows the configuration of the computer (data processing device 100) in the form of a functional block diagram. Referring to this figure, as is well known, the main body 11 of the computer includes:
CPU (Central Processing Unit) 20 and ROM (R
ead Only Memory) 21 and RAM (Random Access Mem)
ory) 22 and a hard disk drive 23. These are mutually connected by a bus.

The data processing program may be installed in a hard disk in a computer in advance, or may be recorded on a removable recording medium such as a CD-ROM or a magnetic tape. In any case, the data processing program is recorded on a computer-readable recording medium.

When the program is recorded on a removable recording medium, the recorded program is stored in the magnetic tape device 1.
3. The data is read from the recording medium by the CD-ROM device 17 or the like and is temporarily stored in the hard disk device 23. After that, the program is loaded from the hard disk device 23 to the RAM 22, and the CPU 20 controls the execution of the program.

As a computer-readable recording medium, a tape system such as a magnetic tape or a cassette tape, a magnetic disk (a flexible disk, a hard disk device, etc.) and an optical disk (CD-ROM / MO / MD)
/ DVD etc., IC card (including memory card) and optical card etc., mask ROM, EPROM, EEPROM, flash RO
A medium that fixedly holds the program, such as a semiconductor memory such as M, may be used.

Further, the data processing program may be downloaded from a network via the communication modem 19. When the program is downloaded from the network as described above, the download program is stored in the computer main body 11 in advance, or is installed in the main body 11 in advance from another recording medium or the like.

The content stored in the recording medium is not limited to a program but may be data.

Next, a case where the data processing program starts up and data processing is actually performed will be described. When the data processing program starts, for example,
The software once stored in the hard disk device 23 is loaded into the RAM 22. FIG. 3 is a diagram illustrating a configuration of software when the data is read into the RAM 22.

Referring to FIG. 4, RAM 22 stores a color chart data input unit 31 for inputting XYZ data sent from color value measuring device 200 and an XYZ data sent from color chart data input unit 31. An RGB value conversion unit 33 that converts RGB data, an LUT calculation unit 35 that performs an operation for creating an LUT using the RGB data, and an XYZ value conversion unit that converts RGB data obtained as a calculation result into XYZ data 37 are included.

A plurality of chart color charts of the color chart 300 are measured by the color value measuring device 200 and sent to the data processing apparatus 100 as XYZ data. The color chart measured here is C (cyan: cyan) M (magenta: magenta) Y (yellow: yellow), which is the primary color in the CMY color space, and R (red: red) G (which is the secondary color) green: green) B (blue: blue) and tertiary color K (bl)
ack: black), which is a color chart for each of N gradations of seven color materials.

Therefore, the number of color charts is (7 × N−
6) Count. Here, the reason why 6 is subtracted is to avoid duplication of white values corresponding to the first gradation for each color.

The transmitted (7 × N−6) XYZ data is input from the color chart data input unit 31 and converted into (7 × N−6) RGB data by the RGB value conversion unit 35. Is done.

Next, using the RGB data, L
The UT calculation unit 35 calculates (N × N × N) RGB data. Details will be described later. And
In the XYZ value converter 37, (N × N × N) RGs
The B data is converted again into (N × N × N) XYZ data.

In this way, from the input data for the (7 × N−6) color chips, the (N × N × N)
Is calculated, and a desired LUT is created using the calculated data.

Next, the algorithm of the data processing method will be described. FIG. 4 is a flowchart showing the flow of data processing in the present embodiment. Referring to this figure, first, in step S401, the color value measuring device 200
Is input.

For example, the chart color charts to be measured include basic three color materials C, M, Y, secondary colors B, R, G,
And the seven color materials of the tertiary color K for five gradations. According to the color value measuring device 200, these 7 × 5−6 = 29
The data of each chart color chart is measured and input to the data processing apparatus 100 as XYZ data.

When the input of the measurement data is completed, next, in step S403, the R of the input XYZ data is
Matrix conversion to GB data is performed. here,
The concept of a color value absorption model is used to determine the color value. In other words, the color value is determined by each color material absorbing the color value of the white point with the color value of the white point of the underlying paper as the maximum color value.

FIG. 5 is a conceptual diagram for explaining this absorption model. Referring to this figure, as shown by arrow A,
The color value of the white point (R _W , G _W , B _W ) indicates the maximum value among the color materials. Then, it is assumed that the three color materials of CMY are arranged in layers on the paper surface, and the color values of the white point are absorbed by the C layer, the M layer, and the Y layer, respectively. Accordingly, the transmission coefficients of the respective layers are φ _C , φ _M , and φ _Y , and the product of these and the maximum color value (R _W , G _W , B _W ) is the color value of a target color.

When such an absorption model is used, RGB values having band characteristics as shown in FIG. 7 are used as color values rather than tristimulus values XYZ having band characteristics as shown in FIG. It is more convenient. So, first,
The input XYZ data is subjected to matrix conversion into RGB data using the following equation.

[0055]

(Equation 1)

When all the XYZ data are converted into RGB data, the data is converted into a transmission coefficient in step S405. That is, the transmission coefficient φ is calculated for each of the 29 pieces of color chart data. Specifically, it is expressed by the ratio between the RGB value of the target color material and the RGB value of the white point, as in the following equation.

Φ _rj = R _j / R _W , φ _gj = G _j / G _W , φ _bj = B _j / B _W. Here, the suffix j is each color material. That is, in the present color chart chart, there are seven colors of C, M, Y, R, G, B, and K. The subscript W means a white point.

FIG. 8 is a flowchart showing details of the transmission coefficient conversion process (step S405) of FIG. FIG.
, The transmission coefficient conversion process is performed first in step S80.
At 1, the RGB value of the i-th gradation of the color material j is input. Next, in step S803, the transmission coefficient φ of the target color material j is determined.

For example, first, the RGB values of the first gradation for C (cyan) are input, and the transmission coefficients (φ _rC (1), φ _gC (1), φ _bC (1)) = (R
_{C (1) / R W,} G C (1) / G W, B C (1) / B W) is calculated. Here, since transmission coefficient data for five gradations is required (“no” in step S805), the process returns to step S801 again, and the next gradation (i =
The RGB values of 2) are input. In this way, when the transmission coefficients for all gradations, that is, 5 gradations, are calculated for C (“yes” in step S805), the transmission coefficient conversion processing is similarly performed for the next color material M. Is performed (“no” in step S807).

In this way, all the color materials (C, M,
(Y, R, G, B, K) transmission coefficient calculation for all gradations is completed.
The above processing (step S801, step S801)
803) is repeated (step S805, step
S807). Therefore, this time, each of the seven color materials
For five gradations, that is, 29 transmission coefficients (φ_rj(I), φ _gj
(I), φ_bj(I)) will be calculated.

When the transmission coefficients φ for all gradations of all color materials are obtained (“yes” in step S807), the process returns to the main routine of FIG. The calculated transmission coefficient φ is temporarily stored in a predetermined area of the memory.

When the transmission coefficient conversion process is completed, next, in step S407, a color value calculation process is performed. That is, (N × N × N) color values are obtained from (M × N-6) color values using the transmission coefficient φ obtained in step S405. Here, M is the number of types of coloring materials,
N is the number of gradations.

FIG. 9 shows the color value calculation process (step S
407) is a flowchart illustrating the details of the process. Referring to FIG. 9, first, in step S901, the transmission coefficients (φ _rC (c), φ _gC (c), φ _g
bC (c)) is read from the memory. Next, in step S903, the transmission coefficient (φ
_rM (m), φ _gM (m), φ _bM (m)), and in step S905, the transmission coefficient (φ
_rY (y), _φgY (y), _φbY (y)) are read.

In step S907, a color value (RGB value) represented by using the product of the read transmission coefficients of the respective color materials is calculated. That is, R (c, m, y) = φ _rC (c) φ _rM (m) φ _rY (y) R
_W , G (c, m, y) = φ _gC (c) φ _gM (m) φ _gY (y) G
_W , B (c, m, y) = φ _bC (c) φ _bM (m) φ _bY (y) B
_W. Is required.

Here, the manner in which the color values (RGB values) are represented using the product of the transmission coefficients will be schematically described with reference to FIG. Referring to FIG. 10, FIG. 10A shows the RGB values (R _W , G _W , B _W ) at the white point. The vertical axis represents the color value, and the color value of the white point becomes the maximum.

Since a part of the color value of the white point is absorbed by the Y layer existing above the white point, as shown in FIG.
Color values (R, G, B) color values of the white point _{(R W, G W, B} W)
And further decrease to (R ⁽¹⁾ , G ⁽¹⁾ , B ⁽¹⁾ ). At this time, the transmittance at which the color value of the white point transmits through the Y layer is φ
_Assuming that _Y , the color values (R ⁽¹⁾ , G ⁽¹⁾ , B ⁽¹⁾ ) are represented by the following formula by the product of the transmittance and the color value of the white point.

R⁽¹⁾= Φ_rYR_W, G⁽¹⁾= Φ_gYG_W, B⁽¹⁾= Φ_bYB_W. Next, a part of the color value of the white point is calculated by the M layer existing on the white point.
Consider the case where is absorbed. As shown in FIG.
In addition, after absorption by the Y layer, there is further absorption by the M layer.
Therefore, the color values (R, G, B) further decrease, and
(R⁽²⁾, G⁽²⁾, B ⁽²⁾). Color value of white point is M layer
The transmittance to transmit is φ_MThen the color value (R⁽²⁾, G⁽²⁾,
B⁽²⁾) Is the product of the white point and the color value and is expressed as
You.

R ⁽²⁾ = φ _rM R ⁽¹⁾ = φ _rY φ _rM R _W , G ⁽²⁾ = φ _gM G ⁽¹⁾ = φ _gY φ _gM G _W , B ⁽²⁾ = φ _bM B ^{( _{1) = φ bY φ bM B}} W. Similarly, the color values (R, G, B) further decrease as shown in FIG. 10D due to the absorption by the C layer existing above the white point, and the color values (R ⁽³⁾ , G ^{(3 ) )} , B ⁽³⁾ ). C
Assuming that the transmittance of the layer is φ _C , the color values (R ⁽³⁾ , G ⁽³⁾ ,
B ⁽³⁾ ) is a product of the white point and the color value, and is represented by the following equation.

R ⁽³⁾ = φ _rC R ⁽²⁾ = φ _rC φ _rY φ _rM R _W , G ⁽³⁾ = φ _gC G ⁽²⁾ = φ _gC φ _gY φ _gM G _W , B ⁽³⁾ = φ _bC B ⁽²⁾ = φ _bC φ _bY φ _bM B _W. Thus, the color value is represented as the product of the color value of the white point and the product of the transmission coefficients of the respective color materials. Although it is possible to roughly estimate the RGB values in this way, an error becomes large as it is, so that correction using secondary colors and tertiary colors is performed in the subsequent processing steps.

Returning to FIG. 9, after the color value RGB value is calculated, it is determined in next step S909 whether or not the color (RGB) represented by using the product of the transmission coefficients is in the secondary color correction area. Is determined. That is, the target color is CM
In the Y space, tertiary color correction is performed when the color is in the vicinity of the CMY three-color mixed area, and in the other area, secondary color correction is performed.

The secondary color correction area and the tertiary color correction area will be briefly described with reference to FIG. Here, C
2 illustrates a secondary color correction area and a tertiary color correction area in an MY color space. With reference to this drawing, in the area A of the shaded portion inside the LUT where the three colors of CMY are mixed,
The correction by the tertiary color is performed, and the correction by the secondary color is performed in other areas.

If it is determined that the area is the secondary color correction area (“yes” in step S909), the process proceeds to step S911.
The secondary color correction calculation process is performed. On the other hand, if it is determined that the area is not the secondary color correction area, that is, if it is determined that the area is the tertiary color correction area (“no” in step S909), the process proceeds to step S913, and the tertiary color correction is performed. Operation processing is performed.

The details of the secondary color correction operation and the tertiary color correction operation will be described later. When the correction process using the secondary color or the tertiary color is completed in this way, the process proceeds to step S915, S917, or S919 as appropriate. Then, a correction operation for all gradations is performed for each of the C, M, and Y color materials. Therefore, each color value is calculated for each of the (N × N × N) colors represented by the product of the transmission coefficients for N gradations of each color material.

FIG. 12 is an image diagram for explaining the secondary color correction processing. Here, cyan and magenta 2
A method for correcting colors will be described as an example. As shown in this figure, two color material layers of cyan and magenta are adhered on white paper. In this example, the amount of the C layer is larger than the amount of the M layer.

Referring to FIG. 12A, the color values at the white point are (R _W , G _W , B _W ), the transmission coefficients of all C layers are φ _iC (c), and the same amount as that of the M layer. The transmission coefficient in the C layer of
_iC (cm) (subscript i = r, g, b). The secondary color correction means that magenta and cyan of the same amount as magenta are replaced with a secondary color of blue, and as shown in FIG. It is a correction treated as something.

For cyan, a part of the color is replaced by the secondary color blue. Therefore, the transmission coefficient φ _iC (c) of cyan is calculated as follows using the same amount of transmission coefficient φ ′ _iC (cm) of cyan as magenta. To be corrected. Note that c corresponds to the amount of all C layers, and cm corresponds to the smaller amount of cyan and magenta.

Φ ″ _iC = φ _iC (c) / φ ′ _iC (cm) When the corrected transmission coefficient φ ″ _{iC of} cyan is obtained in this way, the color value (RGB value) is , Is represented by the following equation.

R = φ ″ _rC φ _rB (cm) R _W = φ _rC (c)
φ _rB (cm) / φ ′ _rC (c) R _W G = φ ″ _gC φ _gB (cm) G _W = φ _gC (c) φ _gB (cm)
/ Φ ' _gC (c) G _W B = φ " _bC φ _bB (cm) B _W = φ _bC (c) φ _bB (cm)
/ Φ ′ _bC (c) B _W The secondary color correction processing is performed by such a method.
Therefore, when the three color materials adhere to white paper, the secondary color correction processing is performed as follows.

FIG. 13 is a diagram for explaining secondary color correction when three CMY color materials adhere to the sheet. As shown in FIG. 13A, it is assumed that a C layer, an M layer, and a Y layer are respectively attached to a sheet. FIG. 13B, FIG. 13C, and FIG.
Consider three patterns in which two color material layers overlap as shown in FIG. Then, the transmission coefficient is determined for each pattern assuming that only two colors overlap.

In FIG. 13B, when the C layer and the M layer overlap, the amount (cm) corresponding to the smaller amount of magenta and cyan is replaced by the secondary color blue.
It is assumed that white color values are absorbed by blue. Similarly, in FIG. 13C, when the M layer and the Y layer overlap, the amount (my) corresponding to the smaller amount of magenta and yellow is replaced with the secondary color red. Then, it is assumed that the white color value is absorbed by red. In FIG. 13D, the amount (cy) corresponding to the smaller amount of cyan and yellow is replaced with the secondary color green by overlapping the C layer and the Y layer. It is assumed that the white color value is absorbed by green.

Therefore, the transmission coefficients of the C and M layers are (φ _{r, CM} , φ _{g, CM} , φ _{b, CM} ), and the transmission coefficients of the M layer and Y layer are (φ _{r, MY} , φ _{g, MY} , φ _{b, MY} ), and the transmission coefficients of the C layer and the Y layer are (φ _{r, CY} , φ _{g, CY} , φ _{b, CY} ).
The transmission coefficient in all the CMY layers in consideration of the absorption for each next color is expressed by the following equation.

Φ _{r, CMY} = φ _{r, CM} (cm) φ _{r, MY} (my)
φ _{r, CY} (cy) φ _{g, CMY} = φ _{g, CM} (cm) φ _{g, MY} (my) φ _{g, CY} (c
y) φ _{b, CMY} = φ _{b, CM} (cm) φ _{b, MY} (my) φ _{b, CY} (c
y) However, in this case, as shown in FIG. 13E, the transmission coefficients of the respective color materials are used repeatedly. Therefore, the following correction is made.

Φ _{r, CMY} = φ _{r, CM} (cm) φ _{r, MY} (my)
φ _{r, CY} (cy) / (φ _{r, C} (c) φ _{r, M} (m) φ
_{r, Y} (y)), φ _{g, CMY} = φ _{g, CM} (cm) φ _{g, MY} (my) φ _{g, CY} (c
y) / (φ _{g, C} (c) φ _{g, M} (m) φ _{g, Y} (y)), φ _{b, CMY} = φ _{b, CM} (cm) φ _{b, MY} (my) φ _{b, CY} (C
y) / (φ _{b, C} (c) φ _{b, M} (m) φ _{b, Y} (y)). In this way, the transmission coefficient of the secondary color correction when the three CMY color materials adhere to the paper is obtained.

Next, the tertiary color correction calculation processing will be described. FIG. 14 is an image diagram for explaining the tertiary color correction processing. As shown in this figure, three color material layers of cyan, magenta, and yellow adhere to a white paper. Note that the amounts of the C layer and the M layer are larger than the amount of the Y layer.

Referring to FIG. 14A, the color values at the white point are (R _W , G _W , B _W ), the transmission coefficients of all the C layers are φ _iC (c), and the same amount as the Y layer. The transmission coefficient in the C layer of
_iC (cy), the transmission coefficients of all M layers are φ
_iM (m), the transmission coefficient in the M layer having the same amount as the Y layer is φ ′ _iM
(My) (subscripts i = r, g, b). The tertiary color correction is to replace yellow, cyan and magenta in the same amount as yellow with tertiary black, and to change the color of white point by cyan, magenta and black as shown in FIG. This is a correction that treats the value as having absorption.

For cyan and magenta, a part of the cyan and magenta is replaced by tertiary color black.
The transmission coefficient φ _iM (m) of _iC (c) and magenta is calculated as follows using the transmission coefficient φ ′ _iC (cy) of cyan and the transmission coefficient φ ′ _iM (my) of magenta of the same amount as yellow. to correct. Note that c and m correspond to the amounts of all the C layers and M layers, respectively, and cy and my correspond to the smaller amounts of cyan and yellow and the smaller amounts of magenta and yellow, respectively.

Φ ″_{I c}= Φ_{I c}(C) / φ '_{I c}(Cy) φ ”_iM= Φ_iM(M) / φ '_iM(My) corrected transmission of cyan and magenta in this way
Coefficient φ ”_{I c}And φ ” _iMIs required, this
Using these, the color value (RGB value) is represented by the following equation.
It is. Note that c and m are the amounts of the C layer and the M layer, respectively.
And cy, my, and cmy are respectively
The smaller amount of the C layer and the Y layer, the smaller amount of the M layer and the Y layer
Volume and the lesser of the C, M and Y layers
I am responding.

R = φ ″ _rC φ ″ _rM φ _rK (cmy) R _W = φ _rC (c) φ _rM (m) φ _rK (cmy) / φ ′ _rC (cy) φ ′ _rM (my) R _W G = Φ ” _gC φ” _iM φ _gK (cmy) G _W = φ _gC (c) φ _gM (m) φ _gK (cmy) / φ ′ _gC (cy) φ ′ _gM (my) G _W B = φ ″ _bC φ ″ _bM φ _bK (cmy) B _W = φ _bC (c) φ _bM (m) φ _bK (cmy) / φ ′ _bC (cy) φ ′ _bM (my) B _W Correction calculation processing is performed.

The above-described secondary color correction and tertiary color correction can be summarized as follows: RGB values (R (c, m, y), G
(C, m, y), B (c, m, y)) can be expressed by the following equation.

R (c, m, y) = φ _rC (c) φ _rM (m)
φ _rY (y) φ ^* _r (c, m, y) R _W G (c, m, y) = φ _gC (c) φ _gM (m) φ _gY (y) φ
^* _g (c, m, y) G _W B (c, m, y) = φ _bC (c) φ _bM (m) φ _bY (y) φ
^* _b (c, m, y) B _W where φ ^* _i (c, m, y) is a correction coefficient, and in the case of secondary color correction and tertiary color correction, respectively, (Subscripts i = r, g, b). (Secondary color correction) φ ^* _i (c, m, y) = φ _ib (cm) / (φ _iC (cm) φ
_iM (cm)) ・ φ _ir (my) / (φ _iM (my) φ _iY (my)) ・ φ
_ig (cy) / (φ _iC (cy) φ _iY (cy)) (Tertiary color correction) φ ^* _i (c, m, y) = φ _iK (cmy) / (φ _iC (cmy) φ
_iM (cmy) φ _iY (cmy)) Again, cm is the amount of the smaller color material of cyan and magenta, my is the amount of the smaller color material of magenta and yellow, and cy is the amount of the color material of cyan and yellow. It corresponds to the amount of the color material of the smaller one. Cmy corresponds to the smallest color material amount among cyan, magenta, and yellow.

Next, specific processing flows of the secondary color correction operation and the tertiary color correction operation will be described with reference to FIGS. FIG. 15 is a flowchart showing details of the secondary color correction calculation processing (step S911) in FIG. 9, and FIG. 16 is a flowchart showing details of the tertiary color correction calculation processing (step S913) in FIG. is there.

Referring to FIG. 15, first, when the RGB values are obtained in step S907 of FIG. 9, step S150
From step 1 to step S1503, the basic CMY
From the three colors, the replacement amounts rgb of the secondary colors RGB are obtained.

In step S1501, the secondary color Red
The (red) replacement amount r is calculated. That is, the smaller amount of the M layer and the Y layer of the color currently being processed is determined as the secondary color red replacement amount r.

In step S1503, similarly,
The replacement amount g of the next color Green (the smaller amount of the C layer and the Y layer) g is then determined in step S15.
05, the replacement amount of the secondary color Blue (blue) (C
The smaller amount b) of the layer and the M layer is calculated respectively.

After the replacement amount rgb of the secondary color RGB is calculated, the process proceeds from step S1507 to step S15.
At 11, each transmission coefficient φ of the secondary color RGB is read. That is, among the transmission coefficients φ for N gradations of all the seven color materials calculated in step S405 and stored in the memory, the transmission coefficients of the secondary colors RGB, rgb
The gradation is read out.

In step S1507, the transmission coefficients (φ _rR (r), φ _gR (r), φ _gR (r),
_bR (r)) is read. Then, step S150
9, the transmission coefficient (φ
_rG (g), φ _gG (g), φ _bG (g)) are obtained in step S1.
In step 511, the transmission coefficient (φ _rB
(B), φ _gB (b), φ _bB (b)) are read out.

When the transmission coefficients of the secondary colors RGB are read, respectively, subsequently, steps S1513 to S1 are performed.
At 517, CMY necessary for operation from memory
Is read out. That is, in step S1513, the transmission coefficients of the gth and bth gradations of C are read, and in step S1515, the transmission coefficients of the rth and bth gradations of M are read. Then, in step S1517, the transmission coefficients of the r-th gradation and the g-th gradation of Y are read.

When the necessary transmission coefficients of the primary color and the secondary color are read, in step S1519, a color value is calculated by secondary color correction. That is, using the RGB values calculated in step S907 and the transmission coefficients read in steps S1507 to S1517, the color values (R′G ′) by the secondary color correction are used.
B ′ value) is calculated by the following equation.

R ′ (c, m, y) = φ _rR (r) φ _rG (g) φ
_rB (b) R (c, m, y) / ( _φrM (r) _φrY (r) _φrC (g) _{φrY
(g) φ rC (b)} φ rM (b) G '(c, m, y) = φ gR (r) φ gG (g) φ gB (b) G (c, m,
y) / (φ _gM (r) φ _gY (r) φ _gC (g) φ _gY (g) φ _gC (b) φ
_gM (b) B '(c, m, y) = φ _bR (r) φ _bG (g) φ _bB (b) B (c, m, y
y) / (φ _bM (r) φ _bY (r) φ _bC (g) φ _bY (g) φ _bC (b) φ
_bM (b) Thus, for the secondary color correction area, the primary color CM
A color value is obtained using not only the transmission coefficient of Y but also the transmission coefficient of RGB as a secondary color. For this reason, it is possible to calculate a highly accurate value with less error as compared with a case where the value is obtained only by the transmission coefficient of the primary color.

Next, the tertiary color correction calculation will be described. Referring to FIG. 16, in step S907 of FIG.
When the B value is determined, in step S1601, the replacement amount k of the tertiary color Black (K) is determined from the three basic CMY colors. In other words, the least amount of the color material layer among the C layer, the M layer, and the Y layer of the color to be currently processed is obtained as the tertiary color black replacement amount k.

After the replacement amount k of the tertiary color black is calculated, the transmission coefficient φ of the tertiary color black is read in step S1603. That is, the transmission coefficient of the k-th gradation of the tertiary color black is read out of the transmission coefficients φ of the N gradations of all the seven color materials calculated in step S405 and stored in the memory.

When the transmission coefficient of the tertiary color black is read, subsequently, steps S1605 to S1609 are performed.
, The CMY transmission coefficients required for the operation are read from the memory. That is, step S1
In step 605, the transmission coefficient of the k-th gradation is read out, and in step S1607, the transmission coefficient of the k-th gradation is read out. Then, in step S1609, the transmission coefficient of the k-th gradation of Y is read.

Then, in step S1611, 3
A color value is calculated by the next color correction. That is, the RGB values calculated in step S907, and
Using the transmission coefficients read from step S1603 to step S1609, a color value (R'G'B 'value) by tertiary color correction is calculated by the following equation.

R ′ (c, m, y) = φ _rK (k) R (c, m, y) /
(Φ _rC (k) φ _rM (k) φ _rY (k)) G ′ (c, m, y) = φ _gK (k) G (c, m, y) / (φ _gC (k) φ
_gM (k) φ _gY (k)) B ′ (c, m, y) = φ _bK (k) B (c, m, y) / (φ _bC (k) φ
_bM (k) φ _bY (k)) Thus, for the tertiary color correction area, the CM of the primary color
Not only the transmission coefficient of Y but also Bac, which is a tertiary color
The color value is also determined using the transmission coefficient of k. For this reason,
It is possible to calculate a highly accurate value with a small error.

As described above, according to the data processing method of the present embodiment, for example, when creating a 5-level LUT in the CMY color space, 7 × 5−6 = 2
What is necessary is just to acquire nine color data. From the 29 pieces of data, 5 × 5 × 5 = 125 pieces of color data are finally appropriately obtained. Thus, usually,
Where (N × N × N) number of data should be measured,
It is sufficient to measure only (7 × N-6) data (N is the number of gradations). Therefore, since the number of data of the color chart to be measured is greatly reduced, the labor required for the measurement is significantly reduced.

<Modification> Next, a modification of the embodiment of the present invention will be described. In this embodiment, a case has been described in which three-dimensional (N × N × N) data is created from a data group of N gradations of each color material to be measured. In this modification, by performing an interpolation operation on the data,
Data of L (L> N) gradations is obtained, and (L × L × L) pieces of data are created.

FIG. 17 is a flowchart showing the flow of data processing in the modification. This drawing is different from the flowchart shown in FIG. 4 in that an interpolation calculation process in step S1702 is inserted after the measured value input process in step S401.

In step S401, as in the case of FIG. 4, color value data for N gradations of each color material measured by the color value measuring device 200 is input. Specifically, since the data is N gradations of seven color materials, the number of data is (7 × N
-6) pieces.

Next, in step S1702, data interpolation is performed. That is, step S401
By interpolating the data of the N gradation inputted in the above, the data of the intermediate gradation is calculated. For example, an interpolation operation is performed such that data for L (L> N) gradations is obtained for each color material. Therefore, here, the number of color data is
The number increases to (7 × L−6).

In this way, when data is interpolated for each color material and L gradations are obtained, processing similar to the processing shown in FIG. 4 is performed thereafter.

That is, in step S403, XYZ
RG of (7 × L-6) data obtained as data
Matrix conversion to B data is performed. Therefore,
(7 × L−6) RGB data are obtained.

Next, a transmission coefficient conversion process is performed on each of the matrix-converted data. The number of transmission coefficients determined here is (7 × L−6). continue,
In step S407, a color value is calculated using the transmission coefficient. Since the number of gradations of each color material is L, the required number of data is (L × L × L).

When the calculation of the color values is completed, step S40
At 9, an inverse matrix transformation of the calculated values is performed,
(L × L × L) pieces of XYZ data are obtained.

According to the above processing, a data group of L gradations is calculated by interpolation from a data group of N gradations for each color material. Therefore, (L × L × L) pieces of data are finally obtained. Therefore, desired data is appropriately calculated from a smaller number of data, and an LUT of a desired size can be easily created. Therefore, the labor required for measurement when creating an LUT is greatly reduced.

This time, an example has been described in which the above-described data processing method is realized by executing a data processing program. However, it is not limited to such a case. Therefore, the above-described data processing may be performed by hardware. Further, the functions may be realized by replacing some processing functions of software with hardware.

In the present embodiment, RG
Although the example in which the present invention is applied when the color space is converted from the B color space to the CMY color space has been described, the present invention is not limited to such a color space. The present invention can be applied to a case where data is color-converted from a certain color space to a different color space.

The embodiment disclosed this time is an example in all respects, and should not be construed as limiting. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

[Brief description of the drawings]

FIG. 1 shows a data processing apparatus 100 according to an embodiment.
FIG. 4 is a diagram showing an example in which a computer as an example is connected to a color value measuring device 200.

FIG. 2 shows a computer (data processing device 10) of FIG.
FIG. 2 is a functional block diagram showing the configuration of FIG.

FIG. 3 is a diagram showing a configuration of software when the data is read into a RAM 22;

FIG. 4 is a flowchart showing a flow of data processing in the present embodiment.

FIG. 5 is a conceptual diagram for explaining an absorption model.

FIG. 6 is a diagram showing band characteristics of tristimulus values XYZ.

FIG. 7 is a diagram showing band characteristics of RGB values.

FIG. 8 is a transmission coefficient conversion process of FIG. 4 (step S405).
5 is a flowchart showing details of the process.

FIG. 9 is a flowchart showing details of a color value calculation process (step S407) of FIG. 4;

FIG. 10 is a schematic diagram for explaining how color values (RGB values) are represented using a product of transmission coefficients.

FIG. 11 is a diagram for describing a secondary color correction area and a tertiary color correction area.

FIG. 12 is an image diagram for explaining a secondary color correction process.

FIG. 13 is a diagram for describing secondary color correction when CMY three color materials adhere to a sheet.

FIG. 14 is an image diagram for explaining a tertiary color correction process.

FIG. 15 shows the secondary color correction calculation processing of FIG. 9 (step S9).
It is a flowchart which showed the detail of 11).

FIG. 16 shows a tertiary color correction calculation process of FIG. 9 (step S9);
13 is a flowchart showing details of 13).

FIG. 17 is a flowchart showing a flow of data processing in a modified example.

[Explanation of symbols]

100 data processing device, 11 main body, 12 display device, 18 CD-ROM, 20 CPU, 21 RO
M, 22 RAM, 23 hard disk drive, 31
Color chart data input unit, 33 RGB value conversion unit, 35 LU
T operation unit, 37 XYZ value conversion unit, 200 color value measuring device.

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 5B057 AA11 CA01 CA08 CA12 CB01 CB08 CB20 CE18 CH01 CH11 CH14 DA16 DA17 DB02 DB06 DB09 DC25 5C077 LL17 LL19 MP08 PP32 PP35 PP37 PQ12 PQ23 5C079 HB01 HB05 LB01 MA04 NA03 NA03

Claims (9)

[Claims] 1. A data processing method for creating a three-dimensional lookup table for recording data of a first color space and data of a second color space in association with each other, wherein the first color An acquiring step of acquiring data of the second color space corresponding to data of N gradations of M (M ≧ 3) types of colors in the space, respectively, and using the acquired data, A first calculation step of calculating a transmittance of a color for a reference white in a color space for N gradations of each of the M types of colors; and a second calculation corresponding to the calculated transmittance and the reference white A second calculation step of calculating desired data in the second color space using data in the color space, wherein the desired data is one of the M colors in the first color space. Predetermined three colors The second calculation step calculates (N × N) by calculating a combination of transmittances for N gradations of each of the three types of colors. × N) A data processing method characterized by acquiring desired data. 2. The data processing method according to claim 1, wherein the predetermined three types of colors are primary colors serving as references in the first color space. 3. The M kinds of colors include a secondary color in addition to the three kinds of primary colors in the first color space, and the second calculating step is performed by the first calculating step. A first correction coefficient calculating step of obtaining a first correction coefficient using the obtained transmittances of the primary color and the secondary color; and calculating the obtained first correction coefficient for each of the three types of colors. A first correction step of performing a correction by multiplying the product of the transmittance. 4. The M kinds of colors further include a tertiary color in the first color space, and the second calculating step includes the step of calculating the first color and the third color calculated in the first calculating step. A second correction coefficient calculating step of obtaining a second correction coefficient using the transmittance of the next color; and multiplying the obtained second correction coefficient by the product of the transmittance of each of the three colors. And a second correction step of performing a correction. For the data of the first area of the first color space, desired data is obtained by the first correction coefficient calculation step and the first correction step. The calculation according to claim 3, wherein desired data is calculated for the data in the second area of the first color space by the second correction coefficient calculation step and the second correction step. Data processing method. 5. The method according to claim 1, wherein the second color space is a CIE-XYZ color space, and wherein the first calculating step includes:
The data in the YZ color space is converted into the data in the RGB color space, the respective transmittances are calculated using the converted data, and the desired data in the RGB color space calculated in the second calculation step is calculated. 5. The data processing method according to claim 1, further comprising an inverse conversion step of converting the data into data in a CIE-XYZ color space. 6. The method according to claim 1, wherein the acquiring step includes: (M × K) pieces of data in the second color space corresponding to data of M kinds of K (K <N) gradations in the first color space. Acquired,
The data processing method according to claim 1, wherein data corresponding to the data for the N gradations is obtained by performing an interpolation operation using the obtained data. 7. A data processing device for creating a three-dimensional look-up table for recording data of a first color space and data of a second color space in association with each other, wherein the first color Acquiring means for respectively acquiring data of the second color space corresponding to data of N gradations of M (M ≧ 3) kinds of colors in the space; and using the acquired data, First calculating means for calculating the transmittance of a color with respect to a reference white in a color space for N gradations of each of the M types of colors; and the second calculating means corresponding to the calculated transmittance and the reference white. And second calculation means for calculating desired data in the second color space using data in the color space, wherein the desired data is one of M types of colors in the first color space. For each of the three specified colors It represented using the product of transmittance Te, the second calculation means by calculating the combination of the three colors each of the N gradations of transmittance,
A data processing device for acquiring (N × N × N) desired data. 8. Data processing for causing a computer to execute a data processing method for creating a three-dimensional look-up table that records data of a first color space and data of a second color space in association with each other. An acquisition step of acquiring data of the second color space corresponding to data of N gradations of M (M ≧ 3) colors in the first color space; A first calculating step of calculating the transmittance of the reference white color in the first color space for the N gradations of each of the M types of colors, using the calculated data, A second calculating step of calculating desired data in the second color space using the data in the second color space corresponding to the reference white; The data is represented using a product of transmittance of each of three predetermined colors among the M types of colors in the first color space. The second calculation step includes calculating the three types of colors. A data processing program for acquiring (N × N × N) desired data by calculating a combination of transmittances for each of N gradations. 9. A computer-readable recording medium on which the data processing program according to claim 8 is recorded.