JP2002152530A - Color collection processing method and device thereof - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a color image processing method and a color image processing device which provide excellent gray balance or can reproduce colors satisfactorily even if a plurality of light sources are used. SOLUTION: This image processing device converts a coordinate point in a color space between a color signal and a device signal according to a look-up table(LUT). Data are obtained from the outside by measuring the coordinates of the grid points of the LUT and color patches are received, the coordinates of the grid points are subjected to nonlinear conversion by an S-function, etc., and coordinates corresponding to the nonlinear-converted coordinates of the grid points are produced to make a new look-up table. Further, a correction of a dynamic range in a lightness direction a γ-correction for a contrast correction, and a chroma correction are carried out to improve the gray balance. Further, a artificial data are produced by using a chromatic adaptation model, ULTs for a plurality of light sources are made by using the artificial data, and the LUTs are weighted to produce a new LUT.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] The present invention relates to a color image processing method and apparatus. In particular, the present invention relates to a color correction processing method and apparatus for improving gray balance.

[0002]

2. Description of the Related Art In recent years, with the spread of PCs, the Internet, and the like, opportunities for handling color images have increased in general home use. For example, digital still
In an era where anyone can easily output images taken with a camera using a printer they have. Along with this, the concept of so-called Device Independent Color (DIC) for reproducing images with the same color between different types of devices has arisen, and its realization has been demanded. A system for realizing this is generally called a color management system (CM).
S), and a representative one is MacOS Col
There are orsync and ICM of Windows98.

In the CMS, a DIC is realized by matching physical colorimetric values of color signals of an input / output device (see FIG. 1). That is, in the CMS, a color signal of an image captured by an input device is converted into a device-independent color signal using a device profile of an input device (sometimes simply referred to as a profile). The independent color signal is converted into a color signal of an image of the output device using the device profile of the output device (see FIG. 2). Thus, when converting an input color signal into an output color signal, the device
A DIC is realized by converting once into a color signal in a device-independent color space using a conversion formula or a conversion table called a profile. Here, the device profile is a device signal value (RG
B, CMYK, etc.) and color values (XYZ, L * a * b *, etc.) of the signal values measured by a colorimeter or the like.

When the relationship between a device signal value and a color value of an image realized by the device is nonlinear as in a printer or the like, a look-up table (LUT) is generally used as a device profile. It is a target. The LUT is created by the following two steps. (1) Create a uniform grid in the input color space. (2) Calculate the output value in the uniform grid.

An LUT used in a CMY output printer is described below.
A general method (conventional method) for creating an image will be described. First, CM
Color values (CIE / XYZ, CIE / L) of N ³ (N × N × N) color patches and the like evenly arranged in the Y space
* a * b *). The color patches may be arranged in any manner, but must be arranged so as to sufficiently fill the color space of the device. The LUT can be created by calculating the inverse mapping of the measurement data (see FIG. 3). In the following description, grid points of the LUT are defined as grid points in the L * a * b * space, and are referred to as L * a * b * grid points. When the measurement data of the color value is data in the L * a * b * color space (hereinafter, this measurement data is referred to as L * a * b * measurement data), the LUT is in the L * a * b * space (for example, , 0
≤L * ≤100, -128≤a * ≤128, -128≤b * ≤128) to form M ³ (M × M × M) grids, and CMY output values corresponding to each grid Is calculated, and generated as a table.

FIG. 4 is a diagram showing a flow of processing up to calculating CMY output values corresponding to each L * a * b * grid point based on measurement data. The N ³ measurement data are arranged evenly in the CMY space.
Plotting on L * a * b * results in an irregular arrangement (see FIG. 5). To form an LUT, the L * a * b * space is defined as M ³ (M
× M × M), and the CMY output value for each grid point is obtained. However, as can be seen from FIG. 5, not all the grid points are within the color gamut. The determination whether the L * a * b * grid point is within the color gamut is performed as follows.

[0007] The N ³ measurement data are composed of (N-1) ³ hexahedrons. A hexahedron without any distortion in the CMY space, that is, a cube (see FIG. 6A) is a distorted hexahedron in the L * a * b * space (see FIG. 6B).
One hexahedron can be divided into five tetrahedrons (see FIGS. 7A and 7B). First, a L * a * b * grid point is a tetrahedron formed by dividing a hexahedron formed by measurement points of L * a * b * measurement data (hereinafter referred to as measurement data tetrahedron).
Find out which tetrahedron is included. Whether the L * a * b * grid points fall within the measurement data tetrahedron is determined as follows.

As shown in FIG. 8, the input grid point is a point P: (L * _p , a * _p , b * _p ), and the coordinates (L * _i , a *) of the vertex of a certain measurement data tetrahedron are set. _i , b * _i ) (i = 0, 1, 2, 3) (see FIG. 8A). At this time, the point P is included in the measurement data tetrahedron if α, β, χ calculated from the following equation (1) satisfy the condition of the following equation (2).

(Equation 1)

If the above equation holds for any measurement data tetrahedron, the point corresponding to the input grid point is included in the color gamut. The CMY value of each vertex of the tetrahedron in the device signal space (here, CMY) corresponding to the measurement data tetrahedron including the input grid points is represented by (c * _i ,
m * _i , y * _i ) (i = 0, 1, 2, 3), the CMY value (c in the device signal space corresponding to the input grid point
* _p , m * _p , y * _p ) can be calculated by linear interpolation as shown in the following equation (3) (see FIG. 8B).

(Equation 2)

If not included in any of the divided tetrahedrons, the point corresponding to the input grid point is outside the device gamut, and is subjected to gamut compression. Various methods have been proposed for color gamut compression, for example, the following methods. (1) Compression for preserving hue on a two-dimensional plane of lightness-saturation (see FIG. 9 (a), JP-A-09-098298) (2) Defining color difference suitable for human vision (See FIG. 9 (b), JP-A-10-084)
As described above, the LUT can be created by performing the inverse mapping of the measurement data and performing tetrahedral interpolation for grid points within the color gamut and color gamut compression for grid points outside the color gamut.

[0011]

However, in such an LUT creation method, since the grid positions are calculated by equally dividing the chromaticity directions such as a * and b *, the LUTs falling within the device color gamut are obtained. There are few grid points, and as a result, there is little information for associating device signals and color signals in the color gamut, and thus there is a problem that color reproducibility, particularly gray balance, is not good.

Further, since the black levels are different between the devices, there is a problem that, in some cases, blackening or floating of black occurs.

Further, even if a process for correcting a difference in black level is performed, a change in saturation may occur depending on the process, and at the same time, a correction in the saturation direction may be required. is there.

Further, since the LUT is created by inversely mapping the measurement data under a certain light source, color matching is performed under the light source, but the color may not match under another light source. .

SUMMARY OF THE INVENTION The present invention has been made in view of the above-mentioned problems, and has as its object to provide a color image processing method and apparatus which are excellent in gray balance or have good color reproduction even with a plurality of light sources. It is in.

[0016]

According to the present invention, there is provided an image processing apparatus for converting a coordinate point in a color space between a color signal and a device signal based on a lookup table. An input unit that externally inputs grid data that is data of coordinates of grid points in a color space of a color signal and data including measurement data obtained by measuring a color patch of a predetermined color, and coordinates of the grid points. Grid conversion means for performing non-linear conversion, lookup table generation means for generating coordinates corresponding to the coordinates of the non-linearly transformed grid points, and forming a new lookup table, Output means for outputting predetermined data including a look-up table. Hereinafter, this is referred to as a first invention.

According to another aspect of the present invention, in the first aspect, the image processing device corrects a dynamic range of a signal relating to brightness of the grid data and performs γ correction for correcting contrast. Is further configured. Hereinafter, this is referred to as a second invention.

According to another aspect of the present invention, in the second aspect, the image processing apparatus further comprises a saturation correcting means for correcting a change in saturation caused by the processing by the range γ correcting means. Is done. Hereinafter, this is referred to as a third invention.

According to another aspect of the present invention, in any one of the first to third aspects, the image processing apparatus further includes a color adaptation model processing means for generating pseudo measurement data using a predetermined color adaptation model. The look-up table generating means generates a new look-up table for each measurement data using a plurality of measurement data including the pseudo measurement data generated by the color adaptation model processing means, It is configured such that a product sum of a corresponding element between the lookup tables and a predetermined weighting factor is obtained for each of the corresponding elements to form a new lookup table. Hereinafter, this is referred to as a fourth invention.

According to another aspect of the present invention, in any one of the first to fourth aspects, the look-up table generating means includes a step of setting the coordinates of the non-linearly transformed grid point in a color gamut obtained from the measurement data. An in-gamut grid determining means for determining whether or not the grid point is included, and for a grid point determined to be included in the color gamut, performing a predetermined interpolation process using the coordinates of the grid point in the color gamut and the measurement data. And a tetrahedral interpolation means for generating device signal coordinates corresponding to the coordinates of the grid points included in the color gamut; and a predetermined color gamut compression process for grid points determined not to be included in the color gamut. And a color gamut compressing means for generating device signal coordinates corresponding to the coordinates of grid points not included in the color gamut.

[0021]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiment 1 FIG. 10 is a diagram illustrating an overall configuration of a color correction processing device 100 according to an embodiment of the present invention. In FIG. 10, the color correction processing device 10
0 is the operation unit 110, the control unit 120, the input / output unit 130,
It comprises a color space conversion section 140, a grid conversion section 150, an in-gamut grid determination section 160, a tetrahedral interpolation section 170, a gamut compression section 180, and a storage section 190. Control unit 1
20 is connected to all other components.

The operation of each component will be described below. In the following description, grid data (e.g., data of the above-described uniform grid) in a predetermined color space and measurement data obtained by measuring the color of a predetermined color patch are externally input to the color correction processing apparatus 100. It is assumed that In the first embodiment, the color space of the grid data is CIE / L *
a * b *, and the color space of the measurement data is CIE / XYZ, but it goes without saying that it is limited to these. Hereinafter, the input grid data is referred to as input grid data, and the measurement data in the CIE / XYZ color space is referred to as XYZ measurement data.

The operation unit 110 displays a menu screen for performing settings and the like necessary for performing color correction processing, and the settings are made using keys and the like. Further, the operation unit 110 receives instructions such as start / stop of processing, data input, and other inputs. Further, the status of the processing in each component, the processing result, and the like are displayed. The output of the operation unit 110 is transmitted to the control unit 120 or to each component via the control unit 120.

The control unit 120 outputs predetermined instructions, data, and the like to each processing unit in accordance with settings, instructions, data, and the like output from the operation unit 110, and outputs signals from each component to the control unit 120. In response to the above, processing such as outputting instructions and data to other components is performed. For example, in response to a request from a grid conversion unit 150 described later, predetermined data is read from a storage unit 190 described later and output to the grid conversion unit 150, or the predetermined data output from the grid conversion unit 150 is For example, output to

The input / output unit 130 takes in predetermined data including LUT grid data (input grid data) and color patch measurement data in accordance with an instruction from the control unit 120, and LUs generated by the present apparatus.
It outputs predetermined data including T and other intermediate data. The control of the control unit 120 regarding the input / output unit 130 is performed based on an instruction input to the operation unit 110. The data input / output method may be a method using a predetermined recording medium such as a flexible disk or a CD.
It may be performed by communication with another information processing device.

Under the control of the control unit 120, the color space conversion unit 140 converts the XYZ measurement data of the color patch input from the input / output unit 130 into L * a * b * data by a known conversion technique. This conversion generally uses a linear matrix, but does not exclude conversion by other methods. Hereinafter, the L * a * b * data obtained by this conversion is referred to as L * a * b * measurement data. It is to be noted that a known Lagrange interpolation may be performed on the L * a * b * measurement data, and the data obtained by this interpolation will be referred to as pseudo L * a * b * measurement data.

Before describing the grid conversion unit 150, a brief description will be given of the principle of processing in this configuration unit. In general, since the LUT calculates the grid position by equally dividing the chromaticity direction such as a *, b *, etc., the ratio of points corresponding to the grid within the color gamut is small, and the gray balance is not good. When creating an LUT, the accuracy near the gray axis is very important. To achieve this, L
The accuracy can be improved by making the density of the grid of the UT finer on the gray axis and rougher as the distance from the gray axis increases. For example, when calculating the grid position of the LUT, it is very effective to perform conversion using an S-shaped function on a uniform grid position to obtain a non-linear grid position. Where CIE 1994 Color Difference:
A description will be given by taking as an example a function based on a saturation correction coefficient of ΔE94 and a representative sigmoid function of an S-shaped function.

The above ΔE94 is represented by the following equation.

(Equation 3) Assuming that the change in the saturation direction at this time is ΔC * ₉₄ , the saturation difference can be expressed as follows.

(Equation 4) Here, when both sides are integrated as C * ₇₆ >> ΔC * ₇₆ , the following equation (6) is obtained.

(Equation 5) Hereinafter, this expression is referred to as a saturation correction function.

By using the saturation correction function, it is also possible to have a grid position that is visually more linear than previous LUTs. If the inverse function of the above equation (6) is calculated, it can be used as an inverse S-shaped function. Further, in the above equation (6), the constant 0.004
By substituting 5 for the parameter k and generalizing as in the following equation (7), various S-shaped and inverse S-shaped functions can be created. Increasing the value of the parameter k increases the curvature of the curve represented by this function, and decreasing the value decreases the curvature (see FIG. 11).

(Equation 6)

On the other hand, the sigmoid function is given by the following equation (8).
It is represented as

(Equation 7) By changing the parameter α in the sigmoid function, various S-shaped functions can be created (FIG. 1).
2). By changing this parameter α and obtaining a value that touches the saturation correction function at ΔE ₉₄ on the gray axis, α ≒ 5. FIG. 13 is a diagram plotting the sigmoid function and the saturation correction function when α = 5. The saturation correction function changes smoothly as a whole, whereas the sigmoid function changes rapidly at the end of the graph. In FIG. 13, when the input signal increases in increments of 8, the former increases by 16.9, and the latter increases by 44.9.

Returning to the description of the components of the color correction processing device 100, the grid conversion unit 150 converts the input grid data from the input / output unit 130 into S under the control of the control unit 120.
Character conversion. The conversion is performed by, for example, the above equation (7),
(8) That is, conversion may be performed based on a saturation correction function or a sigmoid function. Parameter k used at that time
And α may be input from the operation unit 110 or may be stored in advance in a storage unit 190 described later. In the following, the data obtained by this conversion is L * a *
Called b * grid data.

The in-color-gamut grid determining unit 160 controls the control unit 1
Under the control of 20, the L * a * b * measurement data (or pseudo L * a * b * measurement data) output from the color space conversion unit 140 and the L * a * b * grid output from the grid conversion unit 150 Make the following decisions using the data. That is, it is determined for each coordinate point whether or not each coordinate point indicated by the L * a * b * grid data is within the color gamut specified by the L * a * b * measurement data. The determination may be made based on, for example, the above equations (1) and (2), or another method. The in-gamut grid determination unit 160 outputs the L * a * b * measurement data, the L * a * b * grid data, the determination result, and the like to the control unit 120. The control unit 120 outputs the data to the tetrahedral interpolation unit 170 or the color gamut compression unit 180 according to the result of the determination. Hereinafter, of the coordinate points indicated by the L * a * b * grid data, a coordinate point falling within the above color gamut is referred to as a coordinate point within the color gamut, and the data of the coordinate point is referred to as L * a * b * Called grid data. Similarly, among the coordinate points indicated by the L * a * b * grid data, the coordinate points outside the gamut are referred to as out-of-gamut coordinate points, and the data of the coordinate points is referred to as the out-of-gamut L * a * b * Called grid data.

The tetrahedral interpolation unit 170 controls the in-color gamut from the in-gamut grid determination unit 160 according to the control of the control unit 120.
Predetermined interpolation is performed on the L * a * b * grid data, and the points corresponding to the coordinate points in the color gamut are set to the coordinate points (CMY, RGB
Etc.). The above equation (3) may be used for this interpolation. The correspondence between the in-gamut L * a * b * grid data and the coordinate data of the output device obtained by this interpolation constitutes a part of the LUT. These data are output to the control unit 120.

Under the control of the control unit 120, the gamut compression unit 180 controls the outside gamut L *
The known color gamut compression processing is performed on the a * b * grid data. As described above, there are various known processing methods for the color gamut compression processing, and which processing method is selected does not have the essence of the present invention, and any method may be applied. The correspondence between the out-of-gamut L * a * b * grid data and the coordinate data of the output device obtained by this gamut compression processing is LU
It forms another part of T. These data are stored in the control unit 1
20.

The storage section 190 stores predetermined information under the control of the control section 120. The information to be stored includes, among input information input to the control unit 120, for example, setting contents on a menu screen in the operation unit 110,
The above data input from the input / output unit 130, the L * a * b * measurement data from the color space conversion unit 140, the grid conversion unit 1
L * a * b * grid data from 50, predetermined data output from the in-gamut grid determination unit 160, tetrahedral interpolation unit 1
70 and data constituting the LUT output from the color gamut compression unit 180. It goes without saying that other data is not excluded from the stored data.

The processing flow in the color correction processing method according to the first embodiment will be described below. FIG. 14 is a flowchart showing the flow of processing in the color correction processing method according to Embodiment 1 of the present invention. In step S1410,
The control unit 120 performs initial settings such as setting the type of data to be input and the parameter k or α used for LUT generation according to the settings input via the operation unit 110. In step S1420, control unit 120 takes in the data of the type set in step S1410.

In step S1420, the input / output unit 130
Captures the input grid data and the measurement data of a predetermined color patch set in step S1410. In the first embodiment, the input grid data is L * a * b * space data, and the color patch measurement data is XYZ space data. However, it is excluded that each data is different space data. It does not do.
In step S1430, the color space conversion unit 140 converts the XYZ measurement data of the color patch into L * a * b * measurement data. In this step, a predetermined interpolation such as a known Lagrange interpolation may be performed on the L * a * b * measurement data.

In step S1440, grid conversion unit 1
Reference numeral 50 performs a predetermined non-linear conversion on the input grid data to generate L * a * b * grid data. This conversion may be, for example, the S-character conversion described above. In this case, for example, conversion using the above equation (6) may be performed. In step S1450, the in-color-gamut grid determination unit 160 determines the L * a * b * measurement data (or the pseudo L *
a * b * measurement data) and L * a * b * grid data.
It is determined for each coordinate point whether each coordinate point indicated by the a * b * grid data is within the color gamut specified by the L * a * b * measurement data. If it is determined that each coordinate point indicated by the L * a * b * grid data is within the color gamut, the process proceeds to step S146
The process proceeds to 0, and if it is determined that the image is outside the color gamut, the process proceeds to step S1470.

In step S1460, the tetrahedral interpolation unit 17
A value of 0 performs predetermined interpolation on the L * a * b * grid data within the color gamut, and determines a point corresponding to the coordinate point within the color gamut as a coordinate point (CMY, RGB, etc.) of the output device. The above equation (3) may be used for this interpolation. The correspondence between the in-gamut L * a * b * grid data and the coordinate data of the output device obtained by this interpolation constitutes a part of the LUT. In step S1470, the color gamut compression unit 180
A known color gamut compression process is performed on the L * a * b * grid data. Which color gamut compression processing method is selected is not essential to the present invention, and any method may be applied. Out of gamut L *
The correspondence between the a * b * grid data and the coordinate data of the output device obtained by the color gamut compression process forms another part of the LUT. In step S1480, the control unit 1
20 forms an LUT by integrating the processing results from steps S1460 and S1470. Then, the process ends.

As described above, according to the first embodiment, the input grid data is non-linearly converted using the S-shaped function such as the above-described saturation correction function and sigmoid function. It is possible to increase the density of the grid in the vicinity of gray compared to the LUT, and realize a color correction processing method and apparatus capable of improving gray balance. Further, since the ratio of the grid in the color gamut can be increased, the accuracy of the LUT itself can be improved.

Embodiment 2 The color correction processing method and apparatus according to the first embodiment uses an S-shaped function such as the above-described saturation correction function or sigmoid function to perform LUT in a color gamut.
By increasing the data, the conventional LUT
Thus, the density of the grid in the vicinity of gray is increased, and the gray balance is improved. However, even in this case, the problem of black crushing described below remains without being solved. In general, even if the lightness L * and chromaticity a *, b * of black (usually, the color when all the ink is applied), which is the maximum density of the printer, are measured, (L *, a *, b *) = (0, 0, 0). In a normal printer, the lightness L * is around 10,
Even a printer with good black reproducibility is at the second or third place at most. Further, the deviation between a * and b * varies depending on the printer, and this often depends on the reproducibility of gray balance. From this, even if a colorimetric CMS that is colorimetrically faithful connected to another device such as a monitor is executed, all input signals below the maximum density black are crushed. Will be lost. This is one of the causes of so-called black crush.
There is one. In order to improve the black crush, it is effective to perform a correction that can reproduce the dynamic range in the brightness direction to the maximum. In the second embodiment, a description will be given of a color correction processing method and apparatus for performing black correction by performing range correction that is a correction for reproducing a dynamic range in the brightness direction and γ correction.

FIG. 15 is a diagram showing the overall configuration of a color correction processing device 100 according to the second embodiment. The configuration is the same as that shown in the first embodiment except that
0 is added. In the following description, the same components as those shown in FIG. 10 used in the first embodiment are denoted by the same reference numerals, and description thereof will be omitted.

In the second embodiment, the operation unit 110
In addition to the settings described in the first embodiment, a predetermined display is performed.
Wait for an input as to whether or not to correct the dynamic range of the color signal. If it is determined that correction is to be performed, input of information required for dynamic range correction (hereinafter, referred to as range γ correction information) is also waited. Alternatively, the range γ correction information is stored in the storage unit 19.
It is also possible to use the one stored in 0, and this does not exclude other methods. When there is an input, the information is output to the control unit 120. The control unit 120 controls each unit based on the information and outputs the range γ correction information to the range γ correction unit 200. Note that the range γ correction information may be stored in the storage unit 190. If it is determined that the dynamic range is to be corrected, the range γ correction unit 200 performs range γ correction including the processing described below.

Here, the following three types of correction methods will be described (see FIG. 16). (1) A method of applying a correction formula that makes the Y ^(1/3) channel of the black point B of the printer L * = 0 also to the X and Z channels. (2) X ^(1/3) , Y of the black point B of the printer ^(1/3) and Z ^(1/3) A method of correcting so that L * = 0 for all channels (3) A method of correcting so that L * of a black point B of the printer becomes 0 (1) By applying each of the methods (2) and (3), the black point B is mapped in the directions B ¹ , B ² , and B ³ of the arrows in the figure. In the method (1), the point L * = 0 when the axis connecting the black and white of the printer is extended is mapped. Although this approach is generally considered to be superior, care must be taken if the black point of the printer is bright and the chromaticity is far away from the achromatic axis. Method (2)
, The black point of the printer is mapped so that L * = a * = b * = 0. In general, it is possible to minimize the difference in color gamut in a black region, but it is necessary to note that there is a high possibility that the achromatic axis is greatly shifted. In the method (3), since only the lightness L * is corrected, it is possible to hold the chromaticity points.

The black correction is a correction of the dynamic range. However, if the range is corrected linearly, there may be a difference from the original in terms of contrast. In order to correct this contrast, it is effective to perform γ correction using a power function represented by Expression (9) and Expression (10) described below. Where Dran
ge _in is a dynamic range of lightness on the input side, and Drange _out is a range on the output side.

(Equation 8) Here, Drange represents the dynamic range of the color signal in each method, and in method (1), Y
The dynamic range in the ^(1/3) channel is represented by L * in the method (3). In the method (2), the dynamic ranges in the X ^(1/3) , Y ^(1/3) , and Z ^(1/3) channels are respectively represented, and the γ values in the respective channels are naturally different. Become.
The subscript “in” indicates an input device, and the subscript “out” indicates an output device.

FIG. 17 is a flowchart showing the flow of processing in the color correction processing method according to the second embodiment. The processing flow is the same as that shown in the first embodiment (see FIG. 14). Is added to the range γ correction processing. In the following description, the same processes as those shown in FIG. 14 used in the first embodiment are denoted by the same reference numerals, and description thereof will be omitted.

In FIG. 17, in step S1410,
What the control unit 120 initializes includes setting of data necessary for the range γ correction processing such as the data relating to the input side dynamic range and the output side dynamic range. In step S1420, the input / output unit 130
However, after fetching the input grid data and the measurement data of a predetermined color patch set in step S1410, in step S1725, the range γ correction unit 200 performs the above range γ processing. Step S14
In steps 30 and subsequent steps, the same processing as in the first embodiment is performed to form an LUT.

FIG. 18 shows a range γ according to the second embodiment.
It is a flowchart which shows the detailed flow of a correction process (step S1725). In FIG. 18, step S18
In step 10, the control unit 120 determines whether or not to perform the dynamic range correction of the lightness. If it is determined that the correction is to be performed, the process proceeds to step 1820. If it is determined that the correction is not to be performed, the process ends. . In step S1820, control unit 120 determines a correction method to be used based on an instruction from operation unit 110 or the like. These correction methods may include the above-described methods (1) to (3). Here, the case where these methods are included will be described. The process proceeds to step S183 according to the determination result here.
The process proceeds from 0-1 to any one of the steps S1830-n.

The control unit 120 determines in step S1830-1
Then, the correction method of the above (1) is set, and step S183
At 0-2, the correction method of the above (2) is set, and step S
In 1830-3, the correction method of (3) is set, and another correction method is set in steps after step S1830-4. After the correction method is set, step S1840
Then, the range correction unit 210 determines in step S1830
The dynamic range is corrected by the correction method set in the steps from −1 to S1830-n. In step S1850, range correction section 210 performs γ correction for correcting the contrast for each of the above correction methods. With the above processing, the subroutine of the range γ correction processing ends.

As described above, according to the second embodiment, since the range correction processing for reproducing the dynamic range is performed, so-called black crushing can be prevented. In addition, since the γ correction for correcting the contrast is performed in the range γ correction processing, it is possible to prevent a shift in contrast that may occur due to the correction of the dynamic range.

Embodiment 3 FIG. The color correction processing method and apparatus according to the second embodiment provide a correction for reproducing a dynamic range and a γ for correcting a contrast.
Correction was performed to prevent blackening. But,
In the above methods (1) and (2), the saturation changes as shown in FIG. 19 along with the above correction processing. In the third embodiment, a color correction processing method and apparatus for performing saturation correction using a function to be described later to suppress a change in saturation will be described.

FIG. 20 is a diagram showing the overall configuration of a color correction processing apparatus 100 according to the third embodiment. The configuration is the same as that shown in the second embodiment except that a saturation correction section 210 is added. It is. In the following description, the same components as those shown in FIG. 15 used in Embodiment 2 are denoted by the same reference numerals, and description thereof will be omitted.

In the third embodiment, the operation unit 110
Displays a predetermined display in addition to the settings described in the second embodiment, and waits for an input as to whether or not to perform saturation correction. If it is determined that correction is to be performed, input of information required for saturation correction (hereinafter, referred to as saturation correction information) is also waited. Or, the saturation correction information
It is also possible to use the one stored in the storage unit 190, and other methods are not excluded. When there is an input, the information is output to the control unit 120 and the control unit 12
In 0, while controlling each part based on this information,
The saturation correction information is output to the saturation correction unit 210. Note that the saturation correction information may be stored in the storage unit 190. If it is determined that the saturation is to be corrected, the saturation correction unit 210 performs the saturation correction including the processing described below.

In the range γ correction by the above methods (1) and (2), the saturation is increased as shown in FIG. 19 with the correction. Therefore, a correction process for suppressing this is required. So, I examined how much it changes when using a power function. Macbet
h ColorChecker For 18 colors excluding 24 achromatic colors,
In Expression (10), γ is 0.2, 0.4, 0.6,.
8, 1.0, 1.2, and 1.4, and the change in the saturation direction at that time was approximated by Expression (11), and the parameter k of this expression was calculated.

(Equation 9)

The results are as shown in Table 1. When this was approximated, it could be expressed as in equation (14) (see FIG. 21).

[Table 1]

(Equation 10)

As described above, the saturation correction processing can be easily determined as in the equation (13) using the power coefficient (γ) of the power function used in the range γ correction.

[Equation 11] The effect of the saturation correction is as shown in FIG. 22, and it can be confirmed that the correction has been sufficiently performed.

FIG. 23 is a flowchart showing the flow of processing in the color correction processing method according to the third embodiment. The flow of the processing is the same as that shown in the second embodiment (see FIG. 17). Correction processing (step S
2329). In the following description, the same processes as those shown in FIG. 17 used in the second embodiment are denoted by the same reference numerals, and description thereof will be omitted.

In FIG. 23, in step S1410,
The initial setting by the control unit 120 includes setting of data necessary for the saturation correction processing such as exponentiation of the above exponential function.
In step S1420, the input / output unit 130
The input grid data set in step 1410 and the measurement data of a predetermined color patch are fetched. In step S1725, the range γ correction unit 200 performs the above range γ correction processing. In step S2329, the saturation correction is performed. The unit 210 performs the above-described saturation correction processing. Step S
In steps after 1430, the same processing as in the second embodiment is performed to form an LUT.

As described above, according to the third embodiment, in addition to the device range correction and the brightness direction range γ correction, the saturation correction associated with the γ value used there is performed. Even when devices having different black levels are assumed, it is possible to obtain a more reproducible image output without blackening or floating.

Embodiment 4 The color correction processing method and apparatus according to the third embodiment use measurement data of color patches measured under a single measurement light source. However, using the LUT has a problem that color matching may not be performed under other light sources. In the fourth embodiment, a description will be given of a color correction processing method and apparatus for forming an LUT that appropriately matches colors under a plurality of light sources.

FIG. 24 is a diagram showing an overall configuration of a color correction processing apparatus 100 according to the fourth embodiment.
A chromatic adaptation model processing unit 220 is added to the configuration shown in the third embodiment. In the following description, the same components as those shown in FIG. 20 used in Embodiment 3 are denoted by the same reference numerals, and description thereof will be omitted.

In the fourth embodiment, the operation unit 110
In addition to the settings described in the third embodiment, a predetermined display is performed, and an input as to whether or not to perform a process of generating an LUT using a color adaptation model described below (hereinafter referred to as a color adaptation model process). wait. If it is determined that the chromatic adaptation model processing is to be performed, input of predetermined information (hereinafter, referred to as chromatic adaptation model information) required for the chromatic adaptation model processing such as the type of the model is also waited. Alternatively, as the color adaptation model information, information stored in the storage unit 190 can be used, and other methods are not excluded. When there is an input, the information is transmitted to the control unit 1
The control unit 120 controls each unit based on this information, and outputs chromatic adaptation model information to the chromatic adaptation model processing unit 220. The color adaptation model information may be stored in the storage unit 190. If the chromatic adaptation model processing is performed, the chromatic adaptation model processing unit 220
The color adaptation model processing including the processing described below is performed.

As described above, as one problem of the LUT, there is a problem of color rendering properties such that color matching can be performed under a measurement light source when the LUT is created, but the color does not match at all under another light source. In order to avoid this problem, certain intermediate data may be created from measurement data under a plurality of light sources, and an LUT may be created from the intermediate data. Alternatively, LUTs under a plurality of light sources may be created, and an LUT capable of providing intermediate color reproduction may be created from the LUTs. For example, a fluorescent lamp and sunlight (D65) (F10), when considering the observation under both the measured values XYZ in F10 light source and the measured values XYZ _D65 at D65 illuminant
_As a combination of _F10 , a new tristimulus value is defined as follows.

(Equation 12) If an LUT is created from the new tristimulus values XYZ calculated in this way, the problem that colors do not match at all under the D65 light source or the F10 light source is eliminated.

In this example, two types of light sources are assumed, but a plurality of light sources may be assumed. In such a case, the coefficients under the respective light sources may be determined so that the sum of the coefficients of the measured values becomes 1. When determining the coefficient,
The effect can be increased by setting a large coefficient of the light source that is likely to be the largest among the assumed observation light sources. If there is no measurement data of another light source, a tristimulus value under the light source may be calculated using a chromatic adaptation model as described below.

Various chromatic adaptation models have been proposed for converting measurement data (XYZ data) into data on other light sources. Typical ones are Bradford transform, Hunt-Poi
There is nter-Estevas conversion. The flow of the color adaptation model can be represented as shown in FIG. First, the measurement data (XYZ) in under a specific light source is converted into a stimulus value (LMS) adp to the cone level by a 3 × 3 matrix. Furthermore, the stimulus value at the cone level is obtained from the visual environment on the output side.
It will be converted to (LMS) out and then to (XYZ) out by a 3x3 matrix. Where XYZ
The coefficients of the 3 × 3 matrix for converting tristimulus values and LMS tristimulus values are calculated using Bradford transform and Hunt-Pointer-Estevas.
The conversion differs, and the matrix coefficients are as follows.

(Equation 13)

[Equation 14]

[0066] Expressing 3 × 3 transformation matrix described above as M _T, after the conversion by the color adaptation model (XYZ) out is
It can be defined as follows:

(Equation 15) Here, Lmax_i, Mmax_i, and Smax_i are XY of the measured light source.
It is the value converted from Z to LMS, Lmax_o, Mmax_o, Smax_o
Is a value obtained by converting the XYZ of the light source of the light source to be obtained into LMS.

FIG. 26 is a flowchart showing the flow of processing in the color correction processing method according to the fourth embodiment. The processing flow is the same as that shown in the third embodiment (see FIG. 23). Is added. In the following description, the same processes as those shown in FIG. 23 used in the third embodiment will be denoted by the same reference numerals, and description thereof will be omitted.

Referring to FIG. 26, in step S1410,
The initial settings by the control unit 120 include setting of data necessary for chromatic adaptation model processing, such as the above-described weight coefficients such as α and β, and the type of chromatic adaptation model. Step S1420
Then, after the input / output unit 130 captures the input grid data set in step S1410, measurement data of a predetermined color patch, and the like, the input / output unit 130 executes step S2623.
Then, the color adaptation model processing unit 220 performs the above color adaptation model processing using the designated color adaptation model. In steps after step S1725, the same processing as in the third embodiment is performed to form an LUT.

As described above, according to the fourth embodiment, it is possible to calculate the XYZ values for any light source by using the chromatic adaptation model.
This makes it possible to avoid the problem of color rendering properties in which colors do not match at all when the observation light sources are different.

[0070]

As described above, according to the present invention,
Since the input grid data is non-linearly converted using an S-shaped function such as the above-described saturation correction function or sigmoid function, the density of the grid near gray can be increased as compared with a conventional LUT, and the gray balance can be improved. A color correction processing method and apparatus that can be improved can be realized. Also, since the ratio of the grid in the color gamut can be increased, LU
The accuracy of T itself can be improved.

Further, according to the present invention, since the range correction processing for reproducing the dynamic range is performed, so-called black crushing can be prevented. In addition, since the γ correction for correcting the contrast is performed in the range γ correction processing, it is possible to prevent a shift in contrast that may occur due to the correction of the dynamic range.

According to the present invention, in addition to the range correction of the device and the range γ correction in the lightness direction, the saturation correction associated with the γ value used therein is performed, so that devices having different black levels are assumed. However, it is possible to obtain a more reproducible image output without blackening or black floating.

Further, according to the present invention, it is possible to calculate the XYZ values for any light source by using the chromatic adaptation model. It became possible to avoid the problem.

[Brief description of the drawings]

FIG. 1 is a diagram for explaining the concept of a DIC.

FIG. 2 is a diagram schematically showing a flow of processing for implementing a DIC.

FIG. 3 is a diagram schematically showing an inverse mapping of measurement data for generating an LUT.

FIG. 4 is a diagram showing a flow of a conventional process until a CMY output value corresponding to each grid in an L * a * b * space is calculated based on measurement data.

FIG. 5 is a diagram schematically showing that grid data arranged uniformly in a CMY space becomes irregular in an L * a * b * space.

Fig. 6 A hexahedron without distortion in CMY space is L * a * b *
It is a figure which shows typically becoming a distorted hexahedron in space.

FIG. 7 is a diagram for explaining that one hexahedron can be divided into five tetrahedrons.

FIG. 8 is a diagram for explaining a process of determining whether or not a point P in the L * a * b * space is within a certain tetrahedron (L * _p , a * _p , b * _p ); It is.

FIG. 9 is a diagram for explaining compression performed on a two-dimensional plane of lightness and saturation while preserving hue.

FIG. 10 is a diagram showing an overall configuration of a color correction processing device according to the first embodiment of the present invention.

FIG. 11 is a diagram showing an example of an S-shaped function used in grid conversion processing according to the first embodiment of the present invention.

FIG. 12 is a diagram illustrating another example of the S-shaped function used in the grid conversion processing according to the first embodiment of the present invention.

FIG. 13 is a diagram illustrating a sigmoid function and a saturation correction function when α = 5.

FIG. 14 is a flowchart showing a processing flow in a color correction processing method according to the first embodiment of the present invention.

FIG. 15 is a color correction processing apparatus 100 according to a second embodiment.
FIG. 2 is a diagram showing an overall configuration of the embodiment.

FIG. 16 is a diagram schematically illustrating a method of a range γ correction process according to the second embodiment.

FIG. 17 is a flowchart showing a flow of processing in a color correction processing method according to the second embodiment.

FIG. 18 is a flowchart illustrating a detailed flow of a range γ correction process according to the second embodiment.

FIG. 19 is a diagram illustrating an example of data before performing saturation correction, colorimetric data, and a change in saturation.

FIG. 20 is a color correction processing device 100 according to a third embodiment.
FIG. 2 is a diagram showing an overall configuration of the embodiment.

FIG. 21 is a diagram showing a fitting curve between γ and a parameter k.

FIG. 22 is a diagram illustrating an example of matching between data after saturation correction and colorimetric data.

FIG. 23 is a flowchart showing a flow of processing in a color correction processing method according to Embodiment 3.

FIG. 24 is a color correction processing apparatus 100 according to a fourth embodiment.
FIG. 2 is a diagram showing an overall configuration of the embodiment.

FIG. 25 is a diagram showing a conceptual flow of chromatic adaptation model processing using a chromatic adaptation model according to the fourth embodiment.

FIG. 26 is a flowchart showing a flow of processing in a color correction processing method according to Embodiment 4.

[Explanation of symbols]

100: color correction processing device, 110: operation unit, 120: control unit, 130: input / output unit, 140: color space conversion unit, 15
0: grid conversion unit, 160: in-gamut grid determination unit,
170: tetrahedral interpolation unit, 180: color gamut compression unit, 190 ...
Storage unit, 200: range γ correction unit, 210: saturation correction unit, 220: chromatic adaptation model processing unit

Continued on the front page F term (reference) 5B057 BA02 CA01 CA08 CA12 CA16 CB01 CB08 CB12 CB16 CC01 CE17 CE18 CH07 CH08 5C077 LL19 MM27 MP08 NP05 PP15 PP31 PP32 PP33 PP36 PP37 PP66 PQ23 RR19 5C079 HB01 HB02 HB05 LA06 MA04 MA10 MA11 NA03 NA21 PA03 5C082 AA01 AA27 AA32 BA34 BA39 BB51 CA12 CA81 CB01 DA71 MM10

Claims (10)

[Claims] 1. An image processing apparatus for converting a coordinate point in a color space between a color signal and a device signal based on a look-up table, the grid data being coordinate data of a grid point in a color space of the color signal. Input means for externally receiving data including measurement data obtained by measuring a color patch of a predetermined color and grid conversion means for non-linearly converting the coordinates of the grid points; and A lookup table generating unit that generates coordinates corresponding to the coordinates and forms a new lookup table; and an output unit that outputs predetermined data including the lookup table generated by the lookup table generating unit. A color correction processing device, characterized in that: 2. The image processing apparatus according to claim 1, further comprising a range γ correction unit that performs γ correction for correcting a dynamic range of a signal related to brightness of the grid data and γ for contrast correction. The color correction processing apparatus according to the above. 3. The color correction processing apparatus according to claim 2, wherein the image processing apparatus further includes a saturation correction unit that corrects a change in saturation caused by the processing by the range γ correction unit. 4. The image processing apparatus further includes a chromatic adaptation model processing unit that generates pseudo measurement data using a predetermined chromatic adaptation model, and wherein the look-up table generating unit includes a chromatic adaptation model processing unit. A new lookup table is generated for each measurement data using the plurality of measurement data including the generated pseudo measurement data, and a product sum of a corresponding element between the lookup tables of the respective measurement data and a predetermined weight coefficient And a new look-up table is formed for each of the corresponding elements.
4. The color correction processing device according to any one of claims 3 to 3. 5. The in-gamut grid determining unit that determines whether or not the coordinates of the non-linearly transformed grid points are included in a gamut obtained from the measurement data, wherein the look-up table generating unit includes: For the grid points determined to be included in the gamut, a predetermined interpolation process is performed using the coordinates of the grid points in the gamut and the measurement data, and a device signal corresponding to the coordinates of the grid points included in the gamut. A tetrahedral interpolation means for generating coordinates of the following, and for a grid point determined not to be included in the color gamut, a predetermined color gamut compression process is performed to correspond to the coordinates of the grid point not included in the color gamut. 5. The color correction processing apparatus according to claim 1, further comprising a color gamut compression unit that generates coordinates of the device signal. 6. An image processing method for converting a coordinate point in a color space between a color signal and a device signal based on a look-up table, the grid data being coordinate data of a grid point in the color space of the color signal. An input step of externally capturing data including measurement data obtained by measuring a color patch of a predetermined color and a grid conversion step of nonlinearly converting the coordinates of the grid points; and A lookup table generating step of generating coordinates corresponding to the coordinates to form a new lookup table; and an output step of outputting predetermined data including the lookup table generated in the lookup table generating step. A color correction processing method comprising: 7. The image processing method according to claim 6, further comprising a range γ correction step of performing a γ correction for correcting a dynamic range of a signal relating to brightness of the grid data and a correction of a contrast. The described color correction processing method. 8. The color correction processing method according to claim 7, wherein said image processing method further comprises a saturation correction step of correcting a change in saturation caused by the processing in said range γ correction step. 9. The image processing method further includes a chromatic adaptation model processing step of generating pseudo measurement data using a predetermined chromatic adaptation model, wherein the look-up table generating step is performed in the chromatic adaptation model processing step. A new lookup table is generated for each measurement data using the plurality of measurement data including the generated pseudo measurement data, and a product sum of a corresponding element between the lookup tables of the respective measurement data and a predetermined weight coefficient 9. The color correction processing method according to claim 6, wherein a new look-up table is formed by taking the corresponding element for each corresponding element. 10. The in-gamut grid determining step of determining whether or not the coordinates of the non-linearly transformed grid points are included in a gamut obtained from the measurement data, wherein the look-up table generating step includes: For the grid points determined to be included in the gamut, a predetermined interpolation process is performed using the coordinates of the grid points in the gamut and the measurement data, and a device signal corresponding to the coordinates of the grid points included in the gamut. A tetrahedral interpolation step of generating coordinates, and performing a predetermined color gamut compression process on the grid points determined not to be included in the color gamut to correspond to the coordinates of the grid points not included in the color gamut. 10. The color correction processing method according to claim 6, further comprising a color gamut compression step of generating coordinates of the device signal.