JP2011223298A - Method and program for color conversion table creation, and printer - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make a minimum point to be set controllable in an optimization processing for searching an ink amount set of an ink color-system consisted of multiple ink types corresponding to coordinate value of an input color-system.SOLUTION: A method for creating a color conversion table to convert the coordinate value of the input color-system into the ink amount set of the ink color-system consisted of multiple ink types includes the optimization processing to determine the ink amount of the ink color-system corresponding to the coordinate value of the input color-system by performing the multiple optimizations using an objective function E represented by combinations of multiple image quality evaluation indexes, weighted each; and a weighting control processing to make the weight on the multiple image evaluation indexes change in each of the optimizations.

Description

  The present invention relates to a color conversion table creation method, a color conversion table creation program, and a printing apparatus, and in particular, converts an input color coordinate system coordinate value into an ink color set ink amount set composed of a plurality of types of ink. The present invention relates to a color conversion table creation method, a color conversion table creation program, and a printing apparatus including a color conversion table created by the creation method.

  The color conversion correspondence information is information indicating a correspondence relationship between the input color system and the output color system, and is used in a format such as a color conversion table or a color conversion function, for example. The coordinate value of the input color system in the color conversion table represents the position of the point in the color space of the input color system, and the coordinate value of the output color system is the position of the point in the color space of the output color system. Represents. The points in the color space of the output color system correspond to the ink amount set of the ink color system. In the present specification, points in an arbitrary color space are also referred to as “color points” or “grid points”. Also, the color point represented by the input value and the color point represented by the output value registered in the color conversion table are also referred to as “input grid point” and “output grid point”, respectively.

  As a technique for optimizing the output grid point corresponding to the input grid point of the color conversion table, for example, there is one described in Patent Document 1 disclosed by the applicant of the present application. In the optimization described in this document, after moving the grid point of the Lab color system, an input color specification is performed using an optimization process using an objective function configured by a combination of a plurality of image quality evaluation indices. The optimum ink amount corresponding to the grid points of the system is determined. This optimum ink amount is determined as the ink amount that minimizes the objective function.

JP 2008-263579 A

However, in the optimization process described in Patent Document 1 described above, the optimal ink amount may not be reached and the local minimum may be settled. On the other hand, there is a case where the user wants to settle down to a specific local minimum, but settles to the minimum value or falls into another local minimum.
The present invention provides a color that enables control of a minimum point to be optimized in an optimization process for searching for an ink amount set of an ink color system comprising a plurality of types of ink corresponding to coordinate values of an input color system. It is an object of the present invention to provide a conversion table creation method, a color conversion table creation program, and a printing apparatus on which the created color conversion table is mounted.

  SUMMARY An advantage of some aspects of the invention is to solve at least a part of the problems described above, and the invention can be implemented as the following forms.

As one aspect of the present invention, there is provided a method for creating a color conversion table for converting an input color coordinate system coordinate value into an ink color set ink amount set composed of a plurality of types of ink, the input color specification Optimum that is determined by performing the optimization using a predetermined objective function that is expressed by a combination of a plurality of image quality evaluation indexes weighted to each of the ink color system corresponding to the coordinate value of the system multiple times. Based on the ink amount determined by the optimization step, the weight management step for changing the weights for the plurality of image quality evaluation indices for each time of the optimization, and the optimization step, the coordinate values of the input color system A color conversion table creating step for creating a color conversion table for converting into the ink amount of the ink color system.
According to this configuration, in an optimization process for searching for an ink color set of an ink color system composed of a plurality of types of ink corresponding to the coordinate values of the input color system, an optimal solution obtained as a result of the optimization is obtained. It becomes possible to control.

Further, as a selective aspect of the present invention, in the weight management step, the weight is gradually changed so that the image quality evaluation index with higher importance increases as the number of optimizations in the optimization step proceeds. It is good also as a structure.
According to this configuration, the optimum solution is gradually derived from the optimum solution obtained by the objective function given the initial weighting factor to the optimum solution obtained by the objective function given the final weighting factor. Can do. For example, when optimization processing is performed using an objective function expressed by weighting a fixed weight to each of a plurality of image quality evaluation indexes, if the local minimum tends to fall, By performing weighting so as to reduce the depth, or by performing weighting so that a deep minimum point is generated in a place other than the local minimum, it is possible to control to prevent falling into a specific local minimum.

Further, as a selective aspect of the present invention, in the weight management step, the weight is set so that the image quality evaluation index having higher importance in the initial stage of the optimization step becomes larger, and the optimization step ends. The image quality evaluation index, which is sometimes less important, may be configured to gradually change so that the weight becomes relatively larger than the weight at the initial stage of the optimization process.
According to this configuration, the local minimum formed due to the image quality evaluation index having high importance in the objective function given the final weighting factor is emphasized in the objective function given the initial weighting factor ( It is possible to guide the optimal solution obtained by the initial optimization process to the local minimum. Thereafter, the optimum solution is gradually changed from the initial weighting factor to the final weighting factor so that the weight becomes relatively large with respect to the weighting at the initial stage of the optimization step. It is difficult to move from the local minimum, and the optimal solution obtained as a result of the final optimization can be controlled so as to easily converge to the vicinity of the local minimum.

Further, as a selective aspect of the present invention, in the weight management step, the weight is averagely set with a plurality of the image quality evaluation indexes in the initial stage of the optimization step, and is important at the end of the optimization step. The higher the image quality evaluation index, the more gradually the weight may be changed so as to be relatively larger than the weight at the initial stage of the optimization process.
According to this configuration, the optimum solution obtained by the initial optimization process can be guided to an average optimum solution that takes each image quality evaluation index into consideration in a balanced manner. Thereafter, the weight is gradually changed from the initial weighting factor to the final weighting factor so that the weight becomes relatively larger than the initial weighting factor in the optimization step. It is possible to control the optimum solution to be easily converged to the minimum point in the vicinity of the average optimum solution considering each image quality evaluation index in a well-balanced manner.

  The above-described color conversion table creation method includes various modes such as being implemented as part of another method or realized as a color conversion table creation device having means corresponding to each process. Further, the present invention provides a color conversion table creation system including the color conversion table creation device, a color conversion table creation program for causing a computer to realize a function corresponding to the configuration of the above-described method, and a computer readable recording the program. It can also be realized as a simple recording medium. Furthermore, since the printed matter created by the printing executed by the printing apparatus mounted with the color conversion table created by the creation method or the like can reproduce the color reflecting the control result of the weight of the image quality evaluation index. The printing apparatus is also an embodiment of the present invention. That is, the invention of the color conversion table creation device, the color conversion table creation system, the color conversion table creation program, the medium on which the program is recorded, and the printing device also have the above-described operations and effects.

It is a block diagram which shows the structure of the lookup table preparation apparatus in one Example of this invention. It is a flowchart which shows the whole process sequence of an Example. It is explanatory drawing which shows the processing content in the case of producing a base 3D-LUT. It is explanatory drawing which shows the correspondence of the color point of RGB color system which is an input color system, and the color point of Lab color system. It is explanatory drawing which shows the processing content in the case of producing a base 4D-LUT by step S100-S300 of FIG. It is explanatory drawing which shows the preparation method of the color correction LUT using base LUT. It is explanatory drawing which shows the dynamic model utilized for the smoothing process of an Example. It is a flowchart which shows the typical process sequence of a smoothing process. It is a flowchart which shows the detailed procedure of step T100 of FIG. It is explanatory drawing which shows the processing content of step T120-T150 of FIG. It is a flowchart which shows the flow of a setting process of LUT creation conditions. The UI screen displayed at step T91 is shown. It is a figure explaining the weight balance in the case of optimizing to a comprehensive optimal solution. It is a figure explaining the weight balance in the case of giving priority to the optimization regarding the most important image quality element. It is a flowchart which shows the detailed procedure of an optimization process (step T130 of FIG. 8).

Next, embodiments of the present invention will be described in the following order.
(1) Device configuration and overall processing procedure:
(2) Mechanical model:
(3) Smoothing process (smoothing / optimization process):
(4) Setting LUT creation conditions:
(5) Optimization process:
(6) Modification:

(1) Device configuration and overall processing procedure:
FIG. 1 is a block diagram showing the configuration of a lookup table creation apparatus in an embodiment of the present invention. This apparatus includes a base LUT creation module 100, a color correction LUT creation module 200, a forward model converter 300, and an LUT storage unit 400. “LUT” is an abbreviation for a lookup table as a color conversion profile. In this embodiment, this color conversion profile constitutes a color conversion table. The functions of the modules 100 and 200 and the converter 300 are realized by the computer executing an LUT creation program that is a computer program stored in the memory. The LUT storage unit 400 is realized by a recording medium such as a hard disk device.

  The base LUT creation module 100 includes a smoothing processing initial value setting module 120, a smoothing processing module 130, and a table creation module 140. The smoothing processing module 130 includes a color point movement module 132, an optimization condition setting module 133, an ink amount optimization module 134, and an image quality evaluation index calculation module 136. The forward model converter 300 includes a spectral printing model converter 310 and a color calculation unit 320. The functions of these parts will be described later.

  The LUT storage unit 400 is for storing the inverse model initial LUT 410, the base 3D-LUT 510, the base 4D-LUT 520, the color correction 3D-LUT 610, the color correction 4D-LUT 620, and the like. However, LUTs other than the inverse model initial LUT 410 are created by the base LUT creation module 100 and the color correction LUT creation module 200. The base 3D-LUT 510 is a color conversion lookup table that receives an RGB color system and outputs an ink amount. On the other hand, the base 4D-LUT 520 is a color conversion lookup table that receives the CMYK color system and outputs the ink amount. “3D” and “4D” mean the number of input values. The base 3D-LUT 510 and the base 4D-LUT 520 are used when, for example, the color correction 3D-LUT 610 and the color correction 4D-LUT 620 are created. This is because the name “base LUT” is used as a basis for creating a color correction LUT. The color correction 3D-LUT 610 and the color correction 4D-LUT 620 are lookups for converting a standard device-dependent color system (for example, sRGB color system or JAPAN COLOR 2001 color system) into an ink amount of a specific printer. It is a table. The inverse model initial LUT 410 will be described later.

FIG. 2 is a flowchart showing an overall processing procedure of the embodiment. 3A to 3C are explanatory diagrams showing processing contents when a base 3D-LUT is created by steps S100 to S300 of FIG. In step S100, a forward model converter 300 and an inverse model initial LUT 410 are prepared. Here, the “forward model” means a conversion model that converts the ink amount into a color value (colorimetric value) of a device-independent color system. On the contrary, an “inverse model” is a device-independent table. It means a conversion model that converts color values of color system into ink amount. In the embodiment, the CIE-Lab color system is used as the device-independent color system. Hereinafter, the color value of the CIE-Lab color system is also simply referred to as “L ^* a ^* b ^* value” or “Lab value”.

As shown in FIG. 3A, the forward model converter 300 includes a spectral printing model converter 310 at the front stage and a color calculation unit 320 at the rear stage.
The spectral printing model converter 310 converts the ink amounts of a plurality of types of inks into spectral reflectances R (λ) of color patches to be printed according to the ink amounts. In the present specification, the term “color patch” is used in a broad sense including not only a chromatic color patch but also an achromatic color patch. In this embodiment, cyan (C), magenta (M), yellow (Y), black (K), light cyan (Lc), light magenta (Lm), light black (Lk), and very light black (LLk). A color printer that can use eight types of ink is assumed, and the spectral printing model converter 310 also receives the ink amounts of these eight types of ink. However, an arbitrary ink set can be used as the plurality of types of ink used in the printer. As a method for creating the spectral printing model converter 310, for example, a method described in JP-T-2007-511175 can be employed.
The color calculation unit 320 calculates a color value of the Lab color system from the spectral reflectance R (λ). For the calculation of the color value, a light source (for example, standard light D50) selected in advance is used as a color patch observation condition.

The inverse model initial LUT 410 is a look-up table having an L ^* a ^* b ^* value as an input and an ink amount as an output. The inverse model initial LUT 410 is obtained by, for example, dividing the L ^* a ^* b ^* space into a plurality of small cells and selecting and registering an optimum ink amount for each small cell. This selection is performed in consideration of, for example, the image quality of the color patch printed with the ink amount. In general, there are many combinations of ink amounts that reproduce a certain L ^* a ^* b ^* value. Therefore, in the inverse model initial LUT 410, an optimum ink amount selected from a desired viewpoint such as image quality is registered from among a large number of ink amount combinations that reproduce substantially the same L ^* a ^* b ^* value. . The L ^* a ^* b ^* value that is the input value of the inverse model initial LUT 410 is a representative value of each small cell. On the other hand, the ink amount as an output value reproduces any L ^* a ^* b ^* value in the cell.

Therefore, in the inverse model initial LUT 410, the L ^* a ^* b ^* value that is the input value and the ink amount that is the output value do not correspond exactly, and the ink amount of the output value is converted to the forward model converter 300. When converted into L ^* a ^* b ^* values, a value slightly different from the input value of the inverse model initial LUT 410 is obtained. Of course, as the inverse model initial LUT 410, an input value and an output value completely corresponding to each other may be used. Further, if the L ^* a ^* b ^* value can be converted into the ink amount by a conversion formula or the like, the base LUT can be created without using the inverse model initial LUT 410. As a method for creating the inverse model initial LUT 410 by selecting an optimal ink amount for each small cell, for example, the method described in the Japanese translations of PCT publication No. 2007-511175 can be employed.

  In step S200 of FIG. 2, an initial input value for creating a base LUT is set by the user. FIG. 3B shows an example of the configuration of the base 3D-LUT 510 and its initial input value setting. As the input values of the base 3D-LUT 510, values at substantially equal intervals predetermined as RGB values are set. Since a set of RGB values is considered to represent a point in the RGB color space, the set of RGB values is also referred to as an “input grid point”.

  In step S200, the initial value of the ink amount for a small number of input grid points selected in advance from among the plurality of input grid points is input by the user. It is preferable to select at least an input grid point corresponding to a vertex of a three-dimensional color solid in the RGB color space as the input grid point to which the initial input value is set. At the apex of this three-dimensional color solid, each RGB value takes the minimum value or the maximum value of the definition range.

  Specifically, when each RGB value is expressed by 8 bits, (R, G, B) = (0, 0, 0), (0, 0, 255), (0, 255, 0) , (255, 0, 0), (0, 255, 255), (255, 0, 255), (255, 255, 0), (255, 255, 255). The initial input value is set. The ink amounts for the input grid points of (R, G, B) = (255, 255, 255) are all set to zero. The initial input value of the ink amount for the other input grid points is arbitrary, and is set to 0, for example. In the example of FIG. 3B, the ink amount with respect to the input grid point (R, G, B) = (0, 0, 32) is a value other than 0. This is the completion of the base 3D-LUT 510. This is the value when

In step S300 of FIG. 2, the smoothing processing module 130 (FIG. 1) executes smoothing processing (smoothing / optimization processing) based on the initial input value set in step S200. FIG. 3C shows the processing content of step S300. On the left side of FIG. 3C, the distribution of a plurality of color points in a state before the smoothing process is indicated by double circles and white circles. These color points constitute a three-dimensional color solid CS in the L ^* a ^* b ^* space. The L ^* a ^* b ^* coordinate value of each color point is obtained by converting the ink amount at a plurality of input grid points of the base 3D-LUT 510 into an L ^* a ^* b ^* value using the forward model converter 300 (FIG. 3A). This is the converted value. As described above, in step S200, the initial input value of the ink amount is set only for some small number of input grid points. Therefore, the initial value of the ink amount for the other input grid points is set by the smoothing process initial value setting module 120 (FIG. 1) based on the initial input value. This initial value setting method will be described later.

The three-dimensional color solid CS of the Lab color system has the following eight vertices (double circle points in FIG. 3C).
Point P _K : Paper black point corresponding to (R, G, B) = (0, 0, 0).
Point P _W : Paper white point corresponding to (R, G, B) = (255, 255, 255).
Point P _C : cyan point corresponding to (R, G, B) = (0, 255, 255).
Point P _M : Magenta point corresponding to (R, G, B) = (255, 0, 255).
Point P _Y : Yellow point corresponding to (R, G, B) = (255, 255, 0).
Point P _R : Red point corresponding to (R, G, B) = (255, 0, 0).
Point P _G : Green point corresponding to (R, G, B) = (0, 255, 0).
Point P _B : Blue point corresponding to (R, G, B) = (0, 0, 255).

The right side of FIG. 3C shows the distribution of color points after the smoothing process. The smoothing process is a process of moving a plurality of color points in the L ^* a ^* b ^* space and smoothing the distribution of these color points at nearly equal intervals. In the smoothing process, an optimum ink amount is also determined for reproducing the L ^* a ^* b ^* values of the respective color points after movement. When the optimum ink amount is registered as the output value of the base 3D-LUT 510, the base 3D-LUT 510 is completed.

  4A to 4C show the correspondence between the color point of the input color system (that is, the input grid point) and the color point of the Lab color system. The vertices of the Lab color system three-dimensional color solid CS correspond one-to-one with the vertices of the input color system three-dimensional color solid of the base 3D-LUT 510. Also, the sides (ridge lines) connecting the vertices can be considered to correspond to each other in both color solids. Each color point of the Lab color system before the smoothing process is associated with each input grid point of the base 3D-LUT 510. Therefore, each color point of the Lab color system after the smoothing process is also input to the input grid point of the base 3D-LUT 510. Each is associated with a point. Note that the input grid points of the base 3D-LUT 510 are not changed by the smoothing process. The three-dimensional color solid CS of the Lab color system after the smoothing process corresponds to the entire color gamut (color gamut) that can be reproduced by the ink set constituting the output color system of the base 3D-LUT 510. Therefore, the input color system of the base 3D-LUT 510 has significance as a color system that represents the entire color gamut that can be reproduced by this ink set.

The reason for performing the smoothing process in the L ^* a ^* b ^* space when creating the base 3D-LUT 510 is as follows. In the base 3D-LUT 510, there is a demand for setting the amount of ink in the output color system so that a color gamut as large as possible can be reproduced. The color gamut that can be reproduced with a specific ink set is determined in consideration of predetermined limiting conditions such as ink duty limitation (limitation of the amount of ink that can be ejected to a certain area). On the other hand, the forward model converter 300 described above is created regardless of the reproducible color gamut without taking these restrictions into consideration. Therefore, if the range that can be taken by the color point in the L ^* a ^* b ^* space is determined in consideration of limiting conditions such as ink duty limitation during the smoothing process, a color gamut that can be reproduced with a specific ink set is determined. It becomes possible to do. As an algorithm for moving the color point, for example, an algorithm using a dynamic model described later is used.

  In step S400 of FIG. 2, the table creation module 140 creates the base 3D-LUT 510 using the result of the smoothing process. In other words, the table creation module 140 registers the optimum ink amount for reproducing the color point of the Lab color system associated with each input grid point as the output value of the base 3D-LUT 510 (FIG. 3C). To do. In the smoothing process, in order to reduce the calculation load, it is possible to select only the color points corresponding to only a part of the input grid points of the base 3D-LUT 510 as the processing target. For example, when the RGB value interval at the input grid point of the base 3D-LUT 510 is 16, if the RGB value interval at the input grid point to be smoothed is set to 32, the load of the smoothing process is reduced by half. be able to. In this case, the table creation module 140 determines and registers the ink amount for all the input grid points of the base 3D-LUT 510 by interpolating the smoothing processing result.

  FIGS. 5A to 5C are explanatory diagrams showing processing contents when the base 4D-LUT 520 is created by steps S100 to S300 of FIG. FIG. 5A is the same as FIG. A base 4D-LUT 520 shown in FIG. 5B is different from the base 3D-LUT 510 shown in FIG. 3B in that the input is a CMYK color system. As an initial input value of the base 4D-LUT 520, (C, M, Y, K) = (0, 0, 0, 0), (0, 0, 255, 0), (0, 255, 0, 0) ), (0, 255, 255, 0), (255, 0, 0, 0), (255, 0, 255, 0), (255, 255, 0, 0), (255, 255, 255, 0) ), (0, 0, 0, 255), (0, 0, 255, 255), (0, 255, 0, 255), (0, 255, 255, 255), (255, 0, 0, 255) ), (255, 0, 255, 255), (255, 255, 0, 255), (255, 255, 255, 255), the initial value of the ink amount is set for 16 input lattice points. The initial input value of the ink amount for the other input grid points is arbitrary, and is set to 0, for example.

FIG. 5C shows a state of the smoothing process. As the color solid corresponding to the base 4D-LUT 520 in the L ^* a ^* b ^* space, as shown at the right end of FIG. 5C, there is one color solid for each K value of the input values. There is a three-dimensional color solid CS. In this example, a plurality of color solids CS including a color solid of K = 0 and a color solid of K = 32 are illustrated. In the present specification, these individual color solids CS are also referred to as “K layers”. This is because each color solid CS can be considered to correspond to an input layer in which the K value among the CMYK values is constant and the C, M, and Y values are variable. The plurality of color solids CS represent a dark color gamut as the K value increases. The plurality of color solids CS can be realized by determining the ink amount of the dark black ink K so that the ink amount of the dark black ink K increases as the K value of the input color system increases. As described above, the reproducible color gamut is limited by the ink duty limit value. As the ink duty limit value, two limit values are generally imposed, that is, the ink amount of each ink and the total ink amount of all inks. On the other hand, methods for reproducing dark colors include a method using achromatic ink such as dark black ink K and a method using composite black. However, since composite black has a large total ink amount, it is more likely to conflict with the ink duty limit value than dark black ink K, which is disadvantageous for reproducing dark colors. Therefore, a color solid having a large K value in the input color system and a large amount of dark black ink K is more than a color solid having a small K value in the input color system and a small amount of dark black ink K. Dark colors can be reproduced.

6A and 6B are explanatory diagrams of a method for creating a color correction LUT that is performed based on the base LUT. As shown in FIG. 6A, the base 3D-LUT 510 defines the correspondence between the RGB values and the ink amount I _j . Since the ink amount I _j represents the ink amounts of the eight types of ink shown in FIG. 3B, the subscript _j of the ink amount I j is 1 to 8. The ink amount I _j converted from the RGB values with reference to the base 3D-LUT 510 is converted into L ^* a ^* b ^* values by the forward model converter 300.
On the other hand, the sRGB values are converted into L ^* a ^* b ^* values according to a known conversion formula. The L ^* a ^* b ^* value after this conversion is gamut-mapped so that the color gamut matches the color gamut of the L ^* a ^* b ^* value converted by the forward model converter 300.

On the other hand, through the base 3D-LUT 510 and the forward model converter 300, an inverse conversion LUT 511 is created using the L ^* a ^* b ^* values converted from the RGB values as a reverse lookup table. The gamut-mapped L ^* a ^* b ^* values are converted into RGB values by the inverse conversion LUT511. This RGB value is further converted again into the ink amount I _j by the base 3D-LUT 510. The color correction 3D-LUT 610 can be created by registering the correspondence between the last ink amount I _j and the first sRGB value in the lookup table. The color correction 3D-LUT 610 is a color conversion table for converting the sRGB color system to the ink color system.

FIG. 6B shows a method for creating the color correction 4D-LUT 620. The difference from FIG. 6A is that, instead of the base 3D-LUT 510 and its inverse transformation LUT 511, the base 4D-LUT 520 and its inverse transformation LUT 521 are used, and the sRGB color system is changed to L ^* a ^* b. ^* Instead of a known conversion formula that converts to a value, a known conversion formula that converts a JAPAN COLOR color system (shown as “jCMYK” in the figure) to an L ^* a ^* b ^* value is used. . As is well known, JAPAN COLOR is a color system composed of four colors of CMYK. In the method of FIG. 6B, when converting the L ^* a ^* b ^* value into the CMYK value in the inverse transformation LUT 521, the K value of the inverse transformation LUT 521 is calculated from the first K value of the jCMYK value before the known transformation. A layer (a portion where the K value is constant) is selected. Therefore, it is possible to create a color correction 4D-LUT 620 that reflects the characteristics of the K layer in the base 4D-LUT 520. Step S400 executed by the table creation module 140 as described above constitutes a color conversion table creation step in this embodiment.

  Normally, the base 3D-LUT 510 and the base 4D-LUT 520 are mounted on the printer driver, and are used for processes other than the color correction LUT creation process. However, description of other utilization examples is omitted here. To do. In the following, after briefly explaining the dynamic model used in the smoothing process (smoothing / optimization process) of the embodiment, the processing procedure of the smoothing process and the contents of the optimization process will be described sequentially.

ここで、Ｆ_gは着目色点ｇが隣接色点ｇｎ（ｎは１〜Ｎ）から受ける引力の合計値、Ｖ_gは着目色点ｇの速度ベクトル、−ｋ_vＶ_gは速度に応じた抵抗力、Ｘ_gは着目色点ｇの位置ベクトル、Ｘ_gnは隣接色点ｇｎの位置ベクトル、ｋ_p，ｋ_vは係数である。係数ｋ_p，ｋ_vは予め一定の値に設定される。なお、文中では、ベクトルを示す矢印は省略される。 (2) Mechanical model:
FIG. 7 is an explanatory diagram illustrating a dynamic model used for the smoothing process (smoothing / optimization process) of the present embodiment. Here, a state in which a plurality of color points (white circles and double circles) are arranged in the L ^* a ^* b ^* color space is shown. However, for convenience of explanation, the arrangement of the color points is drawn two-dimensionally here. In this dynamic model, it is assumed that virtual force Fp _g of the following formula with respect to focus color point g is applied.

Here, F _g is a total value of the attractive force received by the target color point g from the adjacent color points gn (n is 1 to N), V _g is a velocity vector of the target color point g, and −k _v V _g is a velocity. Resistance, X _g is a position vector of the target color point g, X _gn is a position vector of the adjacent color point gn, and k _p and k _v are coefficients. The coefficients k _p and k _v are set to constant values in advance. In the text, the arrow indicating the vector is omitted.

This dynamic model is a damped vibration model of mass points connected to each other by springs. That is, the virtual force Fp _g according to the target color point g is a focusing color point g and the spring force F _g, which distance increases larger with adjacent color points gn, increases as the speed of the target color point g is large resistance -K _v V _g and the total value. In this dynamic model, for each color point, after setting the initial value of the position vector X _g and the velocity vector F _g, it slides into successively calculates the position vector X _g and the velocity vector F _g after the lapse of short time. Note that the initial value of the velocity vector V _g for a plurality of color points is set to 0, for example. By using such a dynamic model, each color point moves gradually, and a smooth color point distribution can be obtained.

Note that forces other than the spring force F _g and the resistance force −k _v V _g may be used as the force related to each color point. For example, various other forces described in Japanese Patent Laid-Open No. 2006-197080 disclosed by the present applicant may be used in this dynamic model. Further, when moving each color point by applying a dynamic model, a specific color point can be handled as a constraint point that does not move by the dynamic model.

(3) Smoothing process:
FIG. 8 is a flowchart showing a typical processing procedure of the smoothing process (smoothing / optimization process) performed in step S300 of FIG. In step T90, the optimization condition setting module 133 accepts the LUT creation condition in the smoothing process. This LUT creation condition is a guideline for the optimization process, and corresponds to a creation condition for an objective function used in the optimization process in step T130 described later. The LUT creation conditions will be described later. Next, in step T100, the smoothing process initial value setting module 120 (FIG. 1) initializes a plurality of color points to be subjected to the smoothing process.

ここで、Ｉ_(R,G,B)は、入力格子点のＲＧＢ値に対するインクセット全体のインク量（図３の例では８種類のインクのインク量）を表している。ＲＧＢ値が０または２５５を取る入力格子点に対するインク量は、図２のステップＳ２００においてユーザーによって予め入力された値である。前記（２）式および（３）式によれば、任意のＲＧＢ値における仮インク量Ｉ_(R,G,B)を求めることが可能である。 FIG. 9 is a flowchart showing a detailed procedure of step T100 in FIG. In step T102, a temporary ink amount for each color point to be subjected to the smoothing process is determined from the initial input value of the ink amount (FIGS. 3B and 5B). For example, in the smoothing process for 3D-LUT, the temporary ink amount I _{(R, G, B)} for each input grid point is determined according to the following equations (2) and (3).

Here, I _{(R, G, B)} represents the ink amount of the entire ink set with respect to the RGB values of the input lattice points (in the example of FIG. 3, the ink amounts of eight types of ink). The ink amount for the input grid point where the RGB value takes 0 or 255 is a value input in advance by the user in step S200 of FIG. According to the equations (2) and (3), the temporary ink amount I _{(R, G, B)} at an arbitrary RGB value can be obtained.

In the smoothing process for 4D-LUT, the temporary ink amount I _{(C, M, Y, K)} for each input grid point is determined according to the following equations (4) and (5).

ここで、Ｉ_(C,M,Y,0)は、Ｋ＝０の８個の頂点におけるインク量の初期入力値から、前記（２）式と同様の式で算出されたインク量である。（６）式の関数ｆ _D1は値Ｉ_(C,M,Y,0)と値Ｉ_(0,0,0,255)の合計値がインクデューティ制限値をオーバーする場合に、値Ｉ_(C,M,Y,0)を減じることによって、インク量Ｉ_(C,M,Y,255)がインクデューティ制限値内に納まるようにする関数である。また、（７）式の関数ｆ _D2は、値Ｉ_(C,M,Y,0)と値Ｉ_(0,0,0,255)の合計値がインクデューティ制限値をオーバーする場合に、合計値（Ｉ_(C,M,Y,0)＋Ｉ_(0,0,0,255)）の全体を減じることによって、インク量Ｉ_(C,M,Y,255)がインクデューティ制限値内に納まるようにする関数である。なお、インク量Ｉ_j（Ｉ _j(R,G,B)，ΔＩ_j，Ｉ_jr，ｈ_jも含む）を下付文字ｊを付すことなく示す場合は、各インクのインク量Ｉ_jを各行要素として有する行列（ベクトル）を意味することとする。 As can be understood from the equation (4), since there are 16 initial input values of the ink amount for 4D-LUT, setting of the initial input value is complicated. Therefore, for example, the input grid points for setting the initial input value of the ink amount are eight vertices of K = 0, that is, (C, M, Y, K) = (0, 0, 0, 0), ( 0,0,255,0), (0,255,0,0), (0,255,255,0), (255,0,0,0), (255,0,255,0), ( 8 vertices of 255, 255, 0, 0), (255, 255, 255, 0) and 1 vertex of K = 255, for example, (C, M, Y, K) = (0, 0) , 0, 255) only, and the ink amount of the color point of K = 255 may be determined by the following equation (6) or (7).

Here, I _{(C, M, Y, 0)} is an ink amount calculated from the initial input value of the ink amount at eight vertices of K = 0 by the same expression as the expression (2). (6) the function f _D1 is the value I _{(C, M, Y, 0)} if the total value of the value I _{(0, 0, 0, 255)} is over the ink duty limit value I _{(C, M , Y, 0)} is a function for keeping the ink amount I _{(C, M, Y, 255)} within the ink duty limit value. Further, the function f _{D2 in the} equation (7) is _{calculated when} the total value of the value I _{(C, M, Y, 0)} and the value I _{( 0, 0, 0, 255)} exceeds the ink duty limit value ( A function for _keeping the ink amount I _{(C, M, Y, 255)} within the ink duty limit value by subtracting the total of I _{(C, M, Y, 0)} + I _{( 0, 0, 0 , 255))} It is. In addition, when the ink amount I _j (including I _{j (R, G, B)} , ΔI _j , I _jr , h _j ) is indicated without the subscript j, the ink amount I _j of each ink is indicated in each row. It means a matrix (vector) having elements.

ここで、Ｌ^* _(R,G,B)、ａ^* _(R,G,B)、ｂ^* _(R,G,B)、Ｌ^* _(C,M,Y,K)、ａ^* _(C,M,Y,K)、ｂ^* _(C,M,Y,K)は変換後の色彩値Ｌ^*ａ^*ｂ^*を示しており、関数ｆ_L*FM、ｆ_a*FM、ｆ_b*FMはフォワードモデルコンバーター３００による変換を意味している。なお、これらの式からも理解できるように、この変換後の色彩値Ｌ^*ａ^*ｂ^*は、ベースＬＵＴの入力値であるＲＧＢ値またはＣＭＹＫ値に対応したものとなる。 In Step T104 of FIG. 9, the forward model converter 300 is used to obtain a color value L ^* a ^* b ^* corresponding to the temporary ink amount. This calculation can be expressed by the following equation (8) or (9).

Here, L ^* _{(R, G, B)} , a ^* _{(R, G, B)} , b ^* _{(R, G, B)} , L ^* _{(C, M, Y, K)} , a ^* _{(C, M, Y, K)} and b ^* _{(C, M, Y, K)} indicate the color values L ^* a ^* b ^* after conversion, and the functions f _{L * FM} , f _{a * FM} , f _{b * FM} Means conversion by the forward model converter 300. As can be understood from these equations, the converted color value L ^* a ^* b ^* corresponds to the RGB value or CMYK value that is the input value of the base LUT.

In step T106 in FIG. 9, the color value L ^* a ^* b ^* obtained in step T104 is converted again into an ink amount using the inverse model initial LUT 410 (FIG. 3A). Here, the reason why the ink amount is converted again using the inverse model initial LUT 410 is that the initial input value of the ink amount or the temporary ink amount determined in step T102 is the ink amount that reproduces the L ^* a ^* b ^* value. This is because the ink amount is not always preferable. Here, in the inverse model initial LUT 410, a preferable ink amount that takes image quality and the like into consideration is registered. If the L ^* a ^* b ^* value is converted again into the ink amount using this, the L ^* a ^* b ^* A preferable ink amount for realizing the value can be obtained as an initial value. However, since the ink amount is optimized by the optimization process described later, step T106 can be omitted.

As a result of the process in step T100 described above, the following initial values are determined for the color points to be subjected to the smoothing process.
(1) Input grid point value of base LUT: (R, G, B) or (C, M, Y, K)
(2) Initial coordinate values of color points in the L ^* a ^* b ^* space corresponding to each input grid point: (L ^* _{(R, G, B)} , a ^* _{(R, G, B)} , b ^* _{(R , G, B)} ) or (L ^* _{(C, M, Y, K)} , a ^* _{(C, M, Y, K)} , b ^* _{(C, M, Y, K)} )
(3) Initial ink amount corresponding to each input grid point: I _{(R, G, B)} or I _{(C, M, Y, K)}
As can be understood from the above description, the smoothing processing initial value setting module 120 has a function of setting initial values of ink amounts for other input grid points from initial input values of ink amounts for typical input grid points. ing. Note that the smoothing processing initial value setting module 120 may be included in the smoothing processing module 130.

In Step T120 of FIG. 8, the color point moving module 132 moves the color point in the L ^* a ^* b ^* space according to the dynamic model described above.

10A to 10D are explanatory diagrams showing the processing contents of steps T120 to T150 in FIG. As shown in FIG. 10A, there is a considerable bias in the distribution of color points before the smoothing process. FIG. 10B shows the position of each color point after the minute time has elapsed. The L ^* a ^* b ^* value of each color point after this movement is referred to as “target value LAB _t ”. This is because the target value LAB _t is used as a target value in the search process for the optimum value of the ink amount described below.

In Step T130, the ink amount optimizing module 134 searches for the optimum value of the ink amount with respect to the target value LAB _t using the preset objective function E (see FIG. 10C). In the optimization using the objective function E, a plurality of ink amounts I _j that reproduce L ^* a ^* b ^* values close to the coordinate value LAB _t of the color point after moving by a minute amount in the dynamic model. An ink amount whose parameter is as small as possible is determined as the optimum ink amount. The search for the optimum ink amount is started from the initial ink value of each input lattice point set in step T100. When the optimum ink amount I _j is determined for the lattice point after movement, the lattice is then determined by the dynamic model. When the point is moved, an optimum ink amount is searched from the ink amount I _j . Therefore, the ink amount obtained by the search is a value obtained by correcting this initial ink amount. The detailed procedure of step T130 and the contents of the objective function E will be described later.

In step T140 in FIG. 8, the L ^* a ^* b ^* value corresponding to the ink amount I _j searched in step T130 is recalculated by the forward model converter 300 (see FIG. 10D). Since the ink amount I _j searched in step T130 is the ink amount that minimizes the objective function E, the L ^* a ^* b ^* value reproduced with the ink amount I _j is somewhat from the target value LAB _t of the optimization process. It's off. By recalculating the L ^* a ^* b ^* values corresponding to the ink amount I _j, reproduction L ^* a ^* b ^* values of the searched ink amount I _j is calculated accurately. The L ^* a ^* b ^* values recalculated in this way are used as coordinate values after the movement of each color point.

In step T150, it is determined whether or not the average value (ΔLab) _ave of the movement amount of the coordinate value of each color point is equal to or less than a preset threshold value ε. When the average value (ΔLab) _{ave of the} movement amount is larger than the threshold value ε, the process returns to step T120 and the smoothing process of steps T120 to T150 is continued. On the other hand, when the average value (ΔLab) _{ave of} the moving amount is equal to or smaller than the threshold value ε, the color point distribution is sufficiently smoothed, and thus the smoothing process ends. Note that an appropriate value for the threshold ε is experimentally determined in advance.

  As described above, in the typical smoothing process (smoothing / optimization process) of the present embodiment, the optimum ink amount corresponding to the color point after the movement is obtained while moving each color point at every minute time interval by the dynamic model. Is searched with an optimization method. Then, these processes are continued until the movement amount of the color point becomes sufficiently small. As a result, as shown in FIG. 3C, a smooth color point distribution can be obtained by the smoothing process.

(4) Setting LUT creation conditions:
FIG. 11 is a flowchart showing the flow of the LUT creation condition setting process (step T90). The processing shown in the figure is executed by the optimization condition setting module 133. In step T91, the optimization condition setting module 133 displays the UI screen on the display, and accepts the type of printing paper used for printing and the designation of the observation light source for observing the printed matter.

  FIG. 12 shows the UI screen displayed in step T91. In the UI screen shown in the figure, it is possible to specify the type of printing paper and the observation light source for observing the printed matter. The base LUT created based on the LUT creation conditions is optimized for the type of printing paper and the observation light source specified here. Further, the UI screen shown in FIG. 6 enables the priority order of a plurality of image quality elements and the setting of which of the overall optimization and the optimization related to the most important image quality element should be prioritized. . In the UI screen shown in the figure, the priority of graininess, color constancy, gradation, and color reproduction gamut can be set as a plurality of image quality elements. In this embodiment, the priority set here indicates the importance of each image quality element.

  The user operates the mouse and keyboard to select the type of printing paper and the observation light source, and prioritizes setting of the priority of image quality elements, and overall optimization and optimization for the most important image quality elements. When the determination button is clicked, the optimization condition setting module 133 detects this and accepts these settings (T92). In the following description, it is assumed that glossy paper is selected as the printing paper, D65 is selected as the observation light source, and priority is set in the order of graininess, color constancy, gradation, and color reproduction gamut.

In step T93, the optimization condition setting module 133 sets the image quality evaluation function in the following equation (10) based on the type of printing paper and the observation light source set by the user, and the priority order of the image quality elements and the overall quality are determined. The weighting factors w _gr , w _CII , w _S , and w _ga in the following equation (10) are set on the basis of whether to prioritize which one of the optimizations and optimization regarding the most important image quality factor is given priority.

  In the above equation (10), E represents an objective function, and the smaller the objective function E, the higher the overall print performance under the LUT creation conditions set by the user in step S200. Have. In the equation (10), ψ is an ink amount set (dc, dm, dy, dk, dlc, dlm, dlk, dlm, meaning a combination of ink amounts of the respective inks of the set ink set (CMYKlcmlkllk) in the present embodiment. dllk). The first term of the above equation (10) is a term that requires the performance of the granularity of the printed matter. The second term is a term that requires the performance of color constancy with respect to fluctuations in the light source of the printing color. The third term is a term that requires the gradation performance of the printed matter. The fourth term is a term that requires the performance of the color reproduction gamut.

Each term is a scalar quantity normalized with the same size, and the smaller the value, the higher the printing performance. In addition, the first to fourth terms corresponding to each image quality element are linearly combined while adjusting the weights using individual weighting factors w _gr , w _CII , w _S , and w _ga, thereby evaluating the overall printing performance. A possible objective function E is defined. That is, the weighting factors w _gr , w _CII , w _S , and w _ga have meanings as values for adjusting which image quality element is important.

Also, the weighting factors w _gr , w _CII , w _S , and w _ga in the above equation (10) are expressed by the following equation (11).

In the above equation (11), n is a counter indicating the degree of progress of the optimization process, and in this embodiment is the number of times the optimization process has been performed. In addition, the number of times of executing the optimization process for optimizing the ink amount set corresponding to one grid point is defined in advance (10 times in the optimization process described later). w _gr0 , w _CII0 , w _S0 , and w _ga0 are initial values and are weighting coefficients used in the initial _stage of the optimization process. a _gr , a _CII , a _S , and a _ga are weight correction coefficients, and are coefficients for gradually changing the weight coefficient in accordance with the degree of progress of the optimization process. For example, as shown in the above equation (11), the weight coefficients are weight correction coefficients a _gr , a _CII , a _{S with} respect to the weight coefficients used in the immediately preceding optimization process every time the optimization process is repeated. , A _ga is multiplied. That is, the weighting factor is changed in stages as the optimization process proceeds.

In addition, the weighting factors w _gr , w _CII , w _S , and w _ga converge to the target weighting factors w _{gr_t} , w _{CII_t} , w _{S_t} , and w _{ga_t} step by step as the number of executions of the optimization process approaches the specified number. I will do it. That is, according to the degree of progress of the optimization process, the weight coefficients w _gr , w _CII , w _S , and w _ga are determined from the weight balance at the initial values w _gr0 , w _CII0 , w _S0 , and w _ga0 , and the target weight coefficient w _{gr — t} , W _{CII_t} , w _{S_t} , and w _{ga_t} are converged in stages. In the present embodiment, as shown in the above equation (11), the target weighting factor is reached when the number of optimizations reaches the specified number of times. Of course, the target weighting factor is reached before reaching the specified number of times. The weighting factor may not be changed in the optimization processing after reaching the target weighting factor so as to converge to w _{gr_t} , w _{CII_t} , w _{S_t} , and w _{ga_t.} It is also possible to change the weight coefficients w _gr , w _CII , w _S , and w _{ga according} to the weight correction coefficients a _gr , a _CII , a _S , and a _ga each time the process ends.
In this embodiment, the weight correction coefficient is changed in a geometric series. However, the weight correction coefficient may be changed by other methods, for example, the weight coefficient may be changed in an arithmetic series. Good. In this case, a predetermined weight correction amount is added to the initial value every time one optimization process is completed.

In addition, initial values w _gr0 , w _CII0 , w _S0 , w _ga0 and weight correction coefficients a _gr , a _CII , a _S , a _ga corresponding to each image quality element _relate to comprehensive optimization and the most important image quality elements. The magnitude relationship is set according to the setting of which optimization is prioritized. FIG. 13 is a diagram for explaining the weight balance in the case of optimization to a comprehensive optimum solution, and FIG. 14 is a diagram for explaining the weight balance in the case where priority is given to optimization regarding the most important image quality element.

First, when optimizing to a comprehensive optimum solution, as shown in FIG. 13, initial values w _gr0 , w _CII0 , w _S0 , and w _{ga0 relating} to image elements having a high priority are set for each weight coefficient. finally set to desired target weight coefficient _{w gr_t, w CII_t, w S_t} , compared to the weight balance in _w ga_t, are set so that the weight balance so as to have a relatively low weight.

For example, the weight balance of the target weight _{factors, w gr_t: w CII_t: w} S_t: w ga_t = 5: 4: 3: When a 2 weight balance of the initial value _{w gr0: w CII0: w S0} : w ga0 = 1: 1: 1: 1. In this example, the granularity weight coefficient w _gr which is the highest priority image quality element is 5/4 times the other weight coefficients w _CII , w _S and w _{ga in the} weight balance to be finally set. While the weight is 5/3 times and 5/2 times, the initial value is an average weight balance of 1 time with respect to other weighting factors. That is, the granularity weighting coefficient w _gr has a weight balance that is relatively lower than the target weighting coefficient at the initial value.

When the initial value is set with such a weight balance, the weight correction coefficient has a magnitude relationship according to the priority order of the image quality elements. That is, as described above, when the weight balance to be finally set is w _gr > w _CII > w _S > w _ga , the magnitude relationship of the weight correction coefficients is a _gr > a _CII as in the priority order of the image quality elements. > A _S > a _ga . In this way, by setting the weight balance of the initial value of the weighting factor and the magnitude relationship between the weighting correction factors, the initial optimization process allows a state in which the image quality element to be emphasized cannot be sufficiently optimized, and thereafter The weighting factor is adjusted step by step so that the weight balance of the target weighting factor is achieved. Therefore, the objective function for which the target weighting factor has been set is gradually led to a comprehensively optimal ink amount set, so it is possible to search for an ink amount set that is less likely to fall into a local minimum and that has a desired image quality factor. It becomes.

On the other hand, when the optimization regarding the most important image quality element is given priority, as shown in FIG. 14, the initial values w _gr0 , w _CII0 , w _S0 , and w _ga0 of the higher priority are _assigned to the respective weight coefficients. finally set to desired target weight coefficient w _{Gr_t} Te, w _{CII_t,} w _{S_t,} compared to the weight balance in _w ga_t, it is set so that the weight balance so as to have a relatively high weight.

For example, the weight balance of the target weight _{factors, w gr_t: w CII_t: w} S_t: w ga_t = 5: 4: 3: When a 2 weight balance of the initial value _{w gr0: w CII0: w S0} : w ga0 = 9: 7: 5: 3, etc. In this example, the granularity weight coefficient w _gr which is the highest priority image quality element is 5/4 times the other weight coefficients w _CII , w _S and w _{ga in the} weight balance to be finally set. Although the weights are 5/3 times and 5/2 times, the initial values are 9/7 times, 9/5 times, and 9/3 times the other weighting factors, respectively. That is, the granularity weight coefficient w _gr has a weight balance that is relatively higher than the target weight coefficient at the initial value.

When the initial value is set with such a weight balance, the weight correction coefficient has a magnitude relationship opposite to the priority order of the image quality elements. That is, as described above, when the weight balance to be finally set is w _gr > w _CII > w _S > w _ga , the magnitude relationship between the weight correction coefficients is a _gr < a _CII <a _S <a _ga . In this way, by setting the weight balance of the initial value of the weighting coefficient and the magnitude relationship between the weight correction coefficients, in the initial optimization process, the image quality element to be emphasized is preferentially optimized, and then The weight coefficient is adjusted step by step so that the weight balance desired to be originally set is obtained in total for all image quality elements. Therefore, if a local minimum is reached in the initial optimization process, it is likely that the local minimum has been reached at the end of the optimization process, and particularly good image quality is reproduced for the image element with the highest priority. An LUT can be created.

  The graininess index GR, the color constancy index CII, the gradation index S, and the color reproduction gamut evaluation index ΔE of the objective function E can be calculated as follows.

ここで、ａＬは明度補正係数、ＷＳ（ｕ）はカラーパッチの印刷に利用されるハーフトーンデータが示す画像のウイナースペクトラム、ＶＴＦ（ｕ）は視覚の空間周波数特性、ｕは空間周波数である。ハーフトーンデータは、カラーパッチのインク量Ｉ_jからハーフトーン処理（本実施例で作成するＬＵＴが搭載されるプリンターが実行するハーフトーン処理と同一のものとする）によって決定される。前記（１２）式は一次元で表現しているが、空間周波数の関数として二次元画像の空間周波数を算出することは容易である。粒状性指数ＧＩの計算方法としては、例えば、本出願人により開示された特表２００７−５１１１６１号公報に記載された方法や、Makoto Fujino， Ｉmage Quality Evaluation of Inkjet Prints， Japan Hardcopy '99， p.291-294に記載された方法を利用することができる。 The graininess index GR can be calculated using various graininess prediction models. For example, the graininess index GR can be calculated by the following equation (12).

Here, aL is a brightness correction coefficient, WS (u) is a winner spectrum of an image indicated by halftone data used for printing a color patch, VTF (u) is a visual spatial frequency characteristic, and u is a spatial frequency. The halftone data is determined from the ink amount I _j of the color patch by halftone processing (the same as the halftone processing executed by the printer in which the LUT created in this embodiment is mounted). Although the equation (12) is expressed in one dimension, it is easy to calculate the spatial frequency of the two-dimensional image as a function of the spatial frequency. As a method for calculating the graininess index GI, for example, the method described in Japanese Patent Application Publication No. 2007-511161 disclosed by the present applicant, Makoto Fujino, Image Quality Evaluation of Inkjet Prints, Japan Hardcopy '99, p. The method described in 291-294 can be used.

ここで、ΔＬ^*は２つの異なる観察条件下（異なる光源下）におけるカラーパッチの明度差、ΔＣ^* _abは彩度差、ΔＨ^* _abは色相差を示す。色非恒常性指数ＣＩＩの計算時には、２つの異なる観察条件下でのＬ^*ａ^*ｂ^*値は、色順応変換（ＣＡＴ）を用いて標準観察条件（例えば標準の光Ｄ６５の観察下）に変換される。ＣＩＩについては、Billmeyer and Saltzman's Principles of Color Technology， 3rd edi_tion， John Wiley & Sons， Ｉnc， 2000， p.129， pp. 213-215を参照。 The color non-constancy index CII is given by the following equation (13), for example.

Here, ΔL ^* is the lightness difference of the color patch under two different observation conditions (under different light sources), ΔC ^* _ab is the chroma difference, and ΔH ^* _ab is the hue difference. When calculating the color non-constant index CII, the L ^* a ^* b ^* values under two different viewing conditions are converted to standard viewing conditions (eg, under the observation of standard light D65) using chromatic adaptation transformation (CAT). Converted. For the CII, Billmeyer and Saltzman's Principles of Color Technology, 3rd edi t ion, John Wiley & Sons, Inc, 2000, p.129, see pp. 213-215.

ここで、Ｌｐは注目する格子点の位置ベクトル、Ｌ _a1〜Ｌ _a6は当該格子点に隣接する６個の格子点の位置ベクトルを示す。ここで、隣接する格子点を結ぶ線（ベクトルＬ _a1〜ベクトルＬ_p〜ベクトルＬ _a2が示す格子点を通る線等）が直線に近く、また格子点が均等に配置されるほどＣＩＥＬＡＢ色空間における格子点の配置が平滑化される傾向にある。すなわち階調性指数Ｓが小さくなればなるほど、平滑程度が高く、良好な階調性が期待できる。 The gradation index S is given by the following equation (14), for example.

Here, Lp is the position vector of the lattice point of interest, and L _{a1 to} L _a6 are the position vectors of six lattice points adjacent to the lattice point. Here, the lines connecting adjacent lattice points (such as the line passing through the lattice points indicated by the vector L _a1 to the vector L _p to the vector L _a2 ) are closer to a straight line, and the lattice points are evenly arranged in the CIELAB color space. The arrangement of grid points tends to be smoothed. In other words, the smaller the gradation index S, the higher the smoothness and the better the gradation.

For the color reproduction gamut evaluation index ΔE, for example, the color reproduction gamut is acquired from the color reproduction gamut data GD of the printer to which the LUT is applied, and L ^* a ^* on the outer surface, the ridgeline, or the vertex of the color reproduction gamut ^. b ^* value is calculated as the color difference ΔE between the L ^* a ^* b ^* values of some of the grid points calculated by the spectral printing model converter 310 and the color calculation unit 320. Note that the color reproduction gamut data GD is stored in advance in a hard disk device or the like. The calculation target of the color difference ΔE is assumed to be at the outer edge of the ink amount space among the grid points, and the color difference ΔE = 0 is set for the inner grid point. This is because the L ^* a ^* b ^* values obtained by converting the grid points existing at the outer edge of the ink amount space by the spectral printing model converter 310 and the color calculation unit 320 are also present at the outer edge in the CIELAB space. As a result, the L ^* a ^* b ^* values obtained by sequentially converting the lattice points existing at the outer edge of the ink amount space by the spectral printing model converter and the color calculation unit 320 can be reproduced by the printer. It is possible to quantify the color shift on the outer surface, the ridgeline, and the vertex.

As described above, when the setting of the LUT creation conditions is accepted from the user, the initial values of the weighting factors w _gr , w _CII , w _S , and w _ga for the image quality evaluation index in the objective function can be set. Thus, since the objective function E is determined, the preparation for the optimization process described below is ready.

(5) Optimization process:
FIG. 15 is a flowchart showing the flow of optimization processing. The process shown in FIG. 8 corresponds to step T130 in FIG. 8, and is executed by the ink amount optimization module 134 every time the target LAB _t is changed according to the dynamic model. When the process is started, in step T131, the LUT creation conditions set in step T90, that is, the objective function E and the initial values w _gr0 , w _CII0 , w _S0 , w _ga0 of the weighting coefficients and the weight correction coefficients a _gr , a _CII , a _S and a _ga are acquired.

Then, one grid point is selected (T132), a counter n for managing the weighting factor is initialized (T133), and the weighting factor of the objective function E is set based on the counter n (T134). That is, the weighting coefficient of the objective function is the initial value w _gr0 , w _CII0 , w _S0 , w _{ga0 at the} initial _stage of the optimization process, as shown in the above-described equation (11), and the weight correction coefficient as the optimization proceeds. It is changed step by step by a _gr , a _CII , a _S and a _ga . In this embodiment, it is assumed that the counter n corresponds to n in the above formula (11), and the counter n is incremented every time the optimization processing of each lattice point is executed once (T136). It is used as a multiplier for the correction coefficient.

  In step T135, the initial ink amount set is optimized for the lattice point selected in step T132. Specifically, the ink amount set is locally moved from the position of the initial ink amount set in the ink amount space, and an ink amount set for minimizing the objective function E at that time is calculated for each lattice point. The ink amount set that minimizes the objective function E is searched for the lattice point selected in (1). At this time, depending on the optimization algorithm, for example, in the ink amount space, the ink amount set that minimizes the objective function at that time and the ink amount set that is minimized are sequentially selected from the adjacent ink amount sets. In the case of using a method of continuing the search for the ink amount set until there is no ink amount set that further lowers the objective function, the direction of optimization in the ink amount space is adjusted by adjusting the weight balance as in this embodiment. Can be controlled to meet predetermined LUT creation conditions.

  When one optimization process is completed for the grid point selected in step T132 in this way (T135), the counter n is incremented as described above (T136), and the number of optimization processes reaches a predetermined number nmax. (T137: Yes), the optimization process for the grid point is terminated (T137: Yes). If not reached, the weighting coefficient is updated to further set the optimum ink amount. Is searched for (T137: No). The number of repetitions nmax is set to 10 times, for example.

  In each optimization process, an ink amount set that minimizes the objective function to which the weighting coefficient set at that time is applied is searched, and in the next optimization process, the objective function is determined by the previous optimization process. Using the minimized ink amount set as a base point, an ink amount set that further minimizes the objective function is searched. In this embodiment, since the objective function gradually changes, the optimal solution for each objective function also gradually changes.

  At this time, as in the example shown in FIG. 13, by changing the objective function so that the weight balance with respect to each image quality element is gradually emphasized, as the optimization process is repeated, the final optimal solution of the objective function is obtained. And can be gradually induced. When the optimization process is repeatedly executed a predetermined number of times in this manner, finally, the objective function E for each grid point becomes extremely small (the overall printing performance is high). Can be optimized. Of course, the optimization of the lattice points may be completed when the value of the objective function E falls below a predetermined threshold value.

  Conversely, as in the example shown in FIG. 14, by changing the objective function so that the weight balance for each image quality factor is gradually relaxed, the solution corresponding to the local minimum in the final objective function is initialized. The optimal solution obtained by the initial optimization process can be guided to the same solution as the local minimum in the final optimization process. If the optimization process is repeatedly executed a predetermined number of times in this way, it is difficult to escape from the local minimum that has fallen into the initial stage even in the optimization process using the final objective function. Therefore, it is possible to optimize the grid points to the ink amount set in which the other image quality elements are optimized in this state while preferentially optimizing the image quality elements regarded as the most important.

In step T138, it is determined whether the optimization process has been completed for all grid points. If the optimization process is performed for all the LAB _t points determined in accordance with the dynamic model in step T120 and the search for the optimal ink amount set is completed, the optimization process ends (T138: Yes), and the process is completed. If not, the process returns to step T132 and the optimization process is performed on the unprocessed grid point (T138: No). As described above, in the present embodiment, the optimization process executed by the ink amount optimization module 134 constitutes an optimization process, and the optimization condition setting module 133 performs the LUT creation condition in steps T131 and T134 and the LUT creation condition setting process. The process of accepting constitutes a weight management process.

When each lattice point is optimized as described above, the color (L ^* a ^* b ^* ) corresponding to the optimized ink amount set of the lattice point is converted into a spectral printing model converter in step T150 of the smoothing process. 310 and the color calculation unit 320, and the average value (ΔLab) of the movement amount of each color point is evaluated.

As described above, each grid point is determined by using the objective function E which is an index of the overall printing performance set by the weighting factors w _gr , w _CII , w _S , and w _{ga as the} degree of importance of each image quality evaluation index. By optimizing, a suitable ink amount set can be found without prescribing complicated separation rules. Furthermore, according to the priority order of the image quality evaluation index set by the user, the weighting factor of each image quality evaluation index in the objective function is changed step by step as the optimization process proceeds, so that the local minimum of the image quality element that you want to respect It makes it possible to control the optimization process such as making it harder to fall or making it easier to fall into the local minimum of the image quality element that you want to respect.
(6) Modification:
The present invention is not limited to the above-described examples and embodiments, and can be implemented in various modes without departing from the gist thereof. For example, the following modifications are possible.

(6-1) Modification 1:
In this specification, “ink” is not limited to liquid ink used for ink jet printers and offset printing, but is used in a broad sense including toner used for laser printers. As other terms having such a broad meaning of “ink”, “coloring material”, “coloring material”, and “coloring agent” can also be used.

(6-2) Modification 2:
In the above embodiment, the method and apparatus for creating a color conversion profile such as a look-up table has been described. However, the present invention provides a printing apparatus manufacturing system that includes a built-in unit that incorporates the color conversion profile thus obtained in the printing apparatus. Is also applicable. A color conversion profile creation apparatus that creates a color conversion profile may be included in the printing apparatus manufacturing system, or may be included in another system or apparatus. The built-in part of the manufacturing system can be realized as a printer driver installer (installation program), for example.

(6-3) Modification 3:
In the above embodiment, the method and apparatus for creating a color conversion profile such as a lookup table has been described. However, the present invention provides a color conversion profile itself obtained in this way, or a storage unit for storing the color conversion profile. It can also be realized by a printing apparatus that performs printing by converting the input print data based on the color conversion profile.

DESCRIPTION OF SYMBOLS 100 ... Base LUT creation module, 120 ... Smoothing processing initial value setting module, 130 ... Smoothing processing module, 132 ... Color point movement module, 133 ... Optimization condition setting module, 134 ... Ink amount optimization module, 136 ... Image quality evaluation index Calculation module 140 ... Table creation module 200 ... Color correction LUT creation module 300 ... Forward model converter 310 ... Spectral printing model converter 320 ... Color calculation unit 400 ... LUT storage unit 410 ... Inverse model initial LUT 510 ... Base 3D-LUT, 520 ... Base 4D-LUT, 610 ... Color correction 3D-LUT, 620 ... Color correction 4D-LUT, 511 ... Inverse conversion LUT, 521 ... Inverse conversion LUT

Claims (6)

A method for creating a color conversion table for converting an input color coordinate system coordinate value into an ink color set ink amount set composed of a plurality of types of ink,
Optimization is performed a plurality of times using a predetermined objective function expressed by a combination of a plurality of image quality evaluation indexes each weighted with respect to the ink amount of the ink color system corresponding to the coordinate value of the input color system. An optimization process determined by
A weight management step of changing weights for the plurality of image quality evaluation indexes at each time of the optimization;
A color conversion table creating step for creating a color conversion table for converting the coordinate value of the input color system into the ink amount of the ink color system based on the ink amount determined by the optimization step;
A method for creating a color conversion table, comprising:   2. The method of creating a color conversion table according to claim 1, wherein, in the weight management step, the weight is gradually changed so that the image quality evaluation index having higher importance increases as the number of optimizations in the optimization step proceeds.   In the weight management step, the weight is set so as to increase as the image quality evaluation index having higher importance in the initial stage of the optimization step, and as the image quality evaluation index having lower importance at the end of the optimization step, 3. The method of creating a color conversion table according to claim 1, wherein the weight is gradually changed so as to be relatively larger than the weight in the initial stage of the optimization step.   In the weight management step, the weight is averagely set with a plurality of the image quality evaluation indexes at the initial stage of the optimization step, and the weight is higher as the image quality evaluation index is more important at the end of the optimization step. 3. The method of creating a color conversion table according to claim 1, wherein the color conversion table is gradually changed so as to be relatively large with respect to the weight in the initial stage of the optimization process. A color conversion table creation program for converting an input color coordinate system coordinate value into an ink color set ink amount set composed of a plurality of types of ink,
Optimization is performed a plurality of times using a predetermined objective function expressed by a combination of a plurality of image quality evaluation indexes each weighted with respect to the ink amount of the ink color system corresponding to the coordinate value of the input color system. Optimization function determined by
A weight management function for changing the weights for the plurality of image quality evaluation indexes each time the optimization is performed;
A color conversion table creating function for creating a color conversion table for converting the coordinate value of the input color system into the ink amount of the ink color system based on the ink amount determined by the optimization function;
A color conversion table creation program characterized by comprising:   A storage unit that stores a color conversion table created by the color conversion table creation method according to claim 1, and based on the color conversion table stored in the storage unit. A printing apparatus that converts the coordinate value of the input color system in the print data into an ink amount set of the ink color system, and performs printing based on the ink amount set.

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