JP2001358956A - Image processing condition setting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing condition setting method that can automatically set an image processing condition with respect to a specific color depending on a characteristic of received color image data. SOLUTION: Finish information and a weighting coefficient are selected (S51, S52), gradation transformation is applied to received color image data with setup parameters before and after the correction respectively to obtain network percentage data (S53, S56), a change in each of the network percentage data according to the finish information with respect to ideal network percentage data is evaluated by using the weighting coefficient (S57) and the setup parameter is automatically adjusted according to the result the evaluation (S58).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing condition setting method for processing a specific color of input color image data and obtaining desired output color image data.

[0002]

2. Description of the Related Art In the field of printing and plate making, for example, image reading and recording is performed by electrically processing image information recorded on a read original for the purpose of streamlining work processes, improving image quality, etc. Reproduction systems are widely used.

In this case, an image processing apparatus constituting the image reading / recording / reproducing system sets image processing conditions in order to perform desired image processing on image data obtained by scanning a read original. I have. That is, the image processing apparatus scans a magnification, a trimming range, the number of output lines, a screen angle, and the like based on prescanned image data obtained by roughly scanning a read original in order to create a film original according to the purpose. Finishing information such as highlighting, shadow point density setting, gradation setting by tone curve adjustment, gray color adjustment, hue adjustment of specific colors such as skin color, sky blue, green, etc., and brightness adjustment After designating the information, the scanned original is scanned in detail to obtain the main scan image data (see Japanese Patent Application Laid-Open Nos. 4-111575 and 6-291998).

[0004]

In the image processing apparatus, for example, when a specific color is adjusted, an operator specifies a specific pixel to be adjusted on a pre-scanned image, and the color of the pixel is set to a desired value. The image processing conditions are set so that the color becomes the color. Therefore, the color of the image obtained by the main scan greatly depends on the skill of the operator.

The characteristics of an input image to be subjected to image processing vary depending on, for example, the printing company that provides the image. To set image processing conditions in consideration of the characteristics, considerable skill is required. I need.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned inconvenience, and it is possible to automatically set image processing conditions for a specific color. It is an object of the present invention to provide an image processing condition setting method capable of setting processing conditions and obtaining a desired image in accordance with the image processing conditions.

[0007]

SUMMARY OF THE INVENTION In order to achieve the above object, the present invention provides a method of weighting specific color image data constituting a specific color space and processing input color image data by a predetermined image processing. The difference between the processed data obtained by processing under the conditions and the ideal image data of a specific color is obtained, and the difference is weighted and added to all input color image data to obtain an evaluation value. Optimum image processing conditions are set based on the evaluation values according to the above.

By setting the image processing conditions in this way, the optimum image processing conditions are automatically set without going through the process of the operator specifying a specific portion to be a specific color of the input color image data. be able to. If the weighting coefficient is set according to the characteristics of the input color image data and can be selected as appropriate, it is possible to automatically set more optimal image processing conditions according to the characteristics.

[0009]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A preferred embodiment of an image processing condition setting method according to the present invention will be described below in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a configuration of an image reading / recording / reproducing system to which an image processing condition setting method according to the present invention is applied. This image reading / recording / reproducing system includes a reflection type scanner 1 for reading image information recorded on a reflection type original.
0, a transmission scanner 12 for reading image information recorded on the transmission original, controlling the reflection scanner 10 and performing desired image processing on input color image data, and operating the transmission scanner 12 And a console 14 for displaying the image, and an output device 16 for outputting output color image data obtained by performing desired processing as a film original.

Here, the reflection type scanner 10 is shown in FIG.
It is configured as shown in FIG. That is, the reflection type scanner 1
Reference numeral 0 denotes an original mounting table 20 made of light-transmitting glass provided on an upper portion of the casing 18, and a reflective original S pressed by an original pressing plate 22 is mounted on the original mounting table 20. It should be noted that a shading reference plate 25 for performing shading correction of the reading optical system is provided on the document table 20 in parallel. A light source unit 2 illuminating the reflective original S and receiving the reflected light is provided in the casing 18.
4 and a moving mirror unit 26 for changing the optical path of the reflected light
An ND filter 28 for adjusting the highlight density or the shadow density of the reflected light; the imaging lens 30;
2 are provided. The light source unit 24 includes two lamps 34a and 34b that are long in the main scanning direction orthogonal to the paper surface of FIG.
And a reflection mirror 36. The moving mirror unit 26 includes two reflecting mirrors 38a and 38b. The light receiving unit 3
2, three prisms 40a to 40c and each prism 4
And CCDs 42a to 42c fixed to Oa to 40c. In this case, the prisms 40a to 40c split the reflected light from the reflective original S into three primary colors of R, G, and B,
It leads to each CCD42a-42c. The light source unit 24 and the movable mirror unit 26 are configured to be movable in a sub-scanning direction indicated by an arrow by a transport motor 44, and the light source unit 2
4 is configured to move at twice the speed of the moving mirror unit 26. The reflection type scanner 10 further includes a control circuit 46.
The control circuit 46 controls the overall operation, and controls the transmission of the input color image data obtained from the CCDs 42a to 42c to the transmission scanner 12.

The transmission scanner 12 includes a CPU 48 for performing overall control, an image reading section 49 for reading image information of a transmission original (not shown), an image reading section 49 for the reflection scanner 10 and the transmission scanner 12, An input / output control circuit 50 for transmitting / receiving data, a preprocessing circuit 52 for performing preprocessing before performing image processing on input color image data,
Image processing condition correction circuit 56 for correcting image processing conditions
And an image processing circuit 58 for performing desired image processing based on the image processing conditions. The preprocessing circuit 52 includes an image buffer 54 for temporarily storing input color image data.
And an ENDLUT storing an END lookup table for converting input color image data into colorimetric END (Equivalent Neutral Density) data that does not depend on the characteristics of the reflective scanner 10, the transmissive scanner 12, or the output device 16. The storage unit 62 is connected. Also,
The image processing condition correction circuit 56 is connected to a parameter storage unit 60 for storing setup parameters as image processing conditions as finish information, and a gradation LUT storage unit 64 for storing a reference gradation curve as a lookup table. Is done. These are connected to each other via a bus 66.

As shown in FIG. 3, the image processing condition correction circuit 56 stores specific color ideal image data which stores specific colors such as flesh color, sky blue, and green as a set of ideal halftone% data (ideal image data). A storage unit 57 and a weighting coefficient storage unit 5 for storing a weighting coefficient for a specific color space including the ideal halftone% data and data in the vicinity thereof for each data;
9 and device-independent halftone% data (processed data) obtained by converting colorimetric END data using a gradation curve adjusted by a predetermined setup parameter as image processing conditions, as ideal halftone% data and identification. It is basically composed of an evaluation value calculation unit 61 that evaluates with an evaluation function using a color space weighting coefficient and calculates the evaluation value, and a setup parameter setting unit 63 that sets a setup parameter based on the evaluation value. You.

A weighting coefficient setting unit 65 is connected to the image processing condition correction circuit 56 when setting a weighting coefficient based on an operation by a skilled operator.

On the other hand, the console 14 is connected to the bus 66. The console 14 includes a video buffer 68 and a control unit 70. The control unit 70 controls output to a CRT display 72 connected to the console 14, and controls a keyboard 74 and a mouse 7.
6. Process the input data from 6. The output device 16 is connected to the image processing circuit 58,
A function of recording an image on a film based on output image data from the camera.

The image reading / recording / reproducing system according to the present embodiment is basically configured as described above. Next, the operation and effect of the system will be described.

First, the overall operation of the system will be described with reference to the flowchart shown in FIG.

When the reflection type scanner 10 is used, the reflection type document S is set on the document table 20, and the flatness of the image reading surface is maintained by the document pressing plate 22. Then
In accordance with an instruction from the keyboard 74 of the console 14, the reflection scanner 10 performs an image reading operation via the transmission scanner 12. Then, the transport motor 44 is driven, and the light source unit 24 and the moving mirror unit 26 start moving. In this case, the light source unit 24 first irradiates the shading reference plate 25 with illumination light from the lamps 34a and 34b, and the reflected light is reflected by the reflection mirrors 36, 38a and 38.
b, ND filter 28, imaging lens 30, prism 40
The light is guided to each of the CCDs 42a to 42c through a to 40c. Each of the CCDs 42a to 42c photoelectrically converts the reflected light into R, G, and B signals, and converts these signals into a control circuit 46.
To perform shading correction. That is, the control circuit 46 controls the imaging lens 30 and the CCD 4 based on the RGB signals obtained by reading the shading reference plate 25.
The shading caused by the characteristics 2a to 42c is corrected.

Next, the light source section 24 irradiates the reflective original S with illumination light from the lamps 34a and 34b via the original placing table 20, and reads image information as reflected light. The image information is converted into RGB signals by being photoelectrically converted by the CCDs 42a to 42c and guided to the control circuit 46 (step S1). The control circuit 46 transfers the RGB signals to the transmission type scanner 12.

In the transmission type scanner 12, after receiving the RGB signals through the input / output control circuit 50, the CPU 4
In the pre-processing circuit 52, processing such as logarithmic conversion is performed under the action of Step 8 to generate RGB density data (Step S).
2). The RGB density data is temporarily stored in the image buffer 5.
4 is stored. Next, in the pre-processing circuit 52, based on the END lookup table stored in the ENDLUT storage unit 62 corresponding to the amount of the dye of the reflection type original S, the R
The END conversion process is performed on the GB density data to generate C, M, and Y colorimetric END data that does not depend on the device (step S3).

Next, the image processing circuit 58 performs a picture adjustment process for adjusting the highlight density and the shadow density of the colorimetric END data to a preset reference value (step S4). Condition correction circuit 5
The gradation processing (step S5), color correction processing (step S6), U
The halftone data is subjected to processing such as CR (Under Color Removal) and sharpness enhancement (step S7), and is then output to the output device 16.

When reading the image information of the transmission type original by the transmission type scanner 12, the RGB signals read by the image reading section 49 are transferred to the preprocessing circuit 52 via the input / output control circuit 50, and are transmitted to the reflection type original. The processing is performed in the same manner as in the case of S.

The output device 16 performs a shading process on the dot% data in accordance with the output mode to generate dot data (step S8). The halftone data controls, for example, on / off of a laser beam, whereby a desired image is recorded on the film (step S9).

The image reading / recording / reproducing system operates as described above to produce a film original. Next, a case in which setup parameters are set in the system will be described.

That is, in this system, as shown in the flowchart of FIG. 5, after setting the reflection type document S (or transmission type document) on the reflection type scanner 10 (or transmission type scanner 12) (step S20), Prescan is performed to roughly read the image information recorded on the reflection original S (or the transmission original) (step S2).
1). In the transmission type scanner 12, a part of the setup parameters is automatically set based on the pre-scan image data (input color image data) obtained by the pre-scan (step S22). Based on the setup parameters, processes such as picture adjustment (step S4), gradation (step S5), color correction (step S6), UCR, and sharpness (step S7) are performed.

In the transmission type scanner 12, a part of the setup parameters can be automatically set by applying a fuzzy inference rule. That is, the prescan image data obtained by the prescan is stored in the image buffer 54 and the C
It is displayed on the RT display 72, and the characteristic value is calculated. The characteristic values include a density (level) at an arbitrary% of the cumulative histogram, a screen division (for example, 1 /
(4, 1/8), the density of the cumulative histogram for each area, the density average value, the maximum peak density, the cumulative histogram for each of Y, M, and C, and the like. Document classification information, which is a part of the image processing conditions, is obtained by a rule describing the relationship between these characteristic values and document characteristics. For example, document classification information can be obtained according to the following rules.

(A) Very low average IF concentration T
(B) IF density average is low. (C) IF density average is slightly low. (2) IFEN average is slightly low. (D) IF density average is medium. THEN exposure is normal (e). The average IF concentration is slightly higher. The THEN exposure is slightly under. (F) The IF average value is high. The THEN exposure is under. (G) The IF average value is very high. The THEN exposure is considerably under. The regions are classified into seven, and each region is distinguished by (a) to (g). Arbitrary pre-scan image data applies to any of the above seven rules,
The exposure state from under to over is determined. Other document classification information includes high key / low key, presence / absence of highlight point, picture pattern, presence / absence of skin color, color cast, and the like, and the same rules of fuzzy inference as described above can be applied. Next, setup parameters are set from the document classification information according to the following rules.

(A ') IF exposure is considerably over T
HEN highlight point density is 0.05 (b ') IF overexposure THEN highlight point density is 0.10 (c') IF exposure is slightly over THEN highlight point density is 0.15 (d ') IF exposure The normal highlight point density is 0.20 (e ') IF exposure is slightly under. THEN highlight point density is 0.30 (f') IF exposure is under. THEN highlight point density is 0.40 (g ') When the IF exposure is considerably under the THEN, the highlight point density is 0.50 or more, so that the setup parameters of the highlight point can be automatically set. In addition, setup parameters can be set for the finish information based on instructions from the operator as described later.

After the respective setup parameters are set as described above, the reflection type scanner 10 (or transmission type scanner 12) refines the image information recorded on the reflection type original S (or transmission type original). Is performed (step S23). The main scan image data obtained by the main scan is subjected to desired image processing by the image processing circuit 58 based on the image processing conditions set in step S22, and then transferred to the output device 16, where the image is reproduced and output. (Step S24).

Next, a method of automatically setting the setup parameters (image processing conditions) relating to the finish information in step S22 of FIG. 5 will be described.

Here, when setting the setup parameters, the CRT display 72 of the console 14
The screen shown in FIG. 6 is displayed. That is, on this screen, an image obtained by the pre-scan in step S21 is displayed, and the finish information selected by the operator is displayed. The finish information is classified into, for example, a brightness instruction and a finish instruction. In the brightness instruction, brightness information such as “bright”, “slightly bright”, “dark”, “slightly dark”, and “same as original” is used. Can be selected using the mouse 76. In the finishing instruction, “beautiful skin”, “align with gray”, “beautiful sky”, and “beautiful green” can be selected.

Therefore, the case of selecting "beautiful skin" as the finish instruction will be described with reference to the flowchart of FIG.

First, the setup parameter setting section 63
Applies the fuzzy inference rule described above, sets an initial setup parameter that is a correction amount for the standard gradation curve stored in the gradation LUT storage unit 64, and stores it in the parameter storage unit 60 (step S50). . Next, the operator sets the mouse 76
Is used, "Beautiful skin" is selected as finish information on the screen shown in FIG. 6 (step S51). Further, the operator selects, from the weighting coefficient storage unit 59, a weighting coefficient corresponding to the characteristics of the color image data to be subjected to image processing, for example, the characteristics of the printing company that supplies the color image data (step S52).

Here, the weighting coefficient is obtained by specifying an image portion corresponding to "beautiful skin" many times by a skilled operator for a large number of color images of a specific type, The probability that the image data will appear in the specific color space of "beautiful skin" which is the finish information is
By calculating in the weighting coefficient setting unit 65,
It can be set in advance.

That is, the initial weighting coefficient W for each specific color image data constituting the specific color space that defines “beautiful skin” is 1 in the specific color space of “beautiful skin” and 0 in other portions. It is set so that it becomes. The number of the specific color image data is N, and the specific color image data corresponding to the specific portion specified by the skilled operator is (c ₀ , m ₀ ,
y ₀ ) and the other specific color image data as (c, m, y)
And the modified weighting coefficient W (c ₀ , m ₀ , y ₀ ) corresponding to the specific color image data (c ₀ , m ₀ , y ₀ ) is changed to the weighting coefficient W ′ (c ₀ , m ₀ , y ₀ ), W (c ₀ , m ₀ , y ₀ ) = (N · W ′ (c ₀ , m ₀ , y ₀ ) +1) / (N + 1) (1) Also, specific color image data (c, m, y)
The modified weighting coefficient W (c, m, y) corresponding to
From the weighting coefficient W '(c, m, y) before correction, W (c, m, y) = N.W' (c, m, y) / (N + 1) (2)

By repeating such processing a number of times for a large number of documents by a skilled operator, a weighting coefficient W for a specific portion determined to be optimal is obtained.
(C ₀ , m ₀ , y ₀ ) is the weighting coefficient W of the other part
It will be set larger than (c, m, y). These weighting factors W (c ₀ , m ₀ , y ₀ ) and W (c,
m, y) is a unique weighting coefficient W for a specific document.
Is stored in the weighting coefficient storage unit 59. The weighting coefficient W is set according to the type of the document.

Therefore, in step S52, after selecting the weighting coefficient W set as described above, the dot% of the Y, M, C dye amount data of the input color image data is selected.
The data is calculated using the gradation curve corrected by the initial setup parameters set in step S50 (step S53).

Next, the ideal halftone% data corresponding to the "beautiful skin" specified by the operator is read from the specific color ideal image data storage unit 57, and the evaluation value calculation unit 61 calculates each halftone net calculated in step S53. The target network% data closest to the% data is calculated (step S5).
4). In this case, the ideal halftone% data corresponding to “beautiful skin” is defined as data on a plane α surrounded by points a ₁ , a ₂ , and a ₃ in FIG. That is, the dot% data of the pixel i of the pre-scan image is converted to yi,
In the case where mi and ci are used, the ideal net% data that minimizes the index ri defined by the following equation (3) is the target net% data y0i, m0i, c0i (= d0i) for each net% data.
Asking.

Ri ² = (yi−y0i) ² + (mi−m0i) ² + (ci−c0i) ² (3) After performing the above operation on all the pixels of the prescan image data, Y, The initial setup parameters of the middle separation (MS) of the gradation curves of each of the hues M and C are increased or decreased by a fixed amount, and the modified setup parameters are stored in the parameter storage unit 60 (step S55).

Next, based on the gradation curve obtained by using the modified setup parameters, each halftone data yi ', mi', ci 'of the prescanned image data is calculated again as in the case of step S53. (Step S56).

Subsequently, halftone% data is evaluated by correcting the setup parameters (step S57). That is, fy is an evaluation function indicating how far the halftone% data of Y before the setup parameter of the middle separation (MS) is changed from the target halftone data as a whole, and the setup parameter of the middle separation (MS) is Assuming that the modified evaluation function is fy ′,
Each evaluation function is defined by the following equations (4) and (5) using the weighting coefficient Wi of the pixel i.

Fy = ΣWi · √ ((yi−y0i) ² ) (4) fy ′ = ΣWi · √ ((yi′−y0i) ² ) (5) where Σ is prescanned image data. Represents the sum of all input color image data.

Then, based on the evaluation values which are the values of the evaluation functions fy and fy 'defined by the equations (4) and (5),
For example, if fy> fy ′, the halftone% data of Y of the specific color is approaching the target halftone% data as a whole, so that the setup parameter middle separation (MS)
Is determined to be valid (increase or decrease). If fy <fy ′, since the halftone% data of Y of the specific color is totally apart from the target halftone% data, it is determined that the correction direction of the middle separation (MS) of the setup parameter is inappropriate. judge.

With respect to the M hue and the C hue, the correction direction of the setup parameter is determined by using the same evaluation functions as the evaluation functions fy and fy '.

If the correction direction is valid, the setup parameter is corrected by a predetermined amount in that direction. If the correction direction is inappropriate, the setup parameter is corrected by a predetermined amount in the opposite direction. The operation of correcting is repeated, and when the evaluation value is determined to be valid for each of the hues of Y, M, and C, the setup parameters relating to the middle separation (MS) are stored in the parameter storage unit 60.
Is finally set (step S58).

Similarly, setup parameters for highlight separation (HS) and shadow separation (SS) in the gradation curve are set. Thus, the setting of the setup parameters for correcting the gradation curve is completed.

Next, fine adjustment is performed for each of the hues of Y, M, and C. In this case, for example, when the finish instruction is “beautiful skin”, since the flesh color is mainly composed of the hue of Y and the hue of R, the hue of R within the predetermined range in the prescanned image data Only the prescanned image data determined to be extracted is extracted, and the dye amount data of each of the hues of Y, M, and C is corrected for the prescanned image data (step S59), and the same processing as steps S56 and S57 is performed. (Steps S60 and S61) to correct the setup parameters for each dye amount. Similarly, setup parameters are set for the pre-scan image data determined to be the hue of Y (step S).
62).

In addition, as the finish information,
Is selected, the color correction
Similar operations except for the correction work (steps S59 to S61)
Operation to set up the setup parameters.
Can be. In this case, the finish "justify to gray"
The ideal halftone% data corresponding to the offset information is represented by a point b in FIG. ₁
And b_TwoIs defined as data on the curve β between.

When "beautiful sky" is selected as finish information, setup parameters can be set in the same manner as "beautiful skin". in this case,
Ideal net% corresponding to the finish information "Beautiful sky"
Data line segment gamma ₁ on the data between c ₁ and c ₂ points 10, are defined as the data on the surface gamma ₂ surrounded by points c _2, c _3, c _4.

Further, “beautiful green” is used as finish information.
Is selected, the target network in step S54 of FIG.
The calculation processing of% data is performed as follows. Sand
The ideal halftone% data corresponding to “beautiful green” is shown in FIG.
Point 1 of d₁, D_Two, D_Three, D_Four, D _Five, D₆The solid δ surrounded by
Is defined as data within So, pre-scan image
Each of the solid δ surfaces closest to each dot% data of the image data
The ideal net% data is obtained according to equation (3),
Mark net% data. Next, the input color image data
Data is inside or outside the solid δ.
To determine If inside, its net% data
Is set as the true target net% data, and
No processing is performed. In addition, when it is outside, the temporary
Set the target net% data to the true target net% data and
The gradation curve is obtained by performing the processing from step S55.
Make corrections.

It should be noted that the operator can obtain finishing information such as "beautiful skin", "align with gray", "beautiful sky",
When all of “beautiful green” is indicated, the evaluation function shown in the equation (4) is defined as a new evaluation function F as follows: F = {kj} Wij · ((yij−y0ij) ² ) (6) You. In this case, j represents j = 1 (“beautiful skin”), 2 (“gray”), 3 (“beautiful sky”), and 4 (“beautiful green”), and the first Σ is , J, and the second Σ represents the sum for all pixels i. Kj is a weighting coefficient between pieces of finish information. The evaluation function F 'after the setup parameters are modified is defined in the same manner. Therefore, by determining the evaluation values of these evaluation functions F and F ', it is possible to automatically set up the setup parameters that can satisfy all of the finish information.

After setting the setup parameters using the prescanned image data as described above, the main scan of the reflection type original S is performed (step S23), and the obtained main scan image data is set to the setup parameters. By performing gradation and color correction based on the image data, highly accurate image data suitable for finish information can be automatically obtained.

[0053]

As described above, according to the present invention, optimal image processing conditions are automatically set for input color image data of a desired specific color, and a good image having a desired finished state is obtained. be able to.

Prior to setting the image processing conditions,
By selecting a weighting coefficient corresponding to the characteristics of the document, appropriate image processing conditions according to the characteristics of the document can be automatically set. As a result, it becomes possible to perform image processing equivalent to that of a skilled operator on input color image data.

[Brief description of the drawings]

FIG. 1 is a configuration block diagram of an image reading / recording / reproducing system to which an image processing condition setting method according to the present invention is applied.

FIG. 2 is a schematic configuration diagram of the reflection type scanner shown in FIG.

FIG. 3 is a block diagram illustrating a configuration of an image processing condition correction circuit illustrated in FIG. 1;

FIG. 4 is a flowchart of an overall operation of image processing in the system shown in FIG. 1;

FIG. 5 is a schematic flowchart of image processing in the system shown in FIG. 1;

FIG. 6 is an explanatory diagram of a display screen on a console in the system shown in FIG. 1;

FIG. 7 is a detailed flowchart of setting image processing conditions in the flowchart shown in FIG. 5;

FIG. 8 is an explanatory diagram of ideal halftone% data for finish information “beautiful skin”.

FIG. 9 is an explanatory diagram of ideal halftone% data for the finish information “align to gray”.

FIG. 10: Ideal net% for finished information “beautiful sky”
FIG. 4 is an explanatory diagram of data.

FIG. 11: Ideal net% for finished information “beautiful green”
FIG. 4 is an explanatory diagram of data.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 10 ... Reflection type scanner 12 ... Transmission type scanner 14 ... Console 16 ... Output device 32 ... Light receiving part 48 ... CPU 52 ... Preprocessing circuit 56 ... Image processing condition correction circuit 57 ... Specific color ideal image data storage part 58 ... Image processing circuit 59: weighting coefficient storage unit 60: parameter storage unit 61: evaluation value calculation unit 62: ENDLU
T storage unit 63: setup parameter setting unit 64: gradation LUT storage unit 65: weighting coefficient setting unit 72: CRT display S: reflection type original

 ──────────────────────────────────────────────────続 き Continuing on the front page F term (reference) 2H030 AD11 AD16 5B057 AA11 BA02 CA01 CA08 CA12 CA16 CB01 CB08 CB12 CB16 CC01 CE17 CH01 CH07 5C077 MM20 MP08 NN04 PP33 PP37 PP46 PP47 PQ08 PQ12 PQ14 PQ18 PQ19 SS0520 P23 HB02 LA02 LB11 MA11 NA18

Claims (4)

[Claims] 1. A method for processing a specific color of input color image data,
In the image processing condition setting method for obtaining desired output color image data, the method comprises a plurality of specific color image data in which weighting coefficients are set so as to increase near the ideal image data of the specific color and to decrease as the distance increases. A specific color space is created, and an evaluation value is obtained by weighting a difference between processed data obtained by processing the input color image data under predetermined image processing conditions and the ideal image data using the weighting coefficient. And correcting the image processing condition based on the evaluation value. 2. The method according to claim 1, wherein said weighting coefficient is set according to characteristics of said input color image data. 3. The method according to claim 1, wherein the processing data is di, the ideal image data closest to the processing data di is d0i, and the weighting coefficient is Wi (i is the total of the input color image data. Correcting the image processing condition based on an evaluation value f defined as f = ΣWi · √ ((di−d0i) ² ) (Σ represents the sum of i). An image processing condition setting method that is a feature. 4. The method according to claim 1, wherein the weighting coefficient Wi (i targets all of the input color image data) is a weighting coefficient before correction of the specified input color image data. Wi ',
Using the image data number N of the specific color image data constituting the specific color space, Wi = (N · Wi ′ + 1) / (N + 1) and correcting the input color image data other than the specified input color image data. An image processing condition setting method, wherein the weighting coefficient Wi for the input color image data is set by repeating a process of correcting it as Wi = N · Wi ′ / (N + 1).