JPH1127548A - Color image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To realize efficient color reproduction with high fidelity by defining in advance a representative point of a color value on a gamut boundary in the case that part of color image information lies outside of the gamut (color reproduction area) and determining a compression destination through the use of the representative point. SOLUTION: First, a color value is entered with respect to each pixel. Color space conversion processing that converts the entered color value into a color coordinate on an isochromatic space is conducted. Furthermore, whether the color information is within the gamut or at its outside is discriminated. When the information is decided as being inside the gamut, no special processing is conducted. However when the information lies outside of the gamut, the information is defined by a set of color values (representative points) on a gamut boundary surface, and a range of the representative points as the retrieval object is limited in the boundary surface. The color value of the gamut compression destination is calculated by using the representative points and converted into a coordinate in a color space of an output destination, and image outputting is executed.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a color image processing method for transferring color image information between devices having different color reproduction ranges, such as a CRT, a color printer, and a color copy. The present invention relates to a color image processing method that realizes efficient and faithful color reproduction by narrowing a search range of a color image.

[0002]

2. Description of the Related Art In recent years, media handling color images have been developed in various forms. For example, there is well known a system in which a character or an image is read by a color scanner, edited and processed on a display of a computer, and the result is printed out by a color printer or the like.
However, in this case, the color reproduced on the display and the color printed out are determined by a color reproduction method or a mixed color system (RG
(B, YMC), and the fact that colors differ from each other due to the mismatch of color reproduction ranges.

As described above, since the gamut of colors that can be represented by a device is usually different, colors that cannot be output by a color image output device among input colors are converted into reproducible colors. It is desired to perform a so-called color gamut compression process and reproduce an input image on an output device as close as possible to a document.

In such a color image reproduction processing method, for example, as disclosed in Japanese Patent Application Laid-Open No. Sho 61-288690, gamut compression has mainly focused on gamut compression to the same hue. One of the most important factors in color reproduction among hue, lightness, and saturation is hue, and by specifying a constant hue, the compression destination can be specified in a two-dimensional space of lightness and saturation. The processing for determining the compression destination in the three-dimensional space of hue, lightness, and saturation can be easily realized.

[0005]

However, in the conventional color image reproduction processing method as described above, depending on the relationship with the gamut boundary surface as shown in FIG. 5, the gamut compression processing of the same hue is performed. In this case, the color difference may become extremely large (in this example, the saturation is significantly impaired), and it is not always desirable to perform compression with a constant hue. Therefore, in this case, it is necessary to determine the reproduction destination without restricting the hue, and the compression destination must be determined in the three-dimensional space of hue, lightness, and saturation.
There has been a problem that color reproduction processing is complicated and inefficient.

The present invention has been made in view of the above, and realizes an easy and efficient high-precision color reproduction process when an input image is faithfully reproduced on a document image on an output device. The purpose is to:

[0007]

According to a first aspect of the present invention, there is provided a color image processing method comprising:
A color image for converting the non-reproducible color into a reproducible color of the color image output system when at least a part of the color image information is a non-reproducible color that cannot be reproduced in a color image output system gamut (color gamut); A first step of defining a boundary surface of the gamut by a set of color values (representative points) on the gamut boundary surface and specifying a range of representative points to be searched in the boundary surface in the processing method; A second step of determining a compression destination using the color value of the representative point and the hue difference, lightness difference, or saturation difference between the color values to be compressed, or a combination thereof; Is included.

That is, when the color is outside the gamut, a representative point of the color value on the gamut boundary is defined in advance, and the compression destination is specified using the representative point, thereby
Efficient and faithful color reproduction is realized.

According to a second aspect of the present invention, in the color image processing method, the first step divides the gamut boundary surface equally by hue, and determines the length of the side of the gamut boundary surface in each hue. A representative point is defined by equally dividing.

That is, when the gamut boundary surface is compressed using the color values of the representative points, the representative points can be determined so that the length between the representative points is approximately equal for each divided gamut boundary plane. In contrast to the process of performing compression on a constant brightness surface, which is performed, gamut compression can be performed so that the estimation accuracy of the compression destination during compression is uniform for all color values, enabling stable color reproduction. Become.

According to a third aspect of the present invention, in the color image processing method, the second step is to determine a compression destination in accordance with how to prioritize hue, lightness, and saturation.

That is, by determining the compression destination in accordance with the emphasis of hue, lightness, and saturation, faithful color reproduction can be performed based on the specification of the lightness and saturation specified by the user. .

According to the color image processing method of the present invention, the search range in the gamut boundary surface is determined according to the emphasis of hue, lightness, and saturation.

That is, by determining the search range in the gamut boundary surface in accordance with the emphasis of hue, lightness, and saturation, color reproduction faithful to the user's request and efficient and highly accurate is achieved. Is realized.

[0015]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a color image processing method according to the present invention will be described in detail with reference to the accompanying drawings.

[First Embodiment] FIG. 1 is a flowchart showing a color reproduction processing procedure according to the first embodiment. In the figure, to determine a compression destination, first, a color value is input for each pixel (S101). Thereafter, a color space conversion process for changing the input color values to color coordinate values on a uniform color space is executed (S102). Further, it is determined whether it is inside or outside the gamut (color reproduction area) (S103). here,
No special processing is performed when it is determined to be inside the gamut, and when it is determined to be outside the gamut, the color value of the representative point on the gamut boundary is used to represent the search target in the boundary surface. The range of the point is limited (S104). And
The color value of the gamut compression destination is calculated using the representative point (S
105), the coordinates are converted into the coordinates of the color space of the output destination (S10).
6) The image is output (S107).

As the above-mentioned color matching space, for example, an L ^* a ^* b ^* color space (CELAB space) generally known,
Alternatively, an HVC color space or the like is used. The representative points are
It represents a set of color values on the gamut boundary surface as shown in FIG. The process of defining a representative point on the gamut boundary in advance and specifying the compression destination using the representative point is a characteristic process of this embodiment.

[Embodiment 2] Here, when the gamut boundary surface is defined by the representative points, the gamut boundary surface is first equally divided by the hue, and the length of the side of the gamut boundary surface is equally divided by each hue. An example of defining a representative point will be described.

The color value of the representative point on the gamut boundary is calculated in advance. Note that this representative point may be an arbitrary number or color value. FIG. 2 shows an example in which the gamut boundary surface is defined by the representative points.

The representative points are divided so that the distances are approximately equal to each other, and the representative points are determined to define the gamut boundary surface. Here, the distance may be a Euclidean distance between color values in a color uniform space, a specially defined color difference, or a visual distance.

First, the gamut boundary surface is divided for each hue, and the sides on the gamut surface are equally divided so that the distance between the representative points is substantially equal. Then, the hue is equally divided, and the following calculation is performed for each hue. That is, the length L of the side when the white / black point and the gamut vertex (maximum saturation point) are connected by a straight line is divided by a predetermined length ΔLen, the divisor is set to n, and L is divided into n equal parts. To determine the representative point.

FIG. 3 shows an example of setting representative points by the above processing method.
FIG. 3A shows the case where the brightness is determined to be constant, and FIG. 3B shows that the representative points are evenly distributed in the highlighted portion when the two are compared.

That is, when the gamut boundary surface is compressed using the color values of the representative points, the representative points can be determined so that the length between the representative points is approximately equal for each divided gamut boundary plane. In contrast to the process of performing compression on a constant lightness plane as is performed (FIG. 3B), gamut compression can be performed so that the estimation accuracy of the compression destination at the time of compression becomes uniform for any color value. Stable color reproduction becomes possible. For example, when the gamut boundary surface is equally divided by brightness, when the brightness of the maximum chroma point is large, such as yellow, the number of search grid points with a higher brightness is reduced. Estimation in that part Accuracy decreases.

[Embodiment 3] In the method of defining a gamut boundary surface and specifying a search range in the boundary surface and compressing the boundary, the hue, lightness,
An example will be described in which a compression destination is determined according to how to put importance on saturation.

One method of obtaining a search range is to calculate a color difference from a color value to be gamut-compressed, and select some of the representative points having a small value for the color difference. Alternatively, a method of calculating a hue difference, a lightness difference, or a saturation difference from a color value to be gamut-compressed and selecting a representative point having a color value within a certain value range is also conceivable. Alternatively, a method of selecting based on a combination of the two can be considered.

According to the third embodiment, in the method of designating the compression destination, the hue difference, the lightness difference,
A case will be described in which a configuration having a means for designating how to put importance on the saturation difference is used.

Hue difference ΔH, lightness difference Δ
For each of L and the saturation difference ΔC, the largest case is 1
And the smallest case is set to 0. In this example, the emphasis is set to WH, WL, and WC, respectively. For example, for the compression destination, the value of the following evaluation formula is calculated for each representative point, and the color value of the representative point having the smallest value of the evaluation formula among WH × ΔH + WL × ΔL + WC + ΔC is set as the compression destination.

[Embodiment 4] In this embodiment 4,
Using the result of specifying the emphasis on hue, lightness, and saturation,
An example in which the search range of the compression destination is limited and the compression destination is determined in the search range will be described.

That is, as an example of the realization, a representative point having the smallest value of the evaluation formula (for example, WH × ΔH + WL × ΔL + WC + ΔC) among the representative points described in the third embodiment is obtained, and the surrounding area is determined. Is the search range.

FIG. 4 shows a representative point 4 having the smallest value of the evaluation formula.
13 shows an example of the relationship between the search range 402 and the search range 402. A point in the search range 402 where the value of the evaluation expression is the smallest is set as a compression destination color value. As a method of realizing this, an evaluation expression (for example, the above-described WH × ΔH
+ WL × ΔL + WC + ΔC), and the color value at the minimum point is set as a compression destination.

As another method of calculating the compression destination,
There is a method of using interpolation calculation using the color value of the representative point.
This is a method of using the color values (hue value, lightness value, saturation value) of a representative point and estimating the color value of a point between them by interpolation calculation.

[0032]

As described above, according to the color image processing method of the present invention (claim 1), when the color image is outside the gamut, the representative point of the color value on the gamut boundary is defined in advance. Since the compression destination is specified using the representative point, efficient and faithful color reproduction is realized.

According to the color image processing method of the present invention (claim 2), when the gamut boundary surface is compressed using the color value of the representative point, the length between the representative points is divided for each divided gamut boundary plane. The representative point can be determined so that the colors are approximately equal, and the compression destination estimation accuracy at the time of compression becomes equal for all color values, compared to the process of performing compression on a constant brightness surface as is usually done. In this way, gamut compression can be performed, and stable color reproduction can be achieved.

According to the color image processing method of the present invention (claim 3), the compression destination is determined according to the emphasis of hue, lightness, and saturation. Faithful color reproduction based on the specification regarding the degree limit can be achieved.

According to the color image processing method of the present invention (claim 4), the search range in the gamut boundary surface is determined according to the emphasis of hue, lightness, and saturation. It is faithful to the user's requirements and realizes efficient and highly accurate color reproduction.

[Brief description of the drawings]

FIG. 1 is a flowchart illustrating a color reproduction processing procedure according to an embodiment.

FIG. 2 is an explanatory diagram showing an example in which a gamut boundary surface according to the first embodiment is defined by a representative point.

FIG. 3 is an explanatory diagram showing an example of setting a representative point according to the second embodiment (a) and an example (b) of determining a representative point with constant brightness.

FIG. 4 is an explanatory diagram showing a relationship between a representative point having the smallest value of an evaluation expression and a search range according to the fourth embodiment.

FIG. 5 is an explanatory diagram showing an example in which constant hue compression is not desirable.

[Explanation of symbols]

 401 Representative point having the smallest evaluation formula value among representative points 402 Search range

──────────────────────────────────────────────────の Continued on front page (51) Int.Cl. ⁶ Identification code FI H04N 11/04 H04N 9/79 H

Claims (4)

[Claims] If at least a part of the color image information is a non-reproducible color that cannot be reproduced in a gamut (color gamut) of a color image output system, the non-reproducible color is converted to a reproducible color of the color image output system. In the color image processing method, the boundary of the gamut is defined by a set of color values (representative points) on the gamut boundary surface, and a range of a representative point to be searched in the boundary is specified. Step 1 of determining the compression destination by using the process 1 and the color value of the representative point and the hue difference, lightness difference, or saturation difference between the color values to be compressed, or a combination thereof. 2. A color image processing method comprising the steps of: 2. The method according to claim 1, wherein in the first step, the representative point is defined by equally dividing the gamut boundary surface by a hue and equally dividing the length of the side of the gamut boundary surface in each hue. Item 2. The color image processing method according to Item 1. 3. The color image processing method according to claim 1, wherein in the second step, a compression destination is determined according to how to prioritize hue, lightness, and saturation. 4. The color image processing method according to claim 3, wherein the search range in the gamut boundary surface is determined according to the emphasis of hue, lightness, and saturation.