JPH07108019B2 - Color image processing method - Google Patents

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.

[0002]

2. Description of the Related Art Generally, when reading and reproducing an original color image in a color image processing apparatus, an original is separated by a scanner into three component color images of red, green and blue which are three primary colors of a subtractive color mixture system. After reading, after performing color processing such as complementary color conversion, masking, under color removal (UCR) on each component color image,
The image data for each color corresponding to the three primary colors of the additive color mixing system, yellow, magenta, cyan, and black are formed. Then, the color image data is combined to form a color image. The color processing as described above is performed prior to such combination. For example, ink of each component color used for color image reproduction, such as yellow This is because each of the magenta ink, the cyan ink, and the cyan ink has a spectral reflectance characteristic different from the ideal spectral reflectance characteristic.

In general, undercolor removal, that is, UCR processing, removes from each image data corresponding to yellow, magenta, and cyan, an equal amount of undercolor corresponding to black and removes black to obtain image data corresponding to black. The concentration of, that is, the so-called sum amount is calculated. Such processing is performed in order to accurately reproduce an achromatic color (gray) that is difficult to faithfully reproduce depending on the three color materials of yellow, magenta, and cyan. It is also an important matter in printing technology to save the amount of ink used by replacing the three primary color inks with black ink.

The UCR process is defined as the minimum density value of each of the yellow, magenta, and cyan color component densities is 100%, and an amount equal to or less than the minimum density value is removed from each color component density as an undercolor. Further, the amount less than or equal to this minimum density value is the amount of smear. Apply to general color images
The UCR amount is usually 50% or less of the minimum density value, and the UCR process reproduces the shadow portion by both the calculated amount of smear and the remaining black of the three color mixture.

[0005]

However, in the undercolor removal processing in the conventional color image processing apparatus, the UCR amount with respect to the minimum density value is generally a fixed value determined empirically. Therefore, the colors of the image to be reproduced are abundant,
In the case of color photographs with rich gradation, even if there is a color shift, it has little visual impact, but it is an image in which text overlaps the full-color image, or a portion represented by fine lines in the shadow part. (Hereinafter, it is referred to as a detail portion.) That is, in an image with a large edge amount, when a color shift occurs, a color shift of a character portion or a thin line becomes conspicuous, and as a result, color turbidity or image blur occurs.

There is also a UCR amount variable as disclosed in Japanese Patent Laid-Open No. 185446/1982. Although the UCR amount is controlled by detecting gray, the edge amount is not detected. After all, color blur and image blurring occurred in the character part and the detail part.

[0007]

In order to solve the above problems, a color image processing method of the present invention is a color image processing method for performing undercolor removal processing on a color digital image signal of a plurality of color components, Detecting the edge amount in the image represented by the color digital image signals of the plurality of color components, determining the black component from the color digital image signal of the plurality of color components, depending on the detected edge amount and the determined black component The amount of undercolor removal for the color digital image signal is controlled in multiple stages.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail below with reference to the drawings.

First, an embodiment of the principle configuration of the color image processing method according to the present invention is shown in FIG. In the illustrated principle configuration, the edge detector ED detects the amount of change in density at the edge portion of the image, the edge amount ED, and the black level detector 2 detects the image black level BL in the multiplier MUL. Then, the undercolor removal amount UCR and the corner amount CB which are proportional to the product of the two are calculated, and these are supplied to the subtractor unit and the adder ADD, respectively. Subtractor SUB
Since the yellow Y, magenta M, and cyan C densities are supplied, the subtraction outputs are the remaining three primary color densities YY, MM, and CC obtained by subtracting the undercolor removal amount UCR. Also,
Since the black density amount K is supplied to the adder ADD,
The added output is the black density K obtained by adding the corner amount CB.
You get K. Therefore, with the above configuration, it is possible to perform the variable undercolor removal corresponding to the edge amount and the black level of the image, and as a result, it is possible to reduce the color misregistration at the edge portion and to reduce the color turbidity of the image due to the color misregistration. The blur of the image is not noticeable.

The operation principle of the processing method of the present invention can be easily understood by considering a black character as an example of an edge portion in a halftone full color image. In the edge portion of the black character, the density change is larger than in the other halftone portions, and the edge amount that can be detected by the edge detection portion is large. Also, since it is a black character, each complementary color, that is,
The density value of black K, which corresponds to the minimum value among the density values of yellow Y, magenta M, and cyan C, is also large. Therefore, the undercolor removal amount UCR also becomes large at the edge part of the black character, the black character image with a larger UCR amount than other halftone parts is reproduced, and the black character in the halftone full color image is clearly reproduced. . Furthermore, if the corner amount CB is made larger than the UCR amount, the edge portion of the black character is further emphasized. Moreover, such an operating principle can be applied to the shadow portion in the halftone full-color image in the same manner as described above.

Next, FIG. 2 shows an example of a detailed configuration for realizing the color image processing method of the present invention. An example of the signal waveform of each part will be described later with reference to (A) to (G) of FIG.

In the configuration example of FIG. 2, each color density signal obtained by decomposing the digital color image density signal, that is, each color signal of yellow Y, magenta M, and cyan C is input to each of the input terminals 4, 5 and 6, and the minimum The values are supplied in parallel to the value calculator 7, the edge detector 8, and the adders 12, 13, 14 for each color. In the minimum value calculation unit 7, each digital color signal Y,
The color signal of the minimum value of the density of M and C is the color signal black K = Mi
It is calculated as n {Y, M, C} and supplied to the edge detection unit 8 and the black level detection unit 9. Black level detector 9
In, the black density level BL having a value proportional to the density of the color signal black K is calculated.

The black density level BL is effectively set to the following values in order to reduce the color image information amount. One example is shown in FIGS. 3 (A) and 3 (B). FIG. 3A shows an example of the configuration of the black level detection unit 9. The color signal black K, which has an 8-bit configuration, from the minimum value calculation unit 7 is used for the comparators 16 and 17 for each complementary color.
And 18 in parallel to one input terminal A and the other input terminal B to the comparison thresholds TH1 and TH2 for each complementary color.
And TH3 respectively, and compare with color signal black K.

The comparison thresholds TH1, TH2, TH3 and TH4 are selected at unequal intervals as shown in FIG. 3B, and the comparison output signals of the comparators 16 to 18 are encoded by the encoder 19 to A 2-bit signal as shown in (B) of 3 is obtained. In this way, the density level of the shadow part can be expressed by a small amount of information by 2 bits.

On the other hand, the edge detector 8 detects the edge portion in each of the color signals Y, M and C by using, for example, Laplacian. FIG. 4 shows an example of the manner of detecting the edge portion. FIG. 4 shows a pixel group centered on the pixel (i, j) and shows the difference between the density level of each adjacent pixel when the density level of the pixel of interest (i, j) is P (i, j). The sum E is calculated as follows.

[0016]

[Equation 1]

Here, m ≠ i and n ≠ j, and P (i, j) is digital density data.

Examples of operation waveforms for detecting the above-mentioned edge portion are sequentially shown in FIGS. 5A to 5G. However, in FIG. 5, each signal waveform is a digital signal waveform.

Now, each color signal Y or M, C is shown in FIG.
It is assumed to have an edge portion of the signal waveform as shown in (A). Regarding the edge part of such a waveform, the rising edge and the falling edge are divided in two at the center of each,
Let the first and second halves of each be A, B and C, D as shown. When the above equation (1) is calculated for the half-edge portions A, B, C and D, the edge detector 8 produces signals EY, E having waveforms as shown in FIG. 5B, respectively.
M, EC and EK are obtained. It should be noted that the result of performing such calculation on the non-edge portion is always zero. These signals are input to the function conversion units 10 and 11, respectively, and the function conversion units 10 and 11 further include a black level detection unit.
Black density level B of the waveform shown in (C) of FIG. 5 from 9
Is input, and the function conversion unit 10
Edge amount E and black density level by and 11
Waveform functions f (EY ・ B), f (EM ・ B), f (EC ・ B), and (E) in Fig. 5 with B as a parameter in Fig. 5 (D).
The function f (EK · B) of the waveform shown in is obtained. In the configuration example shown in FIG. 2, among these functions, each color signal Y 1, M 2
For C and C, among the half-edge parts A, B, C, D, A
For D and D, it is a function proportional to both the edge amount E and the black density level B, and for the half edges B and C, the edge amount E and the black density level.
Converts to a negative signal in proportion to both B. Regarding the black signal K 1, each half edge portion A, B, C, D is converted into a function proportional to both the edge portion E and the black density level K 2.

The functions obtained for each color signal as described above are supplied to the signal adders 12, 13, 14 to be added to the color signals Y, M, C, respectively, and the functions obtained for the black signal K are obtained. Is supplied to the signal addition unit 15 and added with the black signal K, and the following calculation is performed.

[0021]

[Formula 2] YY = Y + f (EY ・ B) (2) MM = M + f (EM ・ B) (3) CC = C + f (EC ・ B) (4) KK = K + f (EK ・ B) (5) Above The respective signals YY, MM, CC and KK of the waveforms shown in (F) and (G) of Fig. 5 thus obtained represent the edge portion of the respective signals Y, M and C, and the minimum density value Min {Y,
When M, C} is a large blackish edge portion, the density of each color signal Y, M, C is reduced to increase the black density. The signal waveforms shown by broken lines in (F) and (G) of FIG. 5 are the original signal waveforms shown in (A) of FIG.

Therefore, according to the color image processing method described in this embodiment, the edge portion in the shadow portion can be particularly emphasized and the degree of the edge portion emphasis can be changed according to the black density level.

[0023]

According to the present invention, since the undercolor removal amount is controlled in multiple stages by using the edge amount and the black component of the image, it is possible to reproduce a color image by multiplexing color image data of a plurality of color components. In addition, it is possible to remove the undercolor in consideration of the edge amount, and color turbidity and image blurring caused by color misregistration are less noticeable, and good color image reproduction is possible.Even if color misregistration occurs, image deterioration due to color misregistration occurs. The effect of being able to reduce the influence of is exerted.

[Brief description of drawings]

FIG. 1 is a block diagram showing a basic configuration of a color image processing apparatus according to the present invention.

FIG. 2 is a block diagram showing a detailed configuration example of the device.

3A and 3B are a block diagram and a characteristic curve diagram showing a configuration example of a black level detection unit and a configuration example of a detection comparison threshold value, respectively, in the same apparatus.

FIG. 4 is a diagram showing an example of an aspect of edge portion detection in the same apparatus.

5 (A) to (G) are signal waveform diagrams showing examples of operation signal waveforms of respective parts in the configuration example of FIG. 2.

[Explanation of symbols]

 1,8 Edge detector 2,9 Black level detector 3 Edge signal generator 4,5,6 Input terminal 7 Minimum value calculator 10,11 Function converter 12,13,14,15 Signal adder 16,17, 18 Comparator 19 Encoder SUB Subtractor ADD Adder

Claims (1)

[Claims] 1. A color image processing method for performing undercolor removal processing on a color digital image signal of a plurality of color components, the method comprising: detecting an edge amount in an image represented by the color digital image signal of a plurality of color components; A black component is determined from a color digital image signal of a color component, and an undercolor removal amount for the color digital image signal is controlled in multiple stages according to the detected edge amount and the determined black component. Color image processing method.