JPH0473830B2 - - Google Patents

Description

[Detailed Description of the Invention] [Field of Application of the Invention] The present invention relates to a method for correcting color image information, and in particular to obtaining a copy of an original image by printing or the like from color image information given by a color image signal based on RGB three primary color data. Regarding color correction method in case.

[Background of the invention]

Conventionally, so-called printing plate-making scanners have been widely used for printing color images, but in recent years, as various data processing methods using computers have been proposed and put into practical use, such scanners have become increasingly popular. By applying various data processing techniques to this image data after converting it into electrical image data, it has become possible to obtain even more effective printed images. There are color correction techniques.

Incidentally, the methods conventionally used for such color correction have been mainly based on the Neugebauer equation or the photographic masking method.

However, these conventional color correction methods require a large number of parameters to be considered, require a high level of skill for color correction work, and are difficult to manage colors that match the three attributes of color perception: hue, saturation, and brightness. It had the disadvantage of being.

Therefore, in order to eliminate these drawbacks of the conventional technology, color image information is separated into three parts: hue, cloudiness, and gradation.
A color correction method that makes it possible to easily and accurately correct cloudiness of ink during printing or arbitrarily control hue, cloudiness, and gradation was filed as an invention in Japanese Patent Application No. 156514/1983. This application method will be explained below.

In this previously applied method, each of the three primary color data of color image information is rearranged for each pixel to form three data arranged in order of size, and based on these three data, the hue and cloudiness of each pixel are determined.
In addition, information representing each gradation is obtained, so as shown in Figure 2, the color image information is preprocessed.

Separation conversion processing of three attribute data based on preprocessed signals.

Synthesis processing of 3 attribute data.

Post-processing consisting of sumi version calculation and UCR.

Through these four processes, color-corrected data for the original image data is obtained.

(Preprocessing) The contents of this process are as follows.

(1-1) Input color information r, g, b for each pixel of color image information read from the original image using a scanner or the like and stored in advance in memory.

(1-2) Normalize the size of color information r, g, b between 0 (low brightness) and 1 (high brightness), then convert this into complements and define complementary color information c, m, y. do. That is, 0≦r, g, b≦1 cΔ = 1−r, mΔ = 1−g, yΔ = 1−b.

(1-3) Complementary color information c, m, and y are sorted and arranged in ascending order, and the largest one is defined as data a ₁ , the second one is data a ₂ , and the third one is defined as a ₃ .

Here, a ₁ , a ₂ , and a ₃ are referred to as preprocessed data.

(Separation and Conversion Processing) This processing consists of the following three processes that proceed in parallel based on preprocessed data a ₁ , a ₂ , and a ₃ .

(a) Separation conversion processing of hue information c ₁ , m ₁ , y ₁ .

(b) Separation and conversion processing of cloudy information c ₁ ′, m ₁ ′, y ₁ ′.

(c) Separation and conversion processing of gradation information g.

(Separation and conversion process of hue information (a)) This process is a process of selecting a factor that determines the hue, calculating the hue from this, and obtaining the hue information using the hue table.

(A-1) First, determine the factors necessary to determine hue.

．． When (a ₂ ≠ a ₃ ), let (a ₁ − a ₃ ) and (a ₂ − a ₃ ) be factors.

．． In the case of (a ₂ = a ₃ ) (a ₁ − a ₃ is a factor).

This is due to the following reason.

This is because the component with the smallest value among the complementary color information c, m, and y does not become a factor that determines the hue. In other words, the component with the smallest value is because adding it will only make the color closer to gray (that is, reduce the saturation, in other words, increase the muddiness), and the hue will not change. It is. Specifically speaking, (a
This is because data a ₃ when ≠ a 3 ) and data a _{2 and} a ₃ when (a ₂ = a ₃ ) each function only as cloudy components and do not become factors that change the hue. .

Therefore, as mentioned above, complementary color information c, m, y
The component other than the component with the smallest value is selected as the factor that determines the hue.

And the hue in the above case is (a ₂ −
From a ₃ )/(a ₁ − _{a 3} ), as shown in Figure 3, among the points that internally divide the real number line on the hue diagram in which the hues are arranged in order of wavelength, the data becomes a ₁ . c, m, y, which is the point immediately before any of c, m, y, and in the above case, c, m, which is data a ₁ .
This is the point where one of y is located.

For example, data c, m, y is c=0.3, m
= 0.1, y = 0, in this case,
a ₁ = c = 0.3, a ₂ = m = 0.1, a ₃ = y = 0,
Therefore, since (a ₂ ≠ a ₃ ), (a ₂ − a ₃ )/(a ₁ −
a ₃ ) = 1/3 and a ₁ = c (cyan), the third
The point * in the figure is the hue of the above data.

(A-2) Next, as shown in Figure 4, the horizontal axis shows the hue in order of wavelength, and the vertical axis shows the amount of ink (called dot % or sepa density) at the highest gradation for each hue. If you prepare a completed hue table and convert it by referring to it at the hue position described above, you can obtain the amount of ink that does not include cloudiness at the highest gradation required for each version of c, m, and y (separated version). Hue information corresponding to c ₁ ,
m ₁ and y ₁ can be obtained.

(Separation and conversion processing of turbidity information (b)) (b-1) The amount of turbidity is expressed by the amount of the opposite color (complementary color) contained in a certain color. In other words, when looking at a certain color, it is generally thought that the color that exhibits the maximum saturation of the hue that it exhibits is mixed with the complementary color of that color, resulting in a color that is unique to that color. be able to.

Therefore, if the amount of complementary color mixed with a certain color is zero, then the amount of cloudiness is zero, that is, the maximum saturation, so the amount of complementary color is This is regarded as the amount by which the saturation of the color exhibiting maximum saturation is reduced, and is defined as the amount of cloudiness.

Therefore, the original data, that is, complementary color information c, m, y here, and the opposite colors thereof are (1-c, 1-m, 1-y).

If we sort this and arrange it in descending order, we get a ₁ , a ₂ , a ₃ as mentioned above, but if we look at a ₃ , which is the minimum value among them, it is 0 to a It takes the value (a≧a ₁ ). Color is represented by a ₁ and a ₂ . The amount of cloudiness is expressed by a ₃ , so a ₃ = 0
When , the saturation of the color represented by a ₁ and a ₂ is maximum, that is, the turbidity is 0. Note that in a black and white image, a ₁ = a ₂ = a ₃ , and at this time it can be considered that the amount of cloudiness is at its maximum.

As a result, considering the complementary color information c, m, and y given, the colors represented by them are the colors c′, m′, and
For y', its complementary color (1-c', 1-m', 1
−y′) can be analyzed to be a color added at a ratio of a ₃ /a _1. Therefore, in this example, it can be analyzed to be a color added at a ratio of a ₃ /a ₁ , and Therefore, in this embodiment, a ₃ /a ₁ is the hue information c ₁ ,
Let it be the proportion of turbidity that should be added to m ₁ and y ₁ .

(B-2) Therefore, using the data c ₁ , m ₁ , y ₁ and the data a ₁ , a ₃ obtained in the process of (A-2) above, (c ₁ ′, m ₁ ′, y ₁ ′) =a ₃ /a ₁ (1-c ₁ , 1-m ₁ , 1-y ₁ ) ...(5) is calculated to obtain cloudy information c ₁ ′, m ₁ ′, y ₁ ′.

(Separation and conversion processing of gradation information (c)) (c-1) The gradation can be expressed by the value of the data _a1 itself. This is because in preprocessing,
Color information r, g, b is from minimum value = 0 to maximum value = 1
Therefore, the maximum gradation of the hue is always when a ₁ =1. In other words, the gradation is given by the ratio of the data a ₁ at that time to the maximum value of this data a ₁ , but since the maximum value of the data a ₁ is 1, the gradation is (a ₁ / 1) = a ₁ . It will become.

(C-2) Next, prepare a gradation conversion table as shown in FIG. 5, and refer to this table using data _a1 to obtain gradation information g with desired characteristics.

(Synthesizing Process) This process is to obtain dot % or sepa concentration data c ₂ , m ₂ , y ₂ necessary for each separation plate other than the black plate, and the calculation process is as follows.

c ₂ = (c ₁ + c ₁ ′) × g m ₂ = (m ₁ + m ₁ ′) × g y ₂ = (y ₁ + y ₁ ′) × g) ...(6) (Post-processing) Create data _k2 that represents the amount of ink required for the plate, and perform processing when performing UCR (undercolor removal).

(4-1) In the sumi-ban calculation, data k ₂ is first defined and calculated as follows.

k ₂ △ = min (c ₂ , m ₂ , y ₂ ) where min represents a function that gives the minimum value.

(4-2) Prepare the sumi version table shown in Figure 6, and use it to calculate the final data to be used from data k _2.
By converting to _k3 , it is possible to arbitrarily realize either full black or skeleton black by selecting characteristics a and b.

(4-3) When applying UCR, the final data c ₃ , m ₃ , y ₃ are obtained by the following calculations.

c ₃ = c ₂ −α・k ₃ m ₃ = m ₂ −α・k ₃ y ₃ = y ₂ −α・k ₃ ...(7) However, α: UCR rate 0α1 Based on the data obtained in this way, cyan and magenta ,
By exposing each of the yellow separation plates and the blackout plate, it is possible to obtain a printed matter with the desired color development.

According to this method, the color correction work is
For hue, the task is to select the characteristics of the hue table shown in Figure 4, and for cloudiness, the task is to adjust the magnitude of a ₃ /a ₁ in equation (5) above for each color. Then, for the gradation, the task is to select the characteristics of the gradation table shown in Figure 5, which are mutually independent tasks and correspond to the three perceptual attributes of color. , can be performed extremely easily and accurately.

By the way, some of the color image information supplied as a printing original has a lot of cloudiness in the image if it is left as it is, and therefore, if it is used as a printing original as it is, it will not be possible to obtain a desirable result as a printed matter.

On the other hand, in the method of the above-mentioned application, although the cloudy components of the original image are extracted and processed, the purpose is simply to faithfully reproduce the amount of cloudiness in the original image. If original image information containing a lot of turbidity is processed, the turbidity will be reproduced as is, making it impossible to obtain appropriate printed matter.

[Purpose of the invention]

The present invention has been made in view of the above-mentioned circumstances, and its purpose is to eliminate a lot of cloudiness,
Therefore, it is an object of the present invention to provide a color correction method that can always produce suitable printed matter even when a color original image that gives an overall dark impression and is inappropriate as a printing document is given.

[Summary of the invention]

In order to achieve this object, the present invention provides a color correction method that separates color image information into three components: hue, cloudiness, and gradation, and processes these components independently. , is characterized in that it is possible to freely control the amount of clouding in the image that becomes the printed document.

[Embodiments of the invention]

Hereinafter, the color correction method according to the present invention will be explained in detail with reference to illustrated embodiments.

FIG. 1 shows an embodiment of the present invention, in which 1
0 indicates cloudy correction processing, and the rest is the same as in FIG. 2.

In the turbidity correction process 10, the turbidity information c ₁ ′, m ₁ ′, y ₁ ′ obtained by the above equation (5) is inputted, and the corrected turbidity information c ₁ ″, m ₁ ″, y ₁ is calculated by the following equation. It works to output ″.

Here, α, β, and γ are coefficients for determining the correction rate given to each of the complementary color information c, m, and y, and take values from 0 to 1, and can be any value within this range. It is set to . Also, the two items on the right side (a ₁ - c)/a ₁ , (a ₁ - m)/a ₁ , (a ₁
-y)/a ₁ is a value representing the amount of cloudiness possessed by the complementary color information c, m, and y, respectively.

In the embodiment shown in FIG.
The synthesis process to obtain c ₂ , m ₂ , and y ₂ is the following calculation process using the corrected cloudy information c ₁ ″, m ₁ ″, and y ₁ ″.

c ₂ = (c ₁ + c ₁ ″) × g m ₂ = (m ₁ + m ₁ ″) × g y ₂ = (y ₁ + y ₁ ″) × g) ……(6)′ Note that the other processing is It is the same as the case in Figure 2.

Therefore, according to this embodiment, if the above-mentioned coefficients α, β, and γ are set to predetermined values separately or all at once depending on the cloudy state of the image based on the original color image information, the original The state of cloudiness in the image can be changed arbitrarily, and if necessary, the cloudiness in the original image can be completely eliminated or left in a predetermined amount, no matter what original image is given. Optimal printed images can always be obtained.

By the way, in the above embodiment, the color information r, g, b from the original image is read out from the memory and processed, but it is also possible to process it in real time while reading it with a scanner.

Furthermore, if the color information based on the original image data is directly given as complementary color information c, m, and y, it goes without saying that inversion processing in preprocessing is unnecessary.

In the above explanation, the present invention has been explained in relation to printing plate making, but the present invention is not limited to printing plate making.
It can also be applied to color correction in various color hard copy production devices such as inkjet type and electrostatic type printers and copiers, and even in these cases, the same effect as the above embodiment can be expected. Needless to say.

〔Effect of the invention〕

As explained above, according to the present invention, in addition to the conventional method in which color image information is processed by separating it into three components: hue, cloudiness, and gradation, the amount of cloudiness in the image can be controlled arbitrarily. The effects of this conventional method are that color correction processing can be performed according to the sensory classification of colors (hue, saturation, brightness), and there is no concept of parameters, making color matching work intuitive and easy. I can do it.

Hue and brightness can be controlled completely independently, making corrections easy and accurate.

Color communication between multiple workers such as designers and color separation operators becomes smoother.

It can be implemented as either a hardware system or a software system, and has a wide range of applications.

Even when it comes to a hardware system, it can be realized using an inexpensive, highly accurate digital circuit, without requiring the expensive and precise analog circuits used in the past.

Completely independent hue control is possible for each arbitrarily set hue.

In addition to the above effects, it is possible to easily provide a color correction method that provides the excellent effects listed below.

The cloudiness of the original image can be reduced,
An image with increased overall brightness can be obtained.

Colors that contain a lot of cloudy components have a particularly large cloudy removal effect and are converted into more vivid colors, but colors that are close to pure colors do not change much, so the original image's richness can be fully utilized.

Nothing changes in completely black parts of the original picture (parts containing equal amounts of C, M, and Y), and the cloud removal effect appears selectively only in parts containing hue components (chromatic parts). , In this respect as well, it is possible to fully retain the flavor of the original painting.

[Brief explanation of drawings]

FIG. 1 is an explanatory diagram showing the operation of an embodiment of the color correction method according to the present invention, FIG. 2 is an explanatory diagram showing an example of the conventional color correction method, FIG. 3 is an explanatory diagram of hue determination processing, and FIG. The figure is an explanatory diagram showing an example of a hue table,
FIG. 5 is an explanatory diagram showing an example of a gradation conversion table;
FIG. 6 is an explanatory diagram showing an example of a blackboard table. ...Pre-processing, ...separation conversion processing, ...combining processing, ...post-processing, 10...turbidity correction processing.

Claims (1)

[Scope of Claims] 1. Preprocessed data representing the magnitude relationship of three types of complementary color information c, m, and y corresponding to the three primary colors of each pixel, for each pixel of the three primary color image information to be color corrected.
A method for determining a ₁ , a ₂ , and a ₃ and factors representing the hue of the color image information are determined from the magnitude relationship of the preprocessed data, and a method is used to determine the hue on the hue diagram based on the complementary color information and the factors. A means for obtaining hue information c ₁ , m ₁ , y ₁ by referring to a hue table based on the hue position; means for obtaining turbidity information based on the ratio and the color information; and means for obtaining gradation information by referring to a gradation table based on data representing the maximum value of the preprocessed data. In preparation, in a color correction method that independently corrects the hue, turbidity, and gradation of color image information, the above turbidity information is set to c ₁ ′, m ₁ ′, y ₁ ′, and from now on c ₁ ″=c ₁ ′−α・(a ₁ −c/a ₁ )・(1−c ₁ ) m ₁ ″=m ₁ ′−β・(a ₁ −m/a ₁ )・(1−m ₁ ) y ₁ ″=y ₁ ′−γ・(a ₁ −y/a ₁ )・(1−y ₁ ) α, β, γ: Cloudy information corrected by calculation processing as coefficients c ₁ ″,
A means for creating m ₁ ″, y ₁ ″ is provided, and the above coefficients α,
A color correction method characterized in that the amount of blur in an image is controlled by changing β and γ.