JPS6113259A - Color image processing method - Google Patents

Abstract

PURPOSE:To increase amts. of undercolor removal and black ink and to enhance color reproducibility by deciding amts. of undercolors to be removed (UCR amts.) in accordance with color image signals before operating masking processing of the color image signals having the density data of plural colors. CONSTITUTION:The color signals Y, M, C are fed to an addition circuit 5 and a Min selection circuit 1 to find min. density signals Min{Y,M,C} of each color signal. These signals are gamma converted with a black ink gamma conversion circuit 2 and outputted as a black ink amt. (black) (a). On the other hand, the signals Min{Y,M,C} are converted into UCRgamma' with the UCR amts. gamma conversion circuit 3, multiplied with a multiplication circuit 4, and converted into negative UCR amts. (b). These amts. are added with signals Y, M, C to convert them into signals YI, MI, CI. As a result, an ideal color reproductions are carried out.

Description

DETAILED DESCRIPTION OF THE INVENTION [Technical Field] The present invention relates to a digital color image processing method, and more particularly, to an image processing method in which an under color removal amount (UCR amount) is ideally determined based on color density data.

[Prior Art] Conventionally, when outputting image data to a printer using a digital color copying machine, etc., masking coefficients for each color have been changed in order to reproduce colors faithful to the original. With the fluctuation of
The amount of UCR and the amount of smear changed (see FIG. 1), and as a result, it was not possible to reproduce colors faithful to the original.

[Objective] An object of the present invention is to solve the above-mentioned problems, to prevent at least the UCR amount from being affected by variations in masking coefficients, etc., and to enable color reproduction faithful to the original.

[Example] Examples of the present invention will be described in detail below with reference to the drawings.

FIG. 2 is a block diagram showing an embodiment of the main parts of an image processing apparatus for carrying out the first invention.

As shown in Fig. 2, 1 is a selection circuit that selects the minimum density of each density data of Y (yellow), 9M (magenta), and C (cyan), 2 is a γ conversion circuit for the amount of smear, and 3 is a UCR.
4 is a multiplication circuit that makes the undercolor removal rate variable, and 5 is an addition circuit.

Reading systems such as copying machines, 7-upputs of computers) (O
tJT, PtJT) etc., when the density data of each color of Y, M and C is input to the selection circuit 1, the minimum density data (hereinafter Mi
n (represented by Y, M + C)) is selected and output. This minimum density data output is input to the γ conversion circuit 2, and is subjected to γ conversion by this circuit 2 to obtain the amount of smear.This minimum density data output is also input to the γ conversion circuit 3, which converts it into γ. and UCR amount or tr
It is the source of cRI. The characteristics of the two γ conversion circuits 2 and 3 do not necessarily have to match.

The signal UCRγ' output from the γ conversion circuit 3 is input to the multiplication circuit 4, where the undercolor removal rate is multiplied by -1, for example, and output, and then input to the addition circuit 5, where Y
, M and C density data signals. As a result, the Y, M, and C density data are outputted from the adder circuit 5 as data from which the undercolor has been removed.

Through the above processing, it is possible to determine the amount of undercolor removal and the amount of smear as shown in FIG. In addition, each of the above circuits 1,
2, 3.4 and 5 can be configured using memory. In addition, as shown in Figure 1s4, the selection circuit 1
, M, and C, and an encoder 7 that receives signals from these comparators 8A, 8B, and 8G.
and a data selector 8.

The addition circuit 5 may be configured with an adder, and if it is configured with a memory, the multiplication circuit 4 may be omitted. Further, the γ conversion circuits 2 and 3 have several types of γ conversion characteristics, and it is also possible to use a memory address signal as a selection signal for one γ conversion characteristic.

FIG. 5 is a block diagram showing an example of the entire image processing apparatus for carrying out the present invention. As shown in FIG. The undercolor removed data (YI, MI.

C' I ) is input to the masking processing circuit lO, where it is masked (YI[, MIl, CII),
The signal is roughly input to the γ conversion circuit 11 and subjected to γ conversion. In this way, the UCR amount and the amount of smear are determined based on the Y, M, and C density data before the masking process.

Therefore, since the density data of Y, M, and C processed by masking is not used, the quantization error is
In addition to being smaller than colors Y, M, and C, the UCR amount and smear amount are not affected by changing the masking coefficient.This means that when the image data that has been processed is output to a printer, Image feedback processing that changes the masking coefficient also produces the effect that the masking processing coefficient can be changed without almost changing the blackness of the reproduced image color.Furthermore, the amount of UCR and the amount of smear can be changed completely independently of masking. Since even the γ characteristics can be varied, ideal color reproduction can be achieved.

In addition, a part or all of each circuit 1 to 5 in FIG. 2 may be configured by software such as a microcomputer. A simple flowchart in this case is shown in FIG. Read the data of and C, determine whether Y<M in S2, and select Yes.
If so, proceed to S3, if No, proceed to S4. In S3, determine whether M<C, and if Yes, proceed to S5.
If so, proceed to S6. In S4, it is determined whether M<C, and if YES, the process proceeds to S7, and if NO, the process proceeds to S8. In S6, it is determined whether Y<C, and Yes
If so, proceed to S5, and if NO, proceed to S7. In S5, select Y as the minimum density data, select C as the minimum density data in S7, select M as the minimum density data in S8, and proceed to S9.

In S9, the minimum density data (Min(Y.

M, C) are γ-converted to determine the amount of smear, and the process proceeds to S10.In 510, the minimum density data is γ-converted and multiplied by a coefficient to determine the UCR amount, and the process proceeds to Sit.In S11, Y, M YI, MI, and CI are obtained by subtracting the UCR amount from the data of and C, and the process proceeds to S12, where the undercolor is removed.

Outputs MI, CI and sumi amount.

[Effects] As explained above, according to the present invention, a color image processing signal can be maintained at ideal characteristics as shown in FIG. 3, for example. That is, for input images with low density, no undercolor removal is performed, and the amount of smear is set to 0.
For input images with high density, both the UCR amount and the amount of smear can be increased. This enables ideal color reproduction.

[Brief explanation of drawings]

Figure 1 is a diagram showing an example of conventional image processing conversion characteristics;
The figure is a block diagram of an embodiment of the main part of an image processing device for carrying out the present invention. Figure 3 is a diagram showing an example of image processing conversion characteristics according to the present invention. Figure 4 is a block diagram of the minimum data selection circuit. 5 is a block diagram showing an example of the entire image processing apparatus for implementing the present invention, and FIG. 8 is a flowchart showing an example of image processing according to the present invention. 1... Minimum data selection circuit, 2... Gamma conversion circuit for the amount of ink, 3... Gamma conversion circuit for UCR, 4... Multiplication circuit, 5... Addition circuit. Figure 5 (available)

Claims (1)

[Claims] In a color image processing method, in which a smear amount and a UCR amount are determined based on a color image signal having density data of a plurality of colors, and a masking process is performed on the color image signal, based on the color image signal before the masking process. A color image processing method, comprising determining at least an amount of UCR.