JP3033440B2 - Image processing apparatus and 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 an image processing apparatus and an image processing apparatus.
Relates management method, more particularly, a halftone image of a color 2
With the function of creating pseudo-halftone color image data by digitizing, for example, a digital color copier,
Image processing device and image processing method for color printer, etc.
It is about the law .

[0002]

2. Description of the Related Art Conventionally, as a means for generating a pseudo halftone image by binarizing a halftone image, an image is converted to a binary image according to a threshold matrix (dither matrix) table.
Various dithering methods, such as a systematic dithering method, are increasingly used. However, these conventional methods have a contradiction that the matrix table needs to be enlarged in order to improve the tone reproducibility, and the matrix table must be reduced in order to obtain high resolution. It was difficult to achieve both reproducibility and high resolution.

In addition to the above, there is an error diffusion method as a method for achieving both gradation reproducibility and high resolution, and a relatively good evaluation is given among various conventional methods.

Here, a processing procedure of a conventionally proposed error diffusion method will be described with reference to FIGS.

FIG. 3 is a block circuit diagram showing a schematic configuration of an image processing apparatus for realizing the conventionally proposed error diffusion method. FIG. 4 is a flowchart showing the processing procedure, and FIG. FIG. 4 is an explanatory diagram showing an example of an error distribution method in a diffusion method.

First, an image processing apparatus shown in FIG. 3 includes an original image storage device (image memory) 2 for storing halftone original image data input as a digital signal, and a random access used as a working register or a buffer. Memory (RAM) 3 and read-only memory (R
OM) 4, a central processing unit (CPU) 5 for performing various image processing by executing a predetermined control operation in accordance with a program stored in advance in the ROM 4, and pseudo halftone image data subjected to binarization processing And an output image storage device (image memory) 6 for storing
Note that the ROM 4 stores a weighting coefficient matrix of peripheral pixels distributed by the error diffusion method, a threshold T as a reference for binarization, and the like.

The central processing unit (CPU) 5 executes the procedure shown in FIG. 4 to convert the halftone original image data previously input to the original image storage device (image memory) 2 by the error diffusion method. To generate pseudo halftone image data, and store the pseudo halftone binary data in the output image storage device (image memory) 6.

The details will be described below. First, FIG.
In step S1, the CPU 5 extracts the input density value I of the pixel of interest from the image memory 2. Next, in step S2, a threshold value T used for the binarization processing is read from the ROM 4. Conventionally, the same value is used as this threshold value T for all input data. Generally, in the case of image data of 256 gradations, for example, when the input density value I is 0 to 255, Since the value varies within the range, the intermediate value “128” is often used as the threshold T.

Next, at step S3, the RAM 3
The "weighted error sum E" of the binarization error of the peripheral pixels distributed to the target pixel is read, and added to the input density value I of the target pixel previously read from the image memory 2 to obtain a corrected input density I '. .

In step S4, the output density O of the target pixel is determined by comparing the threshold value T with the corrected input density I '. That is, when I ′ ≧ T, the output density O becomes “2
55 ”(step S5), and if I ′ <T, the output density O becomes“ 0 ”(step S6).

If the output density value of the pixel of interest determined as described above is "255", the binary data of "1" is converted to the binary data of "0" if the output density value is "0". Data
The data is written into the image memory 6 (step S7), and the binarization error e (corrected input density I '
Is subtracted from the output density value O) (step S).
8) Distribute to peripheral pixels. That is, error diffusion is performed.

In this distribution, for example, as shown in FIG. 5, a ratio of the binarization error e of the pixel of interest “*” to which peripheral pixels and at what ratio is determined as a “weighting coefficient matrix”. ROM4 stored in advance
Refer to the contents of

Then, the coefficient value of the corresponding pixel is extracted from the positional relationship between the target pixel and the peripheral pixel, and the coefficient value is multiplied by the binarization error e of the target pixel, thereby obtaining the error for each peripheral pixel to be distributed. Find the value. This error value is stored in RAM
3 is added to a buffer allocated to a part of the pixel, that is, a buffer for storing a binarized error sum that stores the error value distributed to each peripheral pixel for each pixel and stores it as a “weighted error sum E”. Then, it prepares for the binarization processing of the next pixel (steps S9 and S10).

The above processing is performed for each pixel.

[0015]

However, an image processing apparatus, for example, a digital processing apparatus for generating a pseudo halftone color image data by binarizing a color halftone image by applying the error diffusion method as described above. The following problems have been encountered in image processing apparatuses in color copiers of the type or color printers such as thermal transfer or ink jet printers.

That is, in the binarization of the target pixel,
Since the peripheral pixels are already binarized, C, M, and Y are recorded even in areas where the density values of cyan (C), magenta (M), and yellow (Y) of the original image match. There is a case where the pixels overlap and a case where the pixels do not overlap, which causes a problem that the reproducibility of gray is different.

For example, if there is an area where the density values of C, M, and Y coincide with each other at the head of the original image, the binarization errors distributed to the target pixel are equal, so that the C, M, and Y recording pixels The arrangements match, so that gray is reproduced.

However, when a color image exists at the center of the original image or the like, the value of the binarization error distributed to the target pixel differs depending on the color component. Even if they match, the arrangement of the C, M, and Y recording pixels may shift, and gray may not be reproduced well.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-described problem, and is capable of producing pseudo-halftone color image data with good gray reproducibility regardless of the binarization error to be distributed. It is an object to provide a processing device and an image processing method .

[0020]

In order to achieve this object, in the image processing apparatus according to the present invention, a color halftone image is binarized to generate pseudo halftone color image data. In the image processing apparatus, if there is a pixel whose cyan, magenta, and yellow density values match,
A color data replacing means for replacing the density values of cyan, magenta and yellow with black, and a binarization processing for performing a binary processing by an error diffusion method based on the density values replaced by the color data replacing means Means.

An image processing method according to the second aspect of the present invention.
In the method, a color halftone image is binarized
Image processing method for creating halftone color image data
Before performing the binarization process,
And the density values of cyan, magenta, and yellow match
Check if there is a pixel that is
If there is, the cyan, magenta, and yellow
Replace the degree value with black, and replace cyan and magenta
Error diffusion based on the density values of
It is characterized in that a binarization process is performed by a method.

Further, the image processing according to the third aspect of the present invention.
The method according to claim 2, wherein
To replace the cyan, magenta, yellow, and black
Based on each density value, binarize one color for all pixels
And then proceed to another color binarization process
It is characterized by that. The invention according to claim 4
3. The image processing method according to claim 2, wherein
Method, the substituted cyan, magenta, yellow and yellow
The binarization process for the pixel of interest is fully performed based on the density values of black and black.
Performs over the color, and then binarizes the next pixel of interest
The feature is that it shifts to. Further, in claim 5
In the image processing method of the invention described above, the color halftone
Creates pseudo-halftone color image data by binarizing the image
In the image processing method, the binarization processing is performed by focusing on each pixel.
Before processing, the cyan, magenta,
Check if the density values of the rows match, and if
If there is, the cyan, magenta, yellow of the pixel of interest
Is replaced with black, and the cyan, maze
Error based on the density values of
Binary processing is performed by the difference diffusion method, and then the next attention
If the density values of cyan, magenta, and yellow of the pixels match,
It is characterized in that the process shifts to a processing operation for checking whether or not there is an error .

[0023]

According to the present invention, there is provided an image processing apparatus having the above-described configuration, and
In the image processing method , if there is a pixel whose cyan, magenta, and yellow density values match beforehand before the binarization processing of the color halftone image by the binarization processing unit, the color data replacement unit Then, the cyan, magenta, and yellow density values of the pixel are replaced with black, and based on the replaced cyan, magenta, yellow, and black density values, binarization processing is performed by an error diffusion method. Therefore, irrespective of the binarization error distributed by the error diffusion method, pseudo halftone color image data with good gray reproducibility can be created.

[0024]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below with reference to the drawings.

The schematic configuration of the image processing apparatus of the present embodiment is substantially the same as that of the image processing apparatus shown in FIG. 3, and has a central processing unit (CPU) 5 functioning as a binarization processing means. However, they differ in that they are configured to also function as color data replacement means.

That is, the CPU 5 stores in the image memory 2
After inputting the color data of all the pixels included in one screen as a color halftone image, before performing the binarization processing by the error diffusion method, the color data replacement processing is performed according to the procedure shown in FIG.

More specifically, for all pixels of one screen stored in the image memory 2, there are pixels whose cyan (C), magenta (M), and yellow (Y) density values match. Check if there is a matching pixel,
The density values of C, M, and Y are replaced with black.

The procedure for replacing color data will now be described with reference to FIG.

First, in step S11, the input density values C, M, Y, and K of the target pixel are extracted from the image memory 2, and it is checked whether the input density values C, M, and Y match (step S12). . Then, the input density values C, M, Y
Are equal to each other, the replacement input densities C ′, M ′, Y ′, and K ′ are obtained in accordance with the following Expression 1 (step S1).
3).

[Equation 1] K '= K + C C' = 0 M '= 0 Y' = 0 Also, cyan (C), magenta (M), yellow (Y)
For pixels whose density values do not match, Equation 2 below
, The input density values C, M, Y, and K are directly output as replacement input densities C ′, M ′, Y ′, and K ′ (step S14).

[Equation 2] K ′ = K C ′ = C M ′ = M Y ′ = Y In this way, the color data replacement process is performed for one pixel of interest. The color data replacement process is performed for all pixels.

Next, based on the replacement input densities C ', M', Y ', and K' obtained as described above, binarization processing by an error diffusion method is performed to obtain pseudo halftone image data. Create

For example, first, for cyan (C '), 2 according to the error diffusion method according to the procedure shown in FIG.
A binarization process is performed on all pixels, and then a binarization process on all pixels for magenta (M ′) is performed.
Furthermore, a binarization process is performed for yellow (Y ′) and finally for black (K ′). Of course, the order of the binarization process for each color is not specified at all,
It can be done arbitrarily.

As described above, pseudo halftone color image data is created by binarizing the original image data and stored in the image memory 6.

Therefore, by applying image data stored as binary data to the image memory 6, for example,
By controlling a color inkjet printer having color (cyan, magenta, yellow, and black) heads, an area portion where the density values of C, M, and Y of the original image match is reproduced only by K. Therefore, it is possible to record a pseudo halftone color image with good gray reproducibility.

<Modification 1> In the above embodiment, before performing the binarization processing,
It is checked in advance whether all pixels have the same density value of cyan, magenta, and yellow. If there is a matching pixel, the density values of cyan, magenta, and yellow of the pixel are determined. Is replaced with black, and based on the replacement input density, binarization processing of any one color is performed over all pixels by an error diffusion method, and thereafter, the processing shifts to binarization processing of another color. However, the present invention is not limited to this. For example, the following procedure may be used.

First, a buffer allocated to a part of the RAM 3, that is, a binarized error sum storage for accumulating error values distributed to peripheral pixels for each pixel and storing the accumulated value as a "weighted error sum E". , Four buffers are prepared for each color.

Then, in the same manner as in the above embodiment, color data replacement processing is performed on all the pixels in advance, and two pixels of the pixel of interest are determined based on the density values of cyan, magenta, yellow, and black after replacement. The binarization process is performed for all colors, and then the process proceeds to the binarization process for the next pixel of interest.

<Modification 2> First, as in Modification 1, four buffers for storing binarized error sums are prepared for each color. Then, before performing binarization processing by focusing on each pixel of the original image data input to the image memory 2, it is checked whether or not the density values of cyan, magenta, and yellow of the pixel of interest match. If they match, the density values of cyan, magenta, and yellow are replaced with black, and the replacement input densities C ′, M ′, Y ′,
Based on K ′, binarization processing of cyan, magenta, yellow, and black is performed.

Then, paying attention to the next pixel, the processing shifts to color data replacement processing for determining whether or not the density values of cyan, magenta, and yellow match. After that processing, binarization processing is performed.

In the same manner, the color data replacement process and the binarization process are repeated for each pixel, and the process for all pixels is completed.

In the case of the second modification, the original image data input to the image memory 2 does not need to input all the pixels included in one screen at a time. Is also good.

<Modification 3> In the previous embodiment, the original image data input to the image memory 2 includes three primary color data of cyan (C), magenta (M), and yellow (Y), Although it is assumed that the data (K) is included, even if the data (K) is not included, for example, there is no problem.

In this case, step S1 shown in FIG.
2, the replacement input densities C ′, M ′, Y ′ in S13,
K ′ can be obtained by the following Expressions 3 and 4.

[Equation 3] K '= C C' = 0 M '= 0 Y' = 0 [Equation 4] K '= 0 C' = CM '= M Y' = Y

[0046]

As is apparent from the above description, according to the image processing apparatus and the image processing method of the present invention, gray reproducibility is good regardless of the binarization error distributed by the error diffusion method. Pseudo halftone color image data can be created.

[Brief description of the drawings]

FIG. 1 is a schematic configuration diagram of the present invention.

FIG. 2 is a flowchart illustrating a procedure of a color data replacement process according to an embodiment of the present invention.

FIG. 3 is a block circuit diagram illustrating a schematic configuration of an image processing apparatus.

FIG. 4 is a flowchart showing a procedure of a binarization process by an error diffusion method.

FIG. 5 is a diagram illustrating a method of distributing a binarized error in the error diffusion method.

[Explanation of symbols]

 2 Original image storage device (image memory) 3 RAM 4 ROM 5 CPU (color data replacement means, binarization processing means) 6 Output image storage device (image memory)

Continuation of the front page (58) Field surveyed (Int.Cl. ⁷ , DB name) H04N 1/40-1/409 H04N 1/46-1/64 G06T 5/00

Claims (5)

(57) [Claims] 1. An image processing apparatus for binarizing a color halftone image to generate pseudo halftone color image data, wherein if there is a pixel whose cyan, magenta, and yellow density values match, the cyan Data replacing means for replacing the density values of magenta and yellow with black, and binarizing processing means for performing a binarizing process by an error diffusion method based on the density values replaced by the color data replacing means. An image processing apparatus comprising: 2. The method of binarizing a color halftone image to generate a pseudo image
The image processing method odor <br/> to create a color image data between tone Te, before performing the binarization processing, a target advance for all the pixels, cyan, magenta, pixel density value of the yellow matches investigated whether, if there is a match to that pixel, the cyan pixels of that, magenta, replacing the density value of the yellow to black, the post-replacement cyan, magenta, each density value of the yellow and black Error diffusion
Image processing characterized by performing a binarization process by a method
How . 3. The image processing method according to claim 2 , wherein
Cyan location換後, magenta, on the basis of the density values of the yellow and black, is performed over the entire pixel binarization processing of one color, to migrate to the binarization processing of another color thereafter Characteristic image processing method . 4. The image processing method according to claim 2 , wherein
Characterized in that the original cyan location換後, magenta, each density value of the yellow and black, the binarization of the pixel of interest is performed over the entire color, then transition to the binarization processing of the next pixel of interest Image processing method . 5. A pseudo halftoning process for binarizing a color halftone image.
Image processing method for creating halftone color image data
Te, before the attention to binarization to each pixel, the cyan of the target pixel, magenta, checks whether the density value of the yellow match, if match if the target pixel
Of the cyan, magenta, and yellow are replaced with black, and a binarization process is performed by an error diffusion method based on the replaced density values of cyan, magenta, yellow, and black. An image processing method for checking whether or not the density values of cyan, magenta, and yellow match.