JPH09233329A - Dither matrix generating method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To suppress production of a noisy pattern due to a dither method by applying binarization processing to each pixel depending on a binarized state of a uniform density pixel matrix having already been binarized. SOLUTION: A microcomputer section 11 of a dither matrix generator 2 uses a CPU 12 to execute generation of a dither matrix based on a program stored in a program memory 13. In this case, each of plural density sets set discretely in a prescribed range set within a density range to be represented in pixels, the density is binarized to ON or OFF as an error spread method for each uniform density pixel matrix as each uniform density pixel matrix as the density of all pixels for each of plural uniform density pixel matrices. Depending on the binary state of the uniform density pixel matrix having already been binarized, each of the uniform density pixel matrix is binarized and the threshold level of each pixel is set based on the binarized density.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for creating a dither matrix for converting a multivalued image into a binary image.

[0002]

2. Description of the Related Art Data that constitutes an image is usually represented by a gray scale of about 8 bits. However, in a device that outputs this image data as an image that can be viewed by a person, such as an output device such as a printer, a dye such as ink is formed as a dot on a recording paper because of its simple mechanism and easy control. So-called binary recording, which is performed only with or without attachment, is general.

When an image represented by 8-bit gray scale is printed using such a binary printing output device, the value of each pixel is simply judged by a threshold value to attach ink. It will be decided whether or not. However, by simply binarizing with a threshold value in this way, the rich gray level of 8-bit gray levels (256 gray levels for one color and 3 primary colors for each 2 levels)
With 56 gradations, approximately 16.7 million colors can be represented. ) Becomes impossible to express. For this reason, a method of artificially expressing the light and shade state in such a binary recording output device has been considered. That is, the concept of area gradation is to express light and shade by the number of dots arranged in a predetermined area.

Various proposals have been made as methods for realizing this idea. For example, the error diffusion method, the random number generation type dither method, the systematic dither method, and the like.

[0005]

However, these methods have the following problems. That is, in the error diffusion method, the binarization process is delayed due to the error diffusion or the error distribution calculation, and a unique pattern is easily generated in the binarized image. Although the random number generation type dither method is fast because it uses a dither matrix, it has a problem that the image quality is very noisy, that is, the image quality is such that the image is filled with a lot of noise because it uses random numbers. It was.

As another method using the dither matrix, there is a spiral type of the systematic dither method. In this spiral type, dots are easily clustered and the clustered dots are recognized as large dots, resulting in poor resolution. It was easy to do. Among the systematic dither methods, there is a Bayer method. This Bayer method has good resolution because dots are dispersed, but it has a unique pattern and has poor gradation in dark areas. Met.

It is an object of the present invention to provide a method for producing a dither matrix which does not cause noise even if the dither method is used, does not deteriorate the resolution, and suppresses the generation of patterns.

[0008]

Means for Solving the Problems and Effects of the Invention According to the dither matrix creating method of the present invention, each of a plurality of density values discretely set within a predetermined range set within a density range that can be represented by a pixel. As a density value of all pixels in each of a plurality of uniform density pixel matrices, the density value is binarized to either ON or OFF by an error diffusion method for each uniform density pixel matrix, and
The threshold value of each pixel in the dither matrix is set based on the binarized density value to form the dither matrix.

As a method of setting the threshold value of each pixel in the dither matrix based on the binarized density value, for example, the binarized density value is set at the same position in all the uniform density pixel matrix. Are accumulated for each pixel of, and based on the accumulation result for each pixel at the same position,
Set the threshold for each pixel in the dither matrix.

When the image is binarized by the dither matrix with the threshold value set in this way, it does not become noisy to the human eye, the resolution does not deteriorate, and the binarized image in which the generation of the pattern is suppressed can be obtained. Can be generated. The binary sequence generated by the error diffusion method looks irregular at first glance, but is not totally random. That is, there is a property that it is difficult to form a pattern, but it is difficult to form a noisy image. As described above, the dither matrix creation method of the present invention uses the binary array generated by the error diffusion method to make the dither matrix also the two values in the error diffusion method.
It is created by taking in the nature of the sequence of values.

Therefore, in the dither matrix which enables high-speed binarization calculation processing, an appropriate threshold distribution which is irregular but not random is formed by the error diffusion method as described above. , Is not noisy to the human eye, and the resolution does not deteriorate,
Furthermore, it is considered that the binarized image in which the generation of the pattern was suppressed could be generated.

Further, in the dither matrix creating method of the present invention, each pixel of the uniform density pixel matrix is binarized according to the binarization state of the already binarized uniform density pixel matrix. Is characterized by. This "binarization processing performed according to the binarization state of the already binarized uniform density pixel matrix" means, for example, the binarization processing in the already binarized uniform density pixel matrix. There is a method of performing binarization processing according to the binarization state of the uniform density pixel matrix having the density closest to the uniform density pixel matrix to be attempted. That is, the binarization process of the uniform density pixel matrix by the error diffusion method is not executed at all independently, but the already binarized state in another uniform density pixel matrix is reflected.

By this reflection, as compared with the case where binarization is performed independently for each uniform density pixel matrix, the integration state at each pixel position is not biased to a specific value and is dispersed into various values. Therefore, in the dither matrix finally obtained based on such an integrated state, the threshold values are appropriately dispersed and distributed in a predetermined range.

That is, according to the present invention, even if the dither method is used, no noise is generated, the resolution is not deteriorated, and the dither matrix for suppressing the generation of the pattern can be formed, and in particular, each uniform density is obtained. It is possible to obtain a dither matrix in which the resolution is improved and the pattern is suppressed more than the dither matrix obtained when the pixel matrix is binarized independently.

More specifically, in the error diffusion method in which the density value i is the density value of all pixels in a uniform density pixel matrix, the density value less than the density value i and closest to the density value i is already binary. The same effect can be obtained by binarizing the same pixel position that is turned on in the lower binarized pixel matrix obtained by binarizing by always performing the error diffusion processing with turning on. it can. In this case, first, for a uniform density pixel matrix in which the minimum value min among a plurality of density values set discretely in a predetermined range is the density value of all pixels, the density value of each pixel is determined by the error diffusion method. It may be binarized to either ON or OFF, and then binarized to another density as the density value i.

In the error diffusion method using the uniform density pixel matrix in which the density value i is the density value of all pixels, the density value exceeding the density value i and closest to the density value i is already binarized. The above-described effect can be obtained by binarizing the pixel position that is the same as the pixel position that is off recently in the upper binarized pixel matrix obtained by performing the error diffusion process without fail. In this case, first, for a uniform density pixel matrix in which the maximum value max among a plurality of density values discretely set in a predetermined range is the density value of all pixels, the density value of each pixel is determined by the error diffusion method. It may be binarized to either ON or OFF, and then binarized to another density as the density value i.

In the error diffusion method using the uniform density pixel matrix in which the density value i is the density value of all pixels, the density value less than the density value i and closest to the density value i is already binarized. Is turned on in the latest lower binarized pixel matrix and turned on also in the latest upper binarized pixel matrix obtained by already binarizing the density value that exceeds the density value i and is closest to the density value i. The pixel position that is the same as the existing pixel position is always turned on, and the same pixel position that is turned off in the latest lower binarized pixel matrix and turned off in the latest upper binarized pixel matrix is always turned off and the error diffusion is performed. Binarization may be performed by processing, and the above-described effects can be obtained. In this case, first, the minimum value min among a plurality of density values set discretely in a predetermined range.
It is preferable to binarize the density value of each pixel to either ON or OFF by the error diffusion method for two uniform density pixel matrices having the maximum value max as the density value of all pixels.

Further, the density value i corresponds to a central integer value of the density values of the nearest lower binarized pixel matrix and the nearest upper binarized pixel matrix, or is set to an almost central integer value. Correspondence is preferable from the viewpoint of improving the resolution and suppressing the pattern of the pseudo-halftone image obtained by processing with the obtained dither matrix.

Further, the predetermined range may be equal to a density range that can be represented by a pixel. In this case, the predetermined range is, for example, a range of 0-255. This is particularly preferable when the data forming the image to be binarized is represented by 8-bit gray scale.

Further, in order to further improve the above-mentioned effect, the plurality of density values are incremented by one from a minimum value min to a maximum value max among the plurality of density values discretely set in a predetermined range. Max-m changed and set
It is preferably in + 1 values.

Further, the uniform density pixel matrix is
The row and column are both larger than the required dither matrix, and after binarization by the error diffusion method, the integration is performed on a specific region having the same size as the dither matrix, and based on the integration result,
A threshold value for each pixel in the dither matrix may be set. In this case, in particular, assuming that the specific area does not include the integration result of the first pixel line portion where the processing of the error diffusion method is started, the error diffusion at the initial stage of the error diffusion or the distortion of the error distribution is converted to the dither matrix. The influence is less likely to occur, and even if the image is binarized using the completed dither matrix, it is possible to further suppress the deviation of dots and the generation of patterns. Further, in this case, in order to eliminate the influence of the distortion as much as possible, the specific region is a line farthest from the first pixel line portion, and the final pixel line portion where the processing of the error diffusion method ends is integrated. It is preferable to include the results.

The accumulation result for each pixel at the same position is, for example, the number of one of the binarized density values in the pixel at the same position, and each of the dither matrixes corresponding to this number. Pixel thresholds can be set. For example, if a binary value is represented by "1" (on) and "0" (off), "1" (on) that exists at the same position in a plurality of binarized uniform density pixel matrices is used. It is possible to count and set the count value as it is, or by multiplying it by a coefficient, as a threshold value at the same position in the dither matrix. Further, the threshold value may be set from the count value based on a table. Instead of "1" (on), "0" (off) may be counted.

In addition to the above method, the threshold value can be set by
The density values are binarized when viewed from the uniform density pixel matrix having the minimum value min to the maximum value max of the plurality of density values discretely set in the predetermined range. For a pixel position that first appears as "1" (on) in the uniform density pixel matrix, a threshold value is set according to the density value of the uniform density pixel matrix that first becomes "1" (on). Also good. For example, each pixel position may be sequentially checked from the smallest density value, and the density value of the uniform density pixel matrix in which “1” (ON) first appears may be set as the threshold value as it is. Further, this density value may be multiplied by a predetermined coefficient to set it as a threshold value.

The threshold value is set to a binarized uniform density pixel matrix when the uniform density pixel matrix whose density value is the maximum value max to the uniform density pixel matrix whose density value is the minimum value min is viewed. A threshold value may be set according to the density value of the uniform density pixel matrix that first becomes “0” (off) for the pixel position that first appears as “0” (off). For example, each pixel position may be sequentially checked from the largest density value, and the density value of the uniform density pixel matrix in which “0” (OFF) first appears may be set as the threshold value as it is. Further, this density value may be multiplied by a predetermined coefficient to set it as a threshold value.

[0025]

BEST MODE FOR CARRYING OUT THE INVENTION

[First Embodiment] FIG. 1 is a main block diagram of a dither matrix creating apparatus 2. The microcomputer unit 11 forming the main body of the dither matrix creating apparatus 2 is C
Program memory 13 including PU 12 and ROM, RA
It is composed of a working memory 14 composed of M, a dither matrix storage memory 16 composed of RAM, and an output image memory 17 composed of RAM. An input unit 10 and an output unit 19 are connected to the microcomputer unit 11 via a system bus 18.

The input unit 10 is provided with an interface for inputting from a keyboard or an external storage device, and inputs data and instructions necessary for creating a dither matrix. Further, the input unit 10 inputs image data in which each pixel has a gradation represented by 8 bits in order to confirm the effect of the created dither matrix.

The CPU 12 executes the creation of a dither matrix as will be described later, and the program memory 13 stores programs for executing various controls performed by the CPU 12. The working memory 14 temporarily stores data required when the CPU 12 executes the program stored in the program memory 13.

The dither matrix storage memory 16 is C
The dither matrix data formed by the processing of the PU 12 is stored. The output image memory 17 is a CPU
12, the dither matrix stored in the dither matrix storage memory 16 is used to binarize the image data having the gradation represented by 8 bits, and the binarized output image data is stored.

The output unit 19 is a device for printing the binarized image data stored in the output image memory 17 by the electrophotographic method with or without dots. Next, the dither matrix creation processing executed by the dither matrix creation device 2 will be described. A flowchart of the dither matrix creation process is shown in FIG.

First, a uniform density pixel matrix in which all pixels have a density value i = 0 and a uniform density pixel matrix in which all pixels have a density value i = 255 are binarized by an error diffusion method (S80). This uniform density pixel matrix is
As shown in FIG. 4, two kinds of uniform density pixel matrices D0 and D255 in which i = 0 and 255 are stored in the working memory 1
It should be read in 4 and used. Then, the binarized pixel matrices F0 and F255 (FIG. 5) are stored in the working memory 14 (S90).

Here, the error diffusion method is used in a broad sense, and when a certain pixel is binarized, the binarization error is distributed to the densities of peripheral pixels which have not been binarized (narrow sense). Error Diffusion Method by Bibliography: Robert W. Floyd and Louis
Steinberg, "An Adaptive Algorithm for Spatial Gray
scale ", Proceeding of the SID Vol.17 / 2,1976
Etc.), or a method of receiving a predetermined ratio of the error generated in the binarization from the already-binarized pixels existing in the surroundings when the binarization is performed (also referred to as the average error minimum method.
Jarvis, CNJudice, and WHNinke, "A Survey of Techn
iques for the Display of Continuous Tone Pictures
on Bilevel Displays ", Computer Graphics and Image P
rocessing.5, 13-40 (1976)) and the like are well known, so a detailed description of the error diffusion method itself will be omitted. However,
The binarization result by the error diffusion method of the uniform density pixel matrix of the density value i = 0, 255 performed in step S80 shows that all pixels are “0” (hereinafter referred to as “off”) when i = 0. When i = 255, all pixels are “1” (hereinafter referred to as “on”). Therefore, the binary pixel matrix in which all pixels are off and all pixels are previously calculated without performing the error diffusion method. An on-state binary pixel matrix may be provided and these matrices may be used.

Next, the density value i is set to "1" (S10).
0), the binarization processing shown in FIG. 3 is executed on the uniform density pixel matrix in which all pixels have the density value i = 1 (S11).
0). As the uniform density pixel matrix, as shown in FIG. 4, 254 kinds of uniform density pixel matrices D1 to D254 of i = 1 to 254 may be read into the working memory 14 and used.

The binarization process of FIG. 3 will be described. First, among the density values that have been binarized, that is, among the density values for which the binarized pixel matrix has already been obtained, the uniform density pixel matrix that exceeds the density value i and is closest to the density value i is set to 2 The binarized pixel matrix that has been binarized (hereinafter, referred to as "the most recent upper binarized pixel matrix H") and the uniform density pixel matrix of the density value less than the density value i and closest to the density value i are binarized. The processed binarized pixel matrix (hereinafter referred to as the "most recently lower binarized pixel matrix L") is searched from the contents of the working memory 14 (S112). In the first embodiment, i = 1
From i to 254, the uppermost binarized pixel matrix H is always a binarized pixel matrix of i = 255, and the latest lower binarized pixel matrix L is i−1. It is a binarized pixel matrix.

Next, the uniform density pixel matrix having the density value i is binarized by the error diffusion method to create a binarized pixel matrix Fi (S116). However, it is binarized under the following conditions. Pixel positions in which both ON are arranged in both the most recently upper binarized pixel matrix H and the most recently lower binarized pixel matrix L are always turned ON.

Pixel positions in which both OFF are arranged in both the most recently upper binarized pixel matrix H and the most recently lower binarized pixel matrix L are always OFF. That is, normally, in the error diffusion method, a value obtained by summing the error distributed from peripheral pixels and the self density is compared with a threshold value, and if the value is equal to or larger than the threshold value, “ON”; Although it has been binarized to "off", in the case of a pixel that meets the above condition or, the pixel is not turned on and compared with the threshold value, and "on" according to the above condition.
Or set to “Off”. Of course, the result of the setting that is not compared with this threshold value is reflected in the binarization error and becomes the target of distribution to the peripheral pixels.

When the binarization of the uniform density pixel matrix of the density value i is completed, the binarized pixel matrix thus obtained is stored in the working memory 14 (S120), and whether or not the density value i = 254 is satisfied. Is determined (S
130). Since the density value i = 1 first (“NO” in S130), the density value i is then incremented (S
140). Therefore, the uniform density pixel matrix having the density value i = 2 for all pixels is binarized as described above (S110), and the binarized pixel matrix F2 is stored in the working memory 14 (S120).

Thereafter, the density value i is sequentially incremented (S140), the uniform density pixel matrix of the corresponding density value i is binarized (S110), and the binarized pixel matrix Fi is stored in the working memory 14. (S
120) Repeat the process. When the processing (S110, S120) of the uniform density pixel matrix of the density value i = 254 is completed, as shown in FIG. 5, the working memory 14 stores 256 binary pixel matrix F0 of the density values i = 0 to 255. To F255 are formed.

Next, since the density value i = 254 (S13)
If the value is 0, “YES”), the ON pixels at the same position are counted for all the binarized pixel matrices, and the integrated result matrix M1 having the count value as an element is formed (S150). That is, as shown in FIG. 5, assuming that the upper left corner is the origin (0, 0) and the horizontal direction is the x-axis and the vertical direction is the y-axis, first, all the binarized pixel matrices F0 to F2.
Count the number of "on" s for 55 (0,0). The count result is stored in the same position of the integrated result matrix M1 prepared in the working memory 14 as shown in FIG. This counting process is performed for each pixel position to fill the entire integration result matrix M1. In this counting process, if each pixel of the binarized pixel matrix is represented by "1" for ON and "0" for OFF, a count value is obtained by summing the values for each pixel.

Next, a threshold value for the dither matrix is set in order from the pixel position of the integrated result matrix M1 having a low count value (S160), and the matrix composed of the threshold value is stored in the dither matrix storage memory 16 as a dither matrix. (S170).

As a method of setting the threshold value, the count value itself may be set as the threshold value. In this case, since the count process of step S150 corresponds to the threshold setting process, no particular process is performed in step S160.
Then, the integrated result matrix M1 itself is used as a dither matrix, and the dither matrix storage memory 16
(S170).

In step S160, each count value of the accumulation result matrix M1 is not used as a threshold value as it is, but each count value of the accumulation result matrix M1 is determined according to a table of count values and threshold values prepared in advance. May be converted into a threshold value. In step S160, the threshold value is set to “0, 1, 2,
... "may be set, or conversely, the thresholds may be set to" 255, 254, 253, ... "in descending order of count value. In this case, the same count value is 2
When there are one or more, they may all be given the same threshold value, or the same count value may be ordered and different threshold values may be set.

When the halftone color image is binarized by using the dither matrix thus formed and recorded by a color printer, it is not noisy to the human eye and the resolution is high. It was possible to generate a pseudo-halftone binarized image in which pattern generation was suppressed without deterioration. Of course, the dither method does not perform many calculations unlike the error diffusion method, so that it can be processed quickly.

Further, as shown in FIG. 7A for explaining the ON / OFF setting state of each pixel position, once the pixel position is turned ON, the above condition is always satisfied in the subsequent density value i. , All on. When normal binarization that does not use the above conditions is performed, as shown in FIG. 7B, OFF appears at the same pixel position even after it is turned ON. Therefore, in the normal binarization, the number of ONs at each pixel position tends to be biased to a specific value within 0 to 255. However, in the first embodiment, various values in the range from 0 to 255 are set. Disperse into a suitable distribution. Therefore, the dither matrix thus obtained has a threshold value of 0 to 2 as well.
It will be appropriately dispersed and distributed in the range of 55. Therefore, in particular, as shown in FIG. 7B, compared with the dither matrix obtained when binarization is performed independently for each uniform density pixel matrix, improvement in resolution and suppression of pattern are further improved. A matrix can be obtained.

Incidentally, FIG. 9C shows an image of a part of the binarized pixel matrix in the case where the density value i = 128 binarized by the method of the first embodiment. Black dots represent on-pixels and white dots represent off-pixels. Similarly, FIG. 9D shows the case where the density value i = 192. FIG.
In (c) and (d), on / off dots are appropriately dispersed and distributed. Therefore, the threshold values obtained as a result are appropriately distributed in the range of 0 to 255.

In the first embodiment, the density value i is sequentially changed to i =
Since the binarization processing is performed while incrementing by 1 from 1, it is not necessary to use the above conditions in particular. Further, when the density value i is sequentially incremented by +1 in this way, the latest lower binarized pixel matrix L is simply referred to by referring to the latest lower binarized pixel matrix L without using the above condition. If the pixel position that is turned on is 2
It may be valued. In other words, when ON is turned on, it is always turned on in the subsequent binarization of the density value.
It may be valued.

In the first embodiment, i = 25
The binarization processing may be performed while sequentially decreasing the number from one by one. In this case, the above condition may be satisfied alone. Further, when the density value i is sequentially decreased by -1 in this way, the latest upper binarized pixel matrix H is simply referred to without referring to the latest upper binarized pixel matrix H.
The pixel position that is turned off in 2 may be binarized under the condition that it is always turned off. That is, when the off state appears, the binarization may be performed according to the rule that the density value is always turned off in the subsequent binarization of the density value.

Further, in the first embodiment or the modification described above, the change of the density value i is +1 or -1, but other than this, it may be increased or decreased by 2 or more. That is, the density value i
May be binarized for all the density values i, and the remaining density values i may be binarized for all the density values i. In this case, the above conditions are always used. By performing the processing in such a discrete manner, it is possible to suppress uneven distribution of threshold values having similar values.

[Embodiment 2] The difference between Embodiment 2 and Embodiment 1 is that the dither matrix creation processing is as shown in FIG. 8, and other configurations are the same as those of Embodiment 1. Same as 1. Further, in the flowchart of FIG. 8, steps S1080, S1090, S11
10, S1120, S1150, S1160, S117
0 indicates steps S80, S90, S11 of the first embodiment.
0, S120, S150, S160, and S170 are the same, so description thereof will be omitted.

The major difference from the first embodiment is that
This is the order of processing of the density value i to be digitized. First of all 1
A density value array is created for the 254 density values (S1
100), next, the density values i are read from the array one by one (S1105), and steps S1110 and S1120 are performed.
If the processing is completed and the processing is completed for all the density values of the array, it is determined in step S1130 that the array is completed,
The processes of steps S1150, S1160 and S1170 are performed.

The density value array in step S1100 is created such that the central density value of the binarized density values is set to i. That is, the head of the array is "128" which is the central integer value of "0" and "255".
(The other central integer value "127" may be used.),
Next is "64" and "12" at the center of "0" and "128".
The central "192" between 8 and 255 (the other central integer "191" may be used), and the next central "32" and "64" between "0" and "64". “96” in the middle of “128” and “128”, “160” in the middle of “128” and “192”, and “22” in the middle of “192” and “255”.
4 ”(the other central integer value“ 223 ”may be used), the central integer value of the previously obtained values is obtained, and the density values from“ 1 ”to“ 254 ”are obtained. Array "128, 64, 192, 32, 96, 160, 22
4, ... ”is created. This array may be calculated in advance and stored as array data, and only the array data may be read and used during this processing.

In step S1105, the density value i is sequentially set from the beginning of this array, and in step S111.
The binarization processing of 0 and the storage processing of the binarized pixel matrix of S1120 are performed, and step S111 is performed until the end of the array.
0, when the processing of S1120 is completed, step S113
It is determined to be "YES" at 0, and the process proceeds to threshold setting processing (S1150, S1160, S1170).

In the second embodiment, differently from the first embodiment, in order to sequentially binarize the central density i of the density values which have already been binarized, the nearest upper binarized pixel matrix is used. Recently, it is affected to the same extent by the respective binary dispersions with the lower binary pixel matrix, and the binary distribution of the binary pixel matrix of the central density i has a relatively uniform distribution. Since the dither matrix is created based on the binarized pixel matrix satisfying the uniform distribution and the conditions thus obtained, the effect of improving the resolution and suppressing the pattern is further increased.

In FIG. 9A, the method of the second embodiment is used.
A part of the binarized pixel matrix when the binarized density value i = 128 is shown as an image. Black dots represent on-pixels and white dots represent off-pixels. FIG.
Similarly, (b) is the case where the density value i = 192. FIG.
Compared to the case of the first embodiment shown in (c) and (d), it was further found that the on / off dots were dispersed appropriately, and the resolution was improved as compared with the first embodiment. It can be seen that the suppression of patterns and patterns is improved.

In the second embodiment, the array is created in advance so that the central value of the density value i is obtained in advance, but instead of creating the array in advance, the processing of step S1105 is performed. The central value may be sequentially calculated and set as the density value i. An example of obtaining the central value by calculation is shown in FIG.
Shown in This process is performed by step S1100 in FIG.
~ It is executed instead of S1130. In this processing, initially, eight variables I0 to I7 are initialized to "0" (S20).
10 to S2080), then sum I0 to I7,
The density value i is set (S2090). If the density value i is "0", I7 is increased by "128" (S212).
0), and then I7> 128 is not satisfied (“NO” in S2130), the density value i is calculated in the total processing of step S2090.
Is set to “128”, i = 0 (“NO” in S2100) and i = 255 (“NO” in S2110), so steps S1110 and S11
The process of 20 (the same as the process of FIG. 8) is performed. That is, the binarization process is performed on the uniform density pixel matrix with the density value i = 128 (S1110), and the result is 2
The binarized pixel matrix is stored (S1120).

Next, in the processing of step S2120, I7 =
In step S2130, it is determined to be "YES", I6 is increased by "64" (S2140), and I6
Since 6 = 64 and I6> 64 is not satisfied (S2150
"NO"), I7 = 0 is initialized in step S2080, and i = 64 in step S2090. Therefore, the process proceeds from steps S2100 and S2110 to steps S1110 and S1120, and the binarization processing is performed on the uniform density pixel matrix with the density value i = 64. Next, in step S2120, I7 = 128, and in step S2130 it is determined to be "NO". In step S2090, I0-I5 = 0, I6 = 64,
Since I7 = 128, i = 192, and after steps S2100 and S2110, the uniform density pixel matrix with the density value i = 192 is binarized.

Next, I0 to I5 = 0, I6 = 64, I7 =
Since it is 128, the process proceeds from step S2120 to step S2160, and I5 = 3 in step S2160.
It becomes 2. Since I5> 32 is not satisfied (in S2170, "N
O "), steps S2070 and S2080 are processed so that I0 to I4 = 0, I5 = 32, I6 = 0, I7 = 0.
Becomes Therefore, in step S2090, i = 32
Therefore, in steps S1110 and S1120, the density value i
= 32 uniform density pixel matrix is binarized.

Next, since I7 = 0, step S2
After 120 and S2130, the process returns to step S2090. At this time, I0 to I4 = 0, I5 = 32, I6 =
0 and I7 = 128. Therefore, step S20
At 90, i = 160, and steps S1110 and S1
At 120, the uniform density pixel matrix with the density value i = 160 is binarized.

Next, in steps S2120 to S2150,
After S2080 is processed, I0 to I4 = 0, I5 = 3
2, I6 = 64, I7 = 0. Therefore, i = 96 in step S2090, and step S111
0, S1120, the uniform density pixel matrix having the density value i = 96 is binarized.

Thereafter, depending on the values of I0 to I7, the density value i is sequentially changed to 224, 1 by one of the processes of steps S2020 to S2080 and S2120 to S2260.
, 144, 80, ..., 127 are set, and the density value i
Binarization and storage of the uniform density pixel matrix of
Finally, I0 = 1, I1 = 2, I2 = 4, I3 = 8, I
4 = 16, I5 = 32, I6 = 64, I7 = 128. At this time, the density value i = 25 in step S2090.
Since 5 is set, “YE
It is determined to be “S”, and the process proceeds to step S1150.
In this way, the uniform density pixel matrix can be binarized by tracing the central value even in the calculation.

In the second embodiment, the binarization processing is performed by tracing the central integer value. However, even if the central integer value is not completely, the position of 1: 2, the position of 1: 3, Position 1:
Although it is an intermediate value between two binarized density values such as a 3: 1 position, the binarization processing may be performed by tracing an integer value biased toward the small side or the large side.

[Third Embodiment] In the first and second embodiments, the integrated result matrix M1 and the dither matrix having the same size as the uniform density pixel matrix D0 to D255 or the binarized pixel matrix F0 to F255 thereof are used. Although it was formed, in the third embodiment,
As shown in FIG. 11, uniform density pixel matrices D0 to D0
D255 and its binary pixel matrix F0 to F2
The size of 55 is much larger than the integrated result matrix M1 and the dither matrix, and the binarized value in a specific region of the binarized pixel matrix F0 to F255 is used as the integrated result matrix M1. , Create a dither matrix.

The dither matrix creation processing according to the third embodiment will be described. Note that the dither matrix creation process is different from those of the first and second embodiments in step S1.
Since the processes of 10, S120 and S1110, S1120 are different and the others are the same, only the different parts are shown in FIG.
It is shown in FIG.

Step S100 or step S11
00, S1105, after setting the density value i, the density value i
The density (equal to the density value i) of the pixel of interest in the uniform density pixel matrix of is read (S210). The first pixel of interest is the pixel at the origin position (0,0).

Next, the value obtained by adding the binarization error distributed from the peripheral pixels to the density value i of the pixel of interest based on the above conditions is binarized by the error diffusion method (S220). That is,
If the condition is met, be sure to turn on 2 regardless of the threshold.
If the condition is met, binarization is always turned off irrespective of the threshold value, and otherwise, binarization is performed using a threshold value to obtain a binarization error.

Next, it is determined whether or not the current target pixel is included in the specific area A1 (S230). As shown in FIG. 11, the specific area A1 is an area in which the binarized value is counted in order to form the integration result matrix M1, and in the third embodiment, the same is applied to all uniform density pixel matrices. It is an area existing at the position of.

This specific area A1 does not include the first pixel line L0 portion in the error diffusion processing, but the last pixel line L0.
x part. This is because in the first pixel line L0, there is no previous line, and therefore, in the diffusion of the binarization error, a distortion is generated as compared with the subsequent line, and dot concentration and a specific pattern are likely to occur. This is because the influence of the distortion due to the binarization error diffusion decreases as the distance from the head pixel line L0 increases, and the influence is minimal in the final pixel line Lx.

When it is determined that the current target pixel is included in the specific area A1 ("YES" in S230), the binarized value of the target pixel is stored in the working memory 14 (S).
240). If it is determined that the current target pixel is not included in the specific area A1 (“NO” in S230), the binarized value of the target pixel is not stored.

Next, it is judged whether or not there is an unprocessed pixel in the density value i (S250), and if there is an unprocessed pixel ("YES" in S250), the process returns to step S210 again, and the unprocessed pixel is returned. The above processing is continued with the pixel of interest as.
The determination of unprocessed pixels in step S250 may be a determination of whether or not there are unprocessed pixels in the specific area A1.

After "NO" is determined in the step S250, the determination process of the step S130 or the step S1130 is performed. Therefore, when “YES” is determined in the step S130 or the step S1130, the working memory 14 stores in the working memory 14 the binarized pixel matrix corresponding to the specific area A1 for each density value i as in the case shown in FIG. F0 to F255 are formed.

All the binarized pixel matrices F0 to F0
The F255 is counted for each pixel at the same position to create the integrated result matrix M1 (S150, S115).
0). Next, a threshold value is set similarly to the first and second embodiments to form a dither matrix (S160, S1160),
It is saved in the dither matrix storage memory 16 (S17).
0, S1170).

The dither matrix obtained in the third embodiment was binarized into a halftone color image and recorded by a color printer.
The same effect as described above was obtained. Furthermore, from the uniform density pixel matrix, the binarized pixel matrix F0 to F255 of the specific area A1 that does not include the first pixel line L0 and that includes the final pixel line Lx is obtained, and from this binarized pixel matrix F0 to F255, Since the integration result matrix M1 smaller than the density pixel matrix is obtained and the dither matrix is formed based on this integration result matrix M1, the influence of the error distribution distortion occurring in the leading pixel line L0 portion is less likely to occur, It was possible to generate a pseudo-halftone binarized image in which the generation of patterns was suppressed.

[Others] In the first to third embodiments, among the binarized values at the same position, the number of ONs, that is, the number of pixels which become "1" by binarization is counted. , OFF, that is, the number of binarized pixels that have become “0” is counted, and an integrated result matrix M1 is created based on the counted value, and steps S160 and S11 are performed.
The processing of 60 may be executed to create the dither matrix.

The count value may not be used as it is as the accumulation result matrix M1, but may be multiplied by a predetermined coefficient. Further, for the binarized value Iixy of the uniform density pixel matrix of the density value i, a coefficient k (i) different for each density value i is set as in the following equation, and the total value Cxy of all uniform density pixel matrices is set. The obtained result matrix M1 may be created.

[0074]

[Equation 1]

Note that x and y represent pixel positions on the uniform density pixel matrix or the integration result matrix M1.
Binarization of uniform density pixel matrix is on ("1")
Alternatively, the binarization is off (“0”), but binarization of any value may be performed, and the number of any one of the values is counted to form the integrated result matrix M1. It suffices to convert M1 into a dither matrix. Further, instead of counting the number as described above, the sum of the binarized values may be used.

In the third embodiment, the specific area A1 for storing the binarized value is at the same position in all uniform density pixel matrices, but it may be different depending on the uniform density pixel matrix. This is because the degree of the backward influence of the distortion of the error diffusion occurring in the head pixel line L0 differs depending on the density value i forming the uniform density pixel matrix.

Since the degree of the influence of the distortion of the error diffusion occurring in the head pixel line L0 portion on the rear is different depending on the density value i as described above, all the uniform density pixel matrices are binarized. In order to eliminate the influence of the error diffusion distortion, the size of the uniform density pixel matrix is set to the density value i.
You may adjust according to the value of.

Steps S80, S110, S1080,
When the binarization processing is performed by the error diffusion method in S1110 and S220, all the pixels in each uniform density pixel matrix have the same density value i except that 256 kinds of uniform density pixel matrices are arranged. When i is used for calculation in the error diffusion method, all can be treated as the density value i. Therefore, 256 from i = 0 to 255 can be used.
Only individual values may be stored. Further, the step value Sp for determining the lower limit value “0” of the density value i, the upper limit value “255”, and the value of the density value i discretely existing between the lower limit value and the upper limit value (processed Value indicating the interval of the density value i, Sp = 1 in the first to third embodiments).

[Brief description of drawings]

FIG. 1 is a main block diagram of a dither matrix creation device according to a first embodiment.

FIG. 2 is a flowchart of a dither matrix creation process according to the first embodiment.

FIG. 3 is a flowchart of binarization processing according to the first embodiment.

FIG. 4 is an explanatory diagram showing uniform density value image data according to the first embodiment.

FIG. 5 is an explanatory diagram showing a state in which uniform density value image data according to the first embodiment is binarized.

FIG. 6 is an explanatory diagram of an accumulation result matrix according to the first embodiment.

FIG. 7 is an explanatory diagram of an on / off setting state of each pixel position.

FIG. 8 is a flowchart of a dither matrix creation process according to the second embodiment.

FIG. 9 is an explanatory diagram showing an image of the binarized pixel matrix obtained in the first and second embodiments.

FIG. 10 is a flowchart showing another example of a method for determining the processing order of a uniform density pixel matrix.

FIG. 11 is an explanatory diagram showing a relationship between a uniform density pixel matrix and a specific region according to the third embodiment.

FIG. 12 is a flowchart showing a part of dither matrix creation processing according to the third embodiment.

[Explanation of symbols]

2 ... Dither matrix creation device 10 ... Input unit 11 ... Microcomputer unit 12 ... CPU 13 ... Program memory 14 ... Working memory 16 ... Dither matrix storage memory 17 ... Output image memory 18 ... System bus
19 ... Output section

Claims (21)

[Claims] 1. A plurality of density values discretely set in a predetermined range set within a density range that can be represented by a pixel are set as density values of all pixels in each of a plurality of uniform density pixel matrices. , The uniform density pixel matrix is binarized by turning on / off the density value by an error diffusion method, and the threshold value of each pixel in the dither matrix is set based on the binarized density value. A method of creating a dither matrix, wherein each pixel of the uniform density pixel matrix is binarized according to a binarized state of the already binarized uniform density pixel matrix. How to create a dither matrix. 2. The binarized density values are integrated for each pixel at the same position for all of the uniform density pixel matrix, and based on the integration result for each pixel at the same position,
2. The dither matrix creating method according to claim 1, wherein a threshold value for each pixel in the dither matrix is set. 3. A binarization state of a uniform density pixel matrix having a density closest to the uniform density pixel matrix to be binarized in the already binarized uniform density pixel matrix. The dither matrix creation method according to claim 1, wherein the dither matrix is binarized. 4. In an error diffusion method using a uniform density pixel matrix in which the density value i is the density value of all pixels, the density value less than the density value i and closest to the density value i is already 2
4. The binarization is performed by always performing an error diffusion process on a pixel position that is the same as a pixel position that is turned on in the latest lower binarized pixel matrix obtained by binarization. How to create the dither matrix described. 5. First, a uniform density pixel matrix in which the minimum value min among a plurality of density values set discretely in the predetermined range is the density value of all pixels is determined by an error diffusion method for each pixel. 5. The dither matrix creating method according to claim 4, wherein the density value is binarized to either ON or OFF, and then another density is binarized as the density value i. 6. In an error diffusion method using a uniform density pixel matrix in which the density value i is the density value of all pixels, the density value exceeding the density value i and closest to the density value i is already binarized. The pixel position that is the same as the pixel position that is off recently in the upper binarized pixel matrix obtained by
4. The dither matrix creating method according to claim 3, wherein the binarization is performed by always performing an error diffusion process with turning off. 7. First, for a uniform density pixel matrix in which the maximum value max among a plurality of density values discretely set in the predetermined range is the density value of all pixels, an error diffusion method is applied to each pixel. 7. The dither matrix creating method according to claim 6, wherein the density value is binarized to either ON or OFF, and then another density is binarized as the density value i. 8. In an error diffusion method using a uniform density pixel matrix in which the density value i is the density value of all pixels, the density value less than the density value i and closest to the density value i is already 2.
In the most recent lower binarized pixel matrix that is on and has already been binarized for the density value that is on and is closest to the density value i in the most recently binarized pixel matrix obtained by binarization. The same pixel position that is also turned on must be turned on, and
4. The binarization is performed by always performing the error diffusion process with the pixel position that is off in the binarized pixel matrix and the same pixel position that is also off in the uppermost binarized pixel matrix being always off. How to create the dither matrix described. 9. First, error diffusion is performed on two uniform density pixel matrices in which the minimum value min and the maximum value max among a plurality of density values discretely set in the predetermined range are the density values of all pixels. 9. The density value of each pixel is binarized to either ON or OFF by the method, and then the other density is binarized as the density value i.
How to create the dither matrix described. 10. The density value i corresponds to an integer value at the center of the density values of the nearest lower binarized pixel matrix and the nearest upper binarized pixel matrix. 9. The dither matrix creation method described in 9. 11. The density value i corresponds to an integer value at the center of the density values of the nearest lower binarized pixel matrix and the nearest upper binarized pixel matrix. Alternatively, the dither matrix creation method described in 9 above. 12. The dither matrix creating method according to claim 1, wherein the predetermined range is equal to a density range that can be represented in the pixel. 13. The dither matrix creation method according to claim 1, wherein the density range that can be represented by the pixel is a range of 0 to 255. 14. A plurality of density values discretely set in the predetermined range have a minimum value min to a maximum value ma among a plurality of density values discretely set in the predetermined range.
14. The dither matrix creation method according to claim 1, wherein the values are max-min + 1 values which are set by changing one by one up to x. 15. The dither matrix creation method according to claim 1, wherein the uniform density pixel matrix is a matrix having a larger number of pixels than a required dither matrix. 16. The uniform density pixel matrix is a matrix in which both rows and columns are larger than a required dither matrix, and after binarization by the error diffusion method, the integration is performed on a specific area having the same size as the dither matrix. 16. The dither matrix creation method according to claim 15, wherein the threshold value of each pixel in the dither matrix is set based on the integration result. 17. The dither matrix creating method according to claim 16, wherein the specific area does not include a result of integration of a first pixel line portion where the processing of the error diffusion method is started. 18. The dither matrix creating method according to claim 16, wherein the specific region includes an integration result of a final pixel line portion where the processing of the error diffusion method is completed. 19. The accumulation result for each pixel at the same position is 2
19. The dither matrix creation method according to claim 1, wherein the threshold value of each pixel of the dither matrix is set according to the number of one of the binarized density values. Method. 20. Instead of setting the threshold value based on the accumulation result, a uniform density pixel matrix in which the density value is the minimum value min among a plurality of density values discretely set in the predetermined range. When the uniform density pixel matrix having the maximum value max is viewed, the density of the first uniform density pixel matrix turned on for the pixel position first turned on in the binarized uniform density pixel matrix. 19. The dither matrix creating method according to claim 1, wherein the threshold value is set according to the value. 21. Instead of setting the threshold value based on the accumulation result, from a uniform density pixel matrix in which the density value is the maximum value max among a plurality of density values discretely set in the predetermined range. When the uniform density pixel matrix having the minimum value min is also viewed, the density of the uniform density pixel matrix that is first turned off with respect to the pixel position that first appears off in the binarized uniform density pixel matrix. 19. The dither matrix creating method according to claim 1, wherein the threshold value is set according to the value.