JPH0556264A - Image information processing method - Google Patents

Abstract

PURPOSE:To obtain an excellent image having a faithful gradation reproducibility without using a threshold table by binarizing an input value from an input picture element with the threshold, dividing the error of the input value and the threshold at the prescribed rate, and storing and adding to the subrequest input values. CONSTITUTION:When multi-value image information is reproduced by an output device to perform the binary output, a matrix (reading value matrix) 5 of an object value is prepared through an A/D converter for the reading value of an input picture element 7 of a color image 4. An element dij of the matrix 5 is binarized by comparing a threshold T with a comparator. An error (e) of the input value to occur at the time of binarization and the threshold T is divided into the error added portions of the size in proportion to the coefficient of the partial matrix of a coefficient matrix 2, and by an arithmetic unit, they are added to the element dij of an object value 5 of other input picture element to distribute fixedly at the position of the input picture element 7.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION The present invention provides a multilevel grayscale image.
The present invention relates to a binarization method, and more particularly to a binarization processing method for reproducing a digital multi-value grayscale image read by a scanner by an output device capable of binary output.

[0002]

2. Description of the Related Art Generally, in the field of image processing, a systematic dither method and an error diffusion method are known as methods for binarizing a multi-valued image to reproduce a gradation.

In the systematic dither method, one pixel of an input signal read from a document of a multi-valued image is made to correspond to one pixel of binary recording, and the periodicity in which the input signal is fixedly made to correspond to the position of the input pixel. Compare with the threshold table you have, and "output",
This is a binarization method that determines "no output".

In the error diffusion method, an error generated when binarizing an input signal of one pixel of an input multi-valued image is determined according to the coefficient size of a coefficient matrix which is relatively fixed at an error occurrence point. This is a binarization method that is dispersedly added to surrounding input pixels.

On the other hand, in the field of printing, a film original is used as an input medium, and color separation is performed to form periodic halftone dots on a black and white film by an optical method using a contact screen, and the film is printed. A method is known in which a plate is made and the image is reproduced as a halftone image. In the case of a halftone dot image, the size of the halftone dot expresses the density of the image. Further, in the case of color printing, there is known a method in which the contact screen is rotated at different angles for each color to reduce the occurrence of moire and color difference due to misregistration for each color.

Further, a method of forming a halftone dot by an electronic method without using an optical screen has also been developed, and has been installed in a recent printing scanner or plotter system.

[0007]

However, the dither method is not always sufficient in terms of faithful gradation reproducibility due to the occurrence of a peculiar pattern related to the structure of the threshold table, and moiré and color difference due to misregistration may occur. Occur.

In the error diffusion method, a striped pattern peculiar to the processed image appears, and there is still a point to be solved in terms of image quality, and there is a problem in faithful gradation reproducibility.

In order to solve these problems, when a read value of an input pixel of an image or a target value obtained by adding an error addition amount to the read value is binarized by comparison with a threshold value, the target value and the threshold value The difference between and is divided into error additions of a size proportional to the coefficient in the submatrix of the coefficient matrix that has a periodicity in the one-dimensional or two-dimensional direction, which consists of elements that fixedly correspond to the position of the input pixel. A method of adding to the target value of another input pixel that is fixedly distributed corresponding to the position of the input pixel is disclosed in Japanese Patent Application No. 2-250944 (filed on Sep. 20, 1990) and Japanese Patent Application No. 3-42716 (1993). Filed on February 14, 2012).

However, in a flat mesh portion in which target values of the same degree are continuous, low-frequency shading unevenness may occur depending on the size of the target values and the rotation angle of the coefficient matrix.

The present invention is a method which has faithful gradation reproducibility, does not use a threshold value table, and can obtain an image of excellent image quality with little density unevenness even in a flat halftone portion.

[0012]

To solve this problem, the image information processing method according to the first aspect of the present invention uses an image input method when reproducing multivalued image information with an output device capable of binary output. When the read value of the pixel or the target value obtained by adding the error addition to the read value is binarized by comparison with the threshold value, the difference between the target value and the threshold value is fixedly corresponded to the position of the input pixel. The element is divided into the above-described error addition amount having a size proportional to the coefficient of the submatrix of the coefficient matrix having one-dimensional or two-dimensional periodicity, and fixedly distributed corresponding to the position of the input pixel. In the image information processing method of adding to the target value of another input pixel, the content of the element of the coefficient matrix is determined by a function having the one period as a domain.

Further, according to the image information processing method of the second invention, when the multivalued image information is reproduced by the output device capable of binary output, the read value of the input pixel of the image or the error addition to the read value. When a target value added with minutes is binarized by comparison with a threshold value, the difference between the target value and the threshold value is a one-dimensional or two-dimensional cycle composed of elements that fixedly correspond to the position of the input pixel. The target value obtained by adding the product of the coefficient of the second coefficient matrix obtained by calculation from the coefficient matrix having the property and the value of the element of the error value matrix for the surrounding error, is binarized by comparison with a threshold value, In the image information processing method of storing the difference between the target value and the threshold value as the value of the element of the error value matrix at a position corresponding to the position of the input pixel of the error value matrix, the content of the element of the first coefficient matrix is set to 1 Determined by a function whose halftone dot period is the domain It is characterized in that. The first
And the second invention are the same method in principle,
The timing of adding the error to the read value is different.

Further, in the image information processing method of the third invention, when the one cycle is n × n, the value of the coefficient a _{i, j} corresponding to the target value in the i-th row and the j-th column of the input image is the above-mentioned function. Formula 3 below

[0015]

[Equation 3]

It is characterized in that it is determined by the function value of

Further, in the image information processing method of the fourth invention, when the one cycle is n × n, the value of the coefficient a _{i, j} corresponding to the target value in the i-th row and the j-th column of the input image is the above-mentioned function. Formula 4 below

[0018]

[Equation 4]

It is characterized in that it is determined by the function value.

In the image information processing method of the fifth invention _, the coordinates (i, j) of the target value d _{i, j} are rotated (i ',
It is characterized in that the function value g (i ′, j ′) obtained by substituting it into the above function as j ′) is the coefficient at the coordinate (i, j).

The image information processing method of the sixth invention is characterized in that the value of the coefficient matrix or the second coefficient matrix previously obtained by using the function is stored in the storage device.

[0022]

First, the coefficient matrix is prepared. Each element of the coefficient matrix fixedly corresponds to the position of the input pixel of the image, and the magnitude of the coefficient value has a one-dimensional or two-dimensional cycle. Then, a p-by-q-column submatrix is assumed in the coefficient matrix.

However, p and q each independently take an integer of 2 to 5.

The input value from the input pixel is binarized by the threshold value, and the error between the input value and the threshold value generated at this time is divided at a predetermined ratio and accumulated and added to the input values from the next and subsequent input pixels. The predetermined ratio at this time is determined in proportion to the coefficient of the element of the partial matrix of the coefficient matrix that fixedly corresponds to the input pixel, and the content of the element of the coefficient matrix defines the size of the one cycle. It is obtained from the function that is the range

Alternatively, the input value from the input pixel is binarized by the threshold value, and the error between the input value and the threshold value generated at this time is stored as an error as an element of an error value matrix positionalally corresponding to the input pixel, When processing subsequent input pixels, the input coefficient is multiplied by a predetermined coefficient and added to the input value. The predetermined coefficient at this time is determined by the element of the second coefficient matrix obtained from the coefficient matrix. The contents of the elements of the matrix are obtained from a function whose domain is the size of the one cycle.

By performing such an operation by scanning all the pixels of the image, a binary image of the image can be obtained.
The coordinates of the input pixel are (i, j) when a monochrome image to be superimposed is reproduced for each color as in color printing.
Rotate at different rotation angles for each color (i ',
j ′) is obtained and (i ′, j ′) is substituted into the function instead of (i, j) to perform the above process.

[0027]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The details of the present invention will be described below with reference to the drawings showing one embodiment.

First, the first and third inventions will be described.

FIG. 2 is a diagram showing a process of image processing of the first invention.

In FIG. 1, reference numeral 2 denotes a coefficient matrix, and the coefficient matrix 2 is a coefficient matrix having a period of length n in the U-axis direction and length n in the V-axis direction, which is two-dimensional. One cycle includes n × n coefficients of a _1,1 , ..., A _{n, n} , and the element value is determined by Expression 3. The elements of the coefficient matrix 2 are the positions of the input pixels 7 of the multivalued image 4 (FIG. 2) which is the original,
And fixedly correspond to the position of the element of the matrix 5 of the target value.

That is, in FIG. 3, 2 is a coefficient matrix, 3 is a partial matrix of the coefficient matrix 2 with p rows and q columns, and the elements a _{i, j} of the coefficient matrix 2 are input multi-valued color images 4 Correspondingly corresponds to the element d _{i, j} of the matrix 5 of the target value of, and the coefficient matrix 2 has periodicity, so the value of a _{i, j} is a
_{imod n, j} equal to the value of _{mod n} . For example when the period n = 3, the value of the _{a 11, 8 = a 11 mod} 3, 8 mod 3 = because it is a _{2, 2} a _{2, 2} and a _11,8 are equal. The element d _{i, j} of the target value matrix 5 fixedly corresponds to the position of the input pixel 7 of the color image 4 (FIG. 2). Here, element d of matrix 5
_The target value indicated by _{i, j} is a read value obtained by reading the input pixel 7 of the image 4 or a value obtained by sequentially adding an error addition amount described below to the read value.

If U is the main scanning direction of processing and V is the sub scanning direction, for example _, the value of d _{i, j} is compared with a certain threshold value T and 2
When binarized, if d _{i, j} > T, the binarized signal becomes “output”, an error of e = d _{i, j} −T occurs, and d
_{When i, j} <T, the binarized signal is “not output”,
An error of e = d _{i, j} occurs.

This error e is calculated as p of coefficient matrix 2 containing a _{i, j}
A coefficient a is assigned to each element of the p-row q-column submatrix 6 of the target value matrix 5 of the input pixels corresponding to the range of the row q-column submatrix 3.
_{w, z} (however, w is changed by taking each natural number from i to i + p−1, and z is a natural number α of q or less for each w
Is set and the natural numbers from j-α + 1 to j-α + q are changed, and a _{i, k} where k ≦ j is excluded) is dispersed in proportion to and added to the target value of the input pixel. To do.

A binary image is obtained by performing this processing on the entire input pixels in the order of main scanning and sub-scanning.

There is no particular relationship between p, q and n.

Next, as an example, a process of diffusing an error by the above process will be shown in the drawings. However, the present invention is not limited by the size and numerical values of the matrix used in this description. In FIG. 4, reference numeral 5 is a matrix of the target values of the input multi-valued image, which is a matrix of the read values of the pixels of the image before the error is added as each element, and reference numeral 10 indicates the location where the error occurs. Show. Reference numeral 2 in FIG. 5 is one cycle of the coefficient matrix of 5 rows and 5 columns, and is an example in which ρ = 2.0 in Expression 3.

For example, the value of the element of the element a _2,5 is _calculated as 4 as shown in the following mathematical expression 5.

[0038]

[Equation 5]

The partial matrix 3 is 2 × 2 as shown in FIG. When the range of the input pixel value is 0 to 100 and the threshold value is 100, the value of d _{1,1 in} the target value matrix 5 is 42.
And it is smaller than the threshold value, so the binary signal is not output.
And 42 becomes an error, and the size of the submatrix is 2 × 2
_Therefore , the matrix elements d _1,2 , d _2,1 and d _2,2 of the input pixels corresponding to the error diffusion ranges a _1,2 , a _2,1 and a _2,2 are e _1,2 respectively. = 10 (= 42 × 8 / (8 + 8 + 1
6)), e _2,1 = 10 (= 42 × 8 / (8 + 8 + 1)
6)), e _2,2 = 21 (= 42 × 16 / (8 + 8 + 1)
6)) is added, and as a result, the matrix 5 of the target values of the input multi-valued image becomes as shown in FIG. 7. Since the value of the input pixel d _1,2 which is the next processing target is 109, which is larger than the threshold value, the binarized signal “outputs” and 9 becomes an error, and the size of the partial matrix is 2 × 2 _Therefore , the error diffusion range a _1,3 ,
input elements d _1,3 , d _2,2 corresponding to a _2,2 , a _2,3 ,
New error divisions for d _2,3 e _1,3 = 1 (= 9 ×
8 / (8 + 16 + 16)), e _2,2 = 3 (= 9 × 16 /
(8 + 16 + 16)), e _2,3 = 3 (= 9 × 16 / (8
+ 16 + 16)) is added, so that the matrix of input multi-valued image readings is shown in FIG.

The same processing is performed for all the input pixels in the order of main scanning and sub-scanning, and the processing for one frame is completed.

By this image information processing, it is possible to perform binarization similar to the conventional halftone dot.

Next, the fourth invention will be described.

FIG. 9 shows one cycle of the coefficient matrix of 5 rows and 5 columns.
This is an example in which ρ = 2.0 in Expression 2. For example, element a
The values of _2,5 are obtained as 1 as shown in the following formula 6.

[0044]

[Equation 6]

By using this coefficient matrix and performing the same image processing as in the description of the first and third inventions, it is possible to perform binarization similar to the conventional halftone dot.

Next, the second invention will be described.

FIG. 10 is a diagram showing a process of image processing of the second invention.

In FIG. 1, reference numeral 2 indicates a coefficient matrix, and the coefficient matrix 2 is a coefficient matrix having a period of length n in the U-axis direction and length n in the V-axis direction and is two-dimensional. _.. , a _{n, n} coefficients are included in one cycle, and the element value is determined by, for example, Expression 3, but Expression 4 may be used. The elements of the coefficient matrix 2 are the positions of the input pixels 7 of the multivalued image 4 (FIG. 10) which is the original, and the matrix 5 of the target values.
Corresponding fixedly to the position of the element of.

That is, in FIG. 11, 2 is a coefficient matrix, 3 is a partial matrix of the coefficient matrix 2 with p rows and q columns,
The element a _{i, j} of the coefficient matrix 2 corresponds in position to the element d _{i, j} of the read value matrix 5 of the input multi-valued color image 4, and the coefficient matrix 2 has periodicity. The value of _{i, j} is equal to the value of a _{i mod n, j mod n} . For example when the period _{n = 3, a 11, 8} = a 11 mod 3, 8 mod 3 = a 2,2
_Therefore , the values of a _2,2 and a _11,8 are equal.

Next, the error value matrix will be described. Figure 10
The error value matrix 10 shown in FIG. 2 is a matrix having an error that is the difference between the read value of the binarization process and the threshold value as an element, and the error value matrix 1
The element e _{i, j} of 0 fixedly corresponds to the position of the input pixel 7 of the image 4 and the element d _{i, j} of the read value matrix.

Next, in order to obtain the second coefficient matrix 9 shown in FIG. 10, U is the main scanning direction of processing, V is the sub scanning direction, and
The element c _{i, j} of the second coefficient matrix is obtained by the following Equation 7.

[0052]

[Equation 7]

To obtain the target value, the value obtained by the following equation 8 is added to the read value d _{s, t} to be processed to obtain the target value.

[0054]

[Equation 8] The element d _{i, j} of the read value matrix 5 fixedly corresponds to the position of the input pixel 7 of the image 4.

When the error value matrix 10 is calculated, U is the main scanning direction of the process, V is the sub scanning direction, and the target value is compared with a certain threshold value T and binarized. If the target value> T when binarized by comparing with the threshold value T,
The binarized signal becomes “output”, an error of target value −T occurs, and when the target value <T, the binarized signal “does not output”.
Then, the target value becomes an error value, and these error values are stored as the element e _{s, t} of the error value matrix 10 with respect to the element d _{s, t} of the reading value matrix which is the processing target.

A binary image is obtained by performing this processing on the entire input pixels in the order of main scanning and sub-scanning.

There is no particular relationship between p, q and n.

Next, as an example, the addition of the above errors is shown in the figure. However, the scope of the claims is not limited by the size and numerical values of the matrix used in this description. 12
5 is a matrix of read values of an input multi-valued image, which is a matrix of read values of pixels of an image before an error is added as each element, and a reference numeral 11 indicates a portion where an error occurs. Reference numeral 2 in FIG. 5 is one cycle of the coefficient matrix of 5 rows and 5 columns, and is an example in which ρ = 2.0 in Expression 1 as an example. The partial matrix 3 is 2 × 2 as shown in FIG. In this case, in Expression 7, p = q = 2 and α = 0. Figure 1
Let 10 of 4 be the error value matrix. Assuming that the range of the input pixel value is 0 to 100 and the threshold value is 100, FIG.
Of the read value matrix 5 of d _3,4
The value of is 45, and the second coefficient matrix 9 shown in FIG. 13 is created from the coefficient matrix 2 of FIG.

{8 / (8 + 16 + 8)} × 70 + {8 /
(4 + 8 + 4)] × 85 + {8 / (8 + 8 + 4)} × 1
0 = 60.25 ...

Therefore, the target value is 45 + 60 = 105, and since it is larger than the threshold value, the binarized signal becomes “output”, 5 becomes an error, and is stored in the error value matrix. The error value matrix is shown in FIG. It becomes the matrix 10 shown.

The same processing is performed for all the input pixels in the order of main scanning and sub-scanning, and the processing for one frame is completed.

With this coefficient matrix, it is possible to perform binarization similar to the conventional halftone dot.

Next, the fifth invention will be described. The coordinate value (i, j) of the element d _{i, j} of the reading value matrix is calculated by the following formula.

I ′ = “i · cos (A) −j · sin (A)” mod n. j ′ = “i · sin (A) + j · cos (A)” mod n. ("" Represents rounding processing here)

The rotation is performed using to obtain (i ', j'), and the function value g (i ', j') of the above function is set as the value of the coefficient matrix corresponding to the position of d _{i, j} . It is possible to obtain a rotated binarized image by performing the processing according to the third, third, or the first and fourth aspects of the invention, and to reduce moire and color difference caused by misregistration at the time of output. ..

It is also possible to obtain the same result by obtaining the second coefficient matrix from this coefficient matrix and performing the processing according to the second invention.

Next, the sixth invention will be described.

The coefficient matrix obtained by the same method as that of the fifth invention or the second coefficient matrix may be stored in advance in the storage device prior to binarization to speed up the processing. It is possible.

When the second coefficient matrix is stored, a four-dimensional matrix 2d of n × n × p × q as shown conceptually in FIG. 16 is prepared in the storage device, and its element is assumed to be h. , The following formula 9

[0070]

[Equation 9]

Let be the element content of h _{s, t, s-i + 1, t-j + 1 ,} and be a coefficient by which the error value e _{i, j} is multiplied when processing the read value d _{s, t} of the image.

In particular, tan θ = δ / γ becomes a rational number,
By selecting an angle θ such that Expression 10 below is an integer or close to an integer, the number of elements on one side is Expression 11 below, a repeatable coefficient matrix after rotation, or a second
A coefficient matrix can be constructed, and the size of the area occupied on the storage device can be reduced.

[0073]

[Equation 10]

[0074]

[Equation 11]

In FIG. 17, 2c is n × n of the coefficient matrix.
2d is a coefficient matrix whose elements are function values obtained by rotating the coordinates at an angle θ such that tan θ = 3/4 and substituting into the function. Is the number of elements on one side and can be repeated vertically and horizontally.

[0076]

[Equation 12]

The above method will be described in detail with reference to experimental examples, but the present invention is not limited to the numbers described in the experimental examples.

(Experimental Example-1) In Equation 3, ρ = 2.0,
Using one cycle of the coefficient matrix as shown in FIG. 18 in which the cycle of the coefficient matrix is n = 5, the threshold value is set to T = 255, and the rotation angle A is selected so that tan (A) = 7/24. The size of the matrix was set to p = q = 3, and the image information processing of the first, third, and fifth inventions was performed on the read-out matrix of the halftone dot density of 30%, and the results shown in FIG. 19 were obtained.

On the other hand, based on the method of the invention of Japanese Patent Application No. 3-42716, one unit of the 5 × 5 coefficient matrix shown in FIG. 20 is used, the threshold value is set to 255, and the rotation angle A is set to tan (A) = 7.
/ 24, and the size of the submatrix is p = q =
3 and the 30% density flat screen reading matrix
Image information processing of the third and fifth inventions was performed, and the results shown in FIG. 21 were obtained.

FIG. 22 stereoscopically shows one cycle of the coefficient matrix shown in FIG. 20, and one cycle of the coefficient matrix shown in FIG. 18 corresponds to FIG. The result shown in FIG. 19 has less unevenness in density than the result shown in FIG.

(Experimental Example-2) In Equation 4, ρ = 2.0,
Using one cycle of the coefficient matrix as shown in FIG. 23 in which the cycle of the coefficient matrix is n = 5, the threshold value is set to T = 255, and the rotation angle A is selected so that tan (A) = 7/24. The size of the matrix was set to p = q = 3, and the image information processing of the second, fourth, and fifth inventions was performed on the read-out matrix of the halftone dot density of 30%, and the results shown in FIG. 24 were obtained.

On the other hand, based on the method of the invention of Japanese Patent Application No. 3-42716, one unit of the 5 × 5 coefficient matrix shown in FIG. 25 is used, the threshold is set to 255, and the rotation angle A is tan (A) = 7.
/ 24, and the size of the submatrix is p = q =
3 and the 30% density flat screen reading matrix
The image information processing of the third and fifth inventions was performed, and the results shown in FIG. 26 were obtained.

FIG. 27 stereoscopically shows one cycle of the coefficient matrix shown in FIG. 25, and one cycle of the coefficient matrix shown in FIG. 23 corresponds to FIG.

The result shown in FIG. 24 has less unevenness in density than the result shown in FIG.

[0085]

As described above, according to the present invention, it is possible to obtain an image information processing method which has faithful gradation reproducibility, does not use a threshold table, and can obtain a processed image excellent in image quality. be able to.

[Brief description of drawings]

FIG. 1 is an explanatory diagram showing a coefficient matrix.

FIG. 2 is an explanatory diagram showing a process of image processing of the first invention.

FIG. 3 is a graph showing a relationship between a coefficient matrix and a matrix of target values.

FIG. 4 is an explanatory diagram showing an example of a matrix of target values.

FIG. 5 is an explanatory diagram showing another example of a coefficient matrix.

FIG. 6 is an explanatory diagram showing a partial matrix of a coefficient matrix.

FIG. 7 is an explanatory diagram showing a matrix of target values after error addition.

FIG. 8 is an explanatory diagram showing a matrix of target values after error addition.

FIG. 9 is an explanatory diagram showing another example of a coefficient matrix.

FIG. 10 is an explanatory diagram showing a process of image processing of the second invention.

FIG. 11 is an explanatory diagram showing a relationship among a coefficient matrix, an error value matrix, and a read value matrix.

FIG. 12 is an explanatory diagram showing an example of a read value matrix.

FIG. 13 is an explanatory diagram showing an example of a second coefficient matrix.

FIG. 14 is an explanatory diagram showing an example of an error value matrix.

FIG. 15 is an explanatory diagram showing an error value matrix after one-pixel processing.

FIG. 16 is an explanatory diagram showing a concept of a second coefficient matrix stored in a storage device.

FIG. 17 is an explanatory diagram showing rotation of a coefficient matrix.

FIG. 18 is an output diagram showing an example of one cycle of a coefficient matrix determined by a function.

FIG. 19 is an output diagram showing an output image according to the processing method of the present invention.

FIG. 20 is an explanatory diagram showing an example of a coefficient matrix used in the processing according to the patent application for an invention of the present invention.

FIG. 21 is an output diagram of a process according to a patent application for an invention of the present invention.

FIG. 22 is a three-dimensional view showing a coefficient matrix used in the processing according to the patent application for an invention.

FIG. 23 is an output diagram showing an example of one cycle of a coefficient matrix determined by a function.

FIG. 24 is an output diagram showing an output image according to the processing method of the present invention.

FIG. 25 is an explanatory diagram showing an example of a coefficient matrix used in a process according to an invention patent application.

FIG. 26 is an output diagram of a process according to an invention patent application.

FIG. 27 is a cubic diagram showing a coefficient matrix used in the processing according to the patent application for an invention.

[Explanation of symbols]

 2-Coefficient matrix 3-Submatrix 4-Image 5-Matrix of target values 7-Input pixels 9-Second coefficient matrix 10-Error value matrix 11-Location of error T-Threshold

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[Procedure amendment]

[Submission date] October 30, 1991

[Procedure Amendment 1]

[Document name to be corrected] Drawing

[Name of item to be corrected] Figure 2

[Correction method] Change

[Correction content]

[Fig. 2]

Claims (6)

[Claims] 1. When reproducing multivalued image information by an output device capable of binary output, a read value of an input pixel of an image or a target value obtained by adding an error addition amount to the read value is compared with a threshold value. When binarizing by, the difference between the target value and the threshold value is converted into a coefficient of a partial matrix of a coefficient matrix having a periodicity in a one-dimensional or two-dimensional direction, which consists of elements fixedly corresponding to the position of the input pixel. In the image information processing method of dividing into the error addition amount of a proportional size and adding to the target value of another input pixel fixedly distributed corresponding to the position of the input pixel, the contents of the elements of the coefficient matrix are An image information processing method characterized in that it is determined by a function having one period as a domain. 2. When reproducing multi-valued image information by an output device capable of binary output, a reading value of an input pixel of an image or a target value obtained by adding an error addition amount to the reading value is compared with a threshold value. In the case of binarization by, the difference between the target value and the threshold value is calculated and obtained from a coefficient matrix having a periodicity in the one-dimensional or two-dimensional direction, which includes elements fixedly corresponding to the position of the input pixel. The target value obtained by adding the product of the coefficient of the second coefficient matrix and the value of the element of the error value matrix regarding the surrounding error is binarized by comparison with the threshold value, and the difference between the target value and the threshold value is calculated as the error value. In the image information processing method for storing the value of the element of the error value matrix at a position corresponding to the position of the input pixel of the matrix, the content of the element of the first coefficient matrix is determined by a function having the one period as a domain. An image information processing method characterized by: 3. When the one cycle is n × n (n is an integer of 2 to 20), the value of the coefficient a _{i, j} corresponding to the target value at the i-th row and the j-th column of the input image is the function below. Formula 1 [Equation 1] The image information processing method according to claim 1, wherein the image information processing method is determined by the function value. 4. When the one cycle is n × n (n is an integer of 2 to 20), the value of the coefficient a _{i, j} corresponding to the target value at the i-th row and the j-th column of the input image is the function Formula 2 [Equation 2] The image information processing method according to claim 1, wherein the image information processing method is determined by the function value. 5. A function value g (i ′, j ′) obtained by rotating the coordinates (i, j) of the target value d _{i, j} and substituting it in the function as (i ′, j ′). 5. The image information processing method according to claim 3, wherein is a coefficient at coordinates (i, j). 6. The image information processing method according to claim 5, wherein the value of the coefficient matrix or the second coefficient matrix previously obtained by using the function is stored in a storage device.