JP2913867B2 - Color image processing method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention
More particularly, the present invention relates to a binarizing method for recreating a digital multi-valued color image read by a scanner using a color output device capable of binary output.

[0002]

2. Description of the Related Art Generally, in the field of image processing, multi-valued colors are used.
As a method for binarizing an image and reproducing gradation, an organized dither method and an error diffusion method are known.

In the systematic dither method, one pixel of an input signal read from a multi-valued image document is made to correspond to one pixel of binary recording, and the periodicity is fixedly made to correspond to the position of the input signal. "Output" by comparing with the given threshold table,
This is a binarization method for determining “not 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 in accordance with the magnitude of a coefficient of a coefficient matrix which is relatively fixed to an error occurrence location. This is a binarization method that is dispersedly added to surrounding input pixels.

On the other hand, in the field of printing, a color film is used as an input medium, and color separation is used to form periodic halftone dots on a black and white film by an optical method using a contact screen. There is known a method in which a printing plate is used to reproduce a color image as a halftone image. In the case of a dot image, the size of the dot represents the density of the image. Furthermore, a method is known in which the contact screen is rotated at a different angle for each color at this time, so that the occurrence of moire and color difference due to misregistration for each color is reduced.

Further, a method of forming a halftone dot by an electronic method without using an optical screen has also been developed, and is provided in recent printing scanners and plotter systems.

[0007]

However, the dither method generates a unique pattern related to the structure of the threshold table, and is not always sufficient in terms of faithful gradation reproducibility. Color difference occurs.

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

In order to solve these problems, a color
When binarizing a density value of an input pixel of an image or a target value obtained by adding an error addition amount to the density value with a threshold value, the difference between the target value and the threshold value is fixedly corresponded to the position of the input pixel. Is divided into error additions having a size proportional to the coefficients in the sub-matrix of the coefficient matrix having periodicity in the one-dimensional or two-dimensional direction and distributed in a fixed manner corresponding to the position of the input pixel. A method for adding to the target value of another input pixel is filed as Japanese Patent Application No. 2-250944 (filed on Sep. 20, 1990). Is smaller than the error value. In particular, when the error value is small, the sum of the error addition becomes 0 even though the error value is not 0, so that a bright (target value) portion of the color image is small. The concentration reproducibility of It was.

The present invention has been made in view of the above circumstances, and is disclosed in Japanese Patent Application No. 2-250944 (Heisei 2).
Image information processing which has improved fidelity gradation reproducibility, does not use a threshold table, and can obtain a processed image excellent in image quality. The purpose is to obtain a method.

[0011]

In response to this object, a color image information processing method according to a first aspect of the present invention provides a method for reproducing multi-valued color image information using an output device capable of binary output. When binarizing a target value consisting of a density value of an input pixel of an image or a value obtained by adding an error addition amount to the density value, and comparing the target value with a threshold, the difference between the target value and the threshold is set at the position of the input pixel. It is divided into the above-mentioned error addition having a size proportional to a coefficient in a partial matrix of a coefficient matrix having a periodicity in one-dimensional or two-dimensional directions consisting of corresponding elements, and is fixed at the position of the input pixel. In the color image information processing method for adding to the target values of other input pixels distributed corresponding to the following, cij is a sub-matrix element of p rows and q columns of the matrix of the target values of the input pixels, and aij is a position of the input pixels. P rows of the coefficient matrix correspondingly fixed When elements of a sub-matrix of q columns are used, the difference between the value of cij and the threshold value is changed by a coefficient awz (where w is a natural number from i to i + p−1, and z is q The following natural number α is set to j−α + 1
(Except for aik where k ≦ j, excluding the natural numbers from to j−α + q), and divide it into error additions ewz having a magnitude proportional to cwz. When adding ewz to cwz, The number of rows p and the number of columns q of the partial matrix are changed according to the magnitude of the error value.

[0012]

[0013]

[0014]

Operation First, a coefficient matrix is prepared. Each element of the coefficient matrix fixedly corresponds to the position of the input pixel of the color image. This coefficient matrix has a period of length m in the row direction,
It has a period of length n in the column direction. Then, a sub-matrix of p rows and q columns is assumed in the coefficient matrix.

An input value from an input pixel is binarized by a threshold value. An error between the input value and the threshold value generated at this time is divided at a predetermined ratio and accumulated in an input value 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 sub-matrix of the coefficient matrix fixedly corresponding to the input pixel, and the number of rows and columns of the sub-matrix is the magnitude of the error value. Is determined according to.

By performing such an operation by scanning all the pixels of the color image, a binary image of a single color image of the color image can be obtained. When a single color image to be superimposed is reproduced for each color, the above process is performed by rotating the coefficient matrix at a different angle for each color.

[0017]

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 invention will be described.

In FIG. 1, reference numeral 2 denotes a coefficient matrix. The coefficient matrix 2 is a coefficient matrix having a length m in the U-axis direction and a length n in the V-axis direction. One cycle includes _nm coefficients of a ₁₁ ... A _nm . Coefficient matrix 2
Are fixedly corresponding to the positions of the input pixels 7 of the multi-valued color image 4 (FIG. 2) as the original.

That is, in FIG. 3, reference numeral 2 denotes a coefficient matrix, 3 denotes a sub-matrix of p rows and q columns of the coefficient matrix 2, and elements a _ij of the coefficient matrix 2 represent input multi-valued color images 4 of the color image 4. Since the coefficient matrix 2 has a periodicity corresponding to the element c _ij of the target value matrix 5, the value of a _ij is a
_It is equal to the value of _{i mod m, j mod n} . For example, period m = 4, n
When a = 3, a _11,8 = a _11mod4,8mod3 = a ₃₂ and _therefore the values of a _3,2 and a _11,8 are equal. The element c _ij of the target value matrix 5 fixedly corresponds to the position of the input pixel 7 of the color image 4. Here, the target value indicated by the element c _ij of the matrix 5 is a read value obtained by reading the input pixel 7 of the color image 4 or a value obtained by sequentially adding an error addition to be described later 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 c _ij is binarized by comparing it with a certain threshold T. If c _ij ≧ T, the binarized signal is “ Output"
, And an error of e = c _ij −T is generated. If c _ij <T, the binarized signal is “not output” and an error of e = c _ij is generated.

The error e is calculated by assigning a coefficient a to each element of the p-row, q-column sub-matrix 6 of the target pixel matrix 5 of the input pixel corresponding to the range of the p-row, q-column sub-matrix 3 of the coefficient matrix 2 including a _{ij wz} (where w is a natural number from i to i + p−1 and is changed, z is a natural number α less than or equal to q for each w, and each natural number from j−α + 1 to j−α + q is (Excluding _aik with k ≦ j among the values changed in this way) and is added to the target value of the input pixel. At this time, p and q change according to the magnitude of the error value.

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

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

Next, as an example, a process of diffusing an error by the above-mentioned processing is shown by a diagram. However, the scope of the claims is not limited by the size and numerical value of the matrix used in this description. In FIG. 4, reference numeral 5 denotes a matrix of target values of the input multi-valued color image, which is a matrix of read values of pixels of the color image before errors are added as elements.
Reference numeral 10 indicates a location where an error has occurred. As shown in FIG. 5, the coefficient matrix 2 is a coefficient matrix of 5 rows and 5 columns, and the sub-matrix 3 is determined by an error value as shown in FIG. Range pixel value can take inputs a 0 to 100, when the threshold value is 100, the binary signal and the value of c ₁₁ of the object value matrix 5 is smaller than is the threshold 42 has 42 becomes "no output" An error occurs, and the size of the sub-matrix is selected as 2 × 2, and the input pixel matrix element c corresponding to the error diffusion ranges a ₁₂ , a ₂₁ and a _22
12 , c ₂₁ and c ₂₂ respectively e ₁₂ = 12 (= 42 × 3 /
(3 + 3 + 4)), e ₂₁ = 12 (= 42 × 3 / (3 + 3)
+4)), e ₂₂ = 16 (= 42 × 4 / (3 + 3 + 4))
Are added, and as a result, the matrix 5 of target values of the input multi-valued color image is as shown in FIG. The value of a pixel a ₁₂ of the input is the next processing target is 11 errors become so larger than a 111 threshold binary signal "output", the size of the submatrix is 2 × 2 is selected Error diffusion ranges a ₁₃ , a ₂₂ , a
Input elements c ₁₃ corresponding to _23, c _22, respectively c ₂₃ new error-division _{e 13 = 3 (= 11 ×} 3 / (3 + 4 +
4)), e ₂₂ = 4 (= 11 × 4 / (3 + 4 + 4)), e
₂₃ = 4 (= 11 × 4 / (3 + 4 + 4)) is added, and as a result, the matrix of the read values of the input multi-valued color image is as shown in FIG. Similar processing is performed on the entire input pixels in the order of main scanning and sub-scanning to complete the processing for one frame.

In the above example, the error amount at the first error occurrence location is 42, but the sum of the dispersed error additions is 40.
(= 12 + 12 + 16).
It has been reduced by two. However, if the number of rows and columns of the submatrix is fixed to 3 rows and 3 columns,

E ₁₂ = e ₁₃ = e ₂₁ = e ₃₁ = (3 × 42) / (3 + 3 + 3 + 4 + 4 + 3 + 4 + 5) = 4 e ₂₂ = e ₂₃ = e ₃₂ = (4 × 42) / (3 + 3 + 3 + 4 + 4 + 3 + 4 + 5) = 5 e ₃₃ = ( 5 × 42) / (3 + 3 + 3 + 4 + 4 + 3 + 4 + 5) = 7

And the sum of the error additions is 38 (4 ×
4 + 5 × 3 + 7), which is further reduced by two compared to the case of two rows and two columns. This indicates that the density reproducibility is better when the number of rows and the number of columns of the partial matrix are changed according to the magnitude of the error value.

Next, the second invention will be described.

In FIG. 9, 2a is obtained by rotating the coefficient matrix 2 by the angle A, and 2b is the color of the input.
Is a coefficient matrix having an element b _ij corresponding to an element c _ij of the matrix 5 of the target value of the multi-valued input pixel of which the value of the element b _ij is a
equal to the value of _rl ,

R = [i · cos (A) −j · sin (A)] mod m. l = [i · sin (A) + j · cos (A)] mod n. There is a relationship. Here, [] indicates a rounding process.

Instead of the coefficient matrix 2, a coefficient matrix 2 b rotated using different angles for each color is used, and by performing the same processing as that used in the description of the first invention, the register at the time of output is obtained. Reduce moire and color difference caused by misalignment 2
A value image is obtained.

Next, the third invention will be described.

The processing speed can be increased by storing the coefficient matrix rotated in the same manner as in the second invention in a storage device before binarization. In particular, by selecting an angle θ such that tan θ = δ / γ is a rational number, it is possible to construct a repeatable and rotated coefficient matrix in which the number of elements on one side is the following equation 1. Yes, it is possible to reduce the size of the area occupied on the storage device. Here, f is the least common multiple of the number of vertical and horizontal elements n and m of the coefficient matrix.

[0035]

(Equation 1)

In FIG. 21, 2c is one unit of an n × n coefficient matrix, and 2d is an example in which the coefficient matrix is rotated by an angle θ such that tan θ = 3/4. 2 is the number of elements on one side, and can be repeated vertically and horizontally.

[0037]

(Equation 2)

(Experimental Examples) Hereinafter, the above method will be specifically described with reference to experimental examples, but the present invention is not limited by the numbers described in the experimental examples.

(Experimental Example-1) FIG. 10 is used as input multi-valued information taking values in the range of 0 to 255, the threshold is set to 255, FIG. 11 is used as a coefficient matrix, and the size of the sub-matrix is shown in FIG. The rotation angle was set to 0 ° and the binary image shown in FIG. 12 was obtained.

On the other hand, under the same conditions, the size of the sub-matrix is 4 ×
When it is fixed to 4, it becomes as shown in FIG.

(Experimental Example 2) FIG. 10 is set as input multi-valued information taking values in the range of 0 to 255, the threshold is set to 255, FIG. 11 is set to a coefficient matrix, and the size of a submatrix is set to 4 × 4. ,
With the rotation angle set to 30 °, the binary image of FIG. 15 was obtained. Also in this case, it can be seen that a shape close to a halftone dot can be obtained.

(Experimental Example-3) A transparent color manuscript was input using SG-818 (manufactured by Dainippon Screen Co., Ltd.) as a printing scanner, and a personal computer (manufactured by NEC Corporation) was input.
The computer PC-9801 performs the binarization processing, outputs a binary image on a black-and-white film using a laser plotter manufactured by Cytex Corporation, and outputs a color image using a proof printing machine manufactured by DuPont Corporation. Was reproduced, and almost the same results as those of the conventional printed matter were obtained. At this time, the coefficient matrix shown in FIG. 11 is used, the size of the sub-matrix is set to 4 × 4, and the coefficient matrix is shown in FIG.
Each color was rotated at the angle shown in FIG.

As a result, a binary image with little color difference and no moiré due to misregistration at the time of output was obtained.

(Experimental Example-4) A stepwise gradation from 10% to 100% in steps of 10% was used as input data, and the sub-matrix was divided into 4 rows and 4 columns using the diffusion matrix shown in FIG. Experiments were conducted on two cases, one in which the error was fixed according to the magnitude of the error value as shown in FIG.
The dot% of the value image was examined, and a result as shown in FIG. 20 was also obtained. From this, it is understood that the density reproducibility is better when the size of the sub-matrix is changed according to the size of the error value.

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

By making the two-dimensional coefficient matrix of one cycle of nm of the present invention into a pyramid shape in which the value at the center is larger than the surroundings as shown in FIG. A dot-like binarized image having a period similar to that of printing plate making using a screen is obtained.
By using a mountain range-like coefficient as shown in (1), an effect similar to the case of using a line screen in conventional printing can be obtained, and in any case, moire and color difference are significantly reduced.

[Brief description of the drawings]

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

FIG. 2 is an explanatory diagram illustrating a process of image processing.

FIG. 3 is a graph showing a sub-matrix in a coefficient matrix.

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 a rotated coefficient matrix.

FIG. 10 is an explanatory diagram showing a read value matrix of a multi-value image.

FIG. 11 is an explanatory diagram showing another example of the coefficient matrix.

FIG. 12 is an output diagram showing an output image obtained by the processing method according to the present invention.

FIG. 13 is an explanatory diagram showing a variable-size submatrix .

FIG. 14 is an output when the size of a submatrix is fixed.
It is a figure showing an image .

FIG. 15 is an output diagram showing another output image according to the present invention.

FIG. 16 is a table showing a rotation angle for each color of a coefficient matrix.

FIG. 17 is a three-dimensional explanatory view showing another example of the distribution of the magnitudes of the coefficients of the elements of the coefficient matrix.

FIG. 18 is a three-dimensional explanatory view showing another example of the distribution of the magnitudes of the coefficients of the elements of the coefficient matrix.

FIG. 19 is an explanatory diagram of a diffusion matrix.

FIG. 20 is a diagram illustrating a ratio (%) of output dots of a binary image.

FIG. 21 is an explanatory diagram of a coefficient matrix rotated by an angle θ such that tan θ is a rational number.

[Explanation of symbols]

 2 Coefficient matrix 3 Submatrix 4 Color image 5 Matrix of target value 6 Submatrix 7 Input pixel T Threshold

Claims (3)

(57) [Claims] When a multi-valued color image information is reproduced by an output device capable of binary output, the density value of an input pixel of a color image or a value obtained by adding an error addition to the density value of the input pixel .
When binarizing a target value consisting of
The error having a magnitude proportional to a coefficient in a sub-matrix of a coefficient matrix having a periodicity in a one-dimensional or two-dimensional direction including elements corresponding to a difference between the target value and a threshold fixedly corresponding to the position of an input pixel. In the color image information processing method of dividing into addition components and adding to a target value of another input pixel fixedly corresponding to the position of the input pixel , cij is defined as the input pixel.
Input aij, element of p row and q column submatrix of target value matrix
P rows and q columns of the coefficient matrix fixedly corresponding to pixel positions
, The difference between the value of cij and the threshold is
Coefficient awz (where w is a natural number from i to i + p-1)
, And for each w, z is a certain natural number less than or equal to q
By setting the number α, each natural from j-α + 1 to j-α + q
Of the values changed and taken, aik with k ≦ j is
Ex), the error is divided into ewz,
When adding ewz to cwz, the magnitude of the error value
A color image information processing method, wherein the number of rows p and the number of columns q of the partial matrix are changed . 2. A color image processing method according to claim 1, wherein the rotating at different angles the coefficient matrix for each color. 3. A color image information processing method according to claim 2 , wherein said coefficient matrix rotated in advance at a different angle for each color is stored in a storage device.