JPH0376630B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION (Field of Industrial Application) The present invention relates to an image processing method that performs at least one of enlarging or reducing an image and gradation processing.

(Prior Art) As methods for enlarging or reducing a binarized image using a pixel density conversion method, the SPC method, the logical sum method, the nine-division method, the projection method, and the like have been known.

(Problems to be Solved by the Invention) Problems with these conventional methods include the fact that the lines are conspicuously blurred or missing.
The biggest problem is that moiré fringes occur when a halftone image with a periodic structure, such as a binarized image expressed by the systematic dither method, is enlarged or reduced.

On the other hand, in the case of this type of binary halftone image, there is no method to easily perform gradation processing (conversion).

The present invention has been made in view of this point, and its purpose is to provide an image that can be enlarged/reduced without causing moiré fringes even if it is a binarized image with a periodic structure, and that can also be easily subjected to gradation processing. The purpose is to provide a processing method.

(Means for Solving the Problems) The present invention, which solves the above-mentioned problems, reads out a binarized image stored in a memory, and reads out a binarized image stored in a memory, A first step of dividing the image into blocks, counting at least one of the number of black pixels or the number of white pixels for each block, and storing the counted value in memory; and storing the number of pixels obtained in the first step from the memory. read out, convert the number of pixels based on the gradation curve,
A second step of storing the number of pixels after the gradation conversion in the memory, and reading out the number of pixels after the gradation conversion obtained in the second step from the memory, and from the number of pixels, for each block, respectively. a third step of obtaining a first density matrix pattern corresponding to the number of pixels and storing it in the memory; reading out the first density matrix pattern of each block obtained in the third step from the memory; When converting into a second density matrix pattern of a size corresponding to the magnification m/n (where m and n are integers), the second density matrix of the block located I-th in the row direction and J-th in the column direction is As the density value of the x-th row and y-th column in the pattern, the density value in the first density matrix pattern of the block before enlargement/reduction located at the I-th row direction and the J-th column direction
Adopt the density value of AD1 row and AD2 column.
mod[p, q] is the remainder of p÷q.

For magnification (magnification m/n>1), AD1=mod[x+mod[(I-1)(m-n),n]+1-2,n]+1 AD2=mod[y+mod[(J-1)( m-n) ,n]+1-2,n]+1 For reduction (magnification m/n<1), AD1=mod[x+mod[(I-1)(n-|n-m
|) ,n]+1-2,n]+1 AD2=mod[y+mod[(J-1)(n-|n-m
|) ,n]+1-2,n]+1 A fourth step of obtaining the second density matrix pattern in all blocks, and an image reconstructed with the second density matrix pattern of each block. is the processed image.

(Example) Hereinafter, the image processing method of the present invention will be specifically explained using FIGS. 1 to 7.

First, the object of image processing is a binarized image. This binarized image can be easily obtained by using, for example, a 4×4 or 8×8 dither matrix as a threshold value. The setting width of the threshold values that make up this dither matrix is, for example, wide in the case of gradation drawings, about 0.1 to 1.4 in terms of reflection density, and narrow in the case of line drawings, in terms of reflection density, about 0.1 to 0.5 (or by setting a fixed threshold value). It is preferable to use This is to prevent the image from becoming blank or thick. Further, different types of dither matrices may be used for gradation drawings and line drawings. Note that the binarization method may be a method other than the dither method, such as a density pattern method or a dot method.

In the method of the present invention illustrated in FIG. 1, first, if the image is not a binarized image, the above-mentioned binarization is performed (step). In Figure 2, the size is 4×
Using the dot dispersion type (Bayer type) dither matrix DM1 (see Fig. 2 A) of No. 4, the original image A (see Fig. 2 B) is binarized by the dither method, as shown in Fig. 2 C. An example of obtaining a binarized image B is shown. In this figure, the dither matrix
The numbers in DM1 and original image A indicate standardized density levels, and the pixels in the diagonally shaded portion of binarized image B indicate that they are black pixels.

In the next step, the binarized image is divided into blocks of appropriate size. In FIG. 2C, it is divided into 4×4 sizes. Then, the number of black pixels (or the number of white pixels) in each block is counted (step), and the process proceeds to gradation processing. The gradation processing performed here is
This is done by converting the above black pixel number (hereinafter referred to as the original black pixel number) to another black surface prime number (hereinafter referred to as the converted black pixel number) based on a predetermined gradation curve (step) . In the example in Figure 3,
Using the gradation curve shown in FIG. 3A, the original black pixel number shown in FIG. 3B is converted to the converted black pixel number shown in FIG. 3C. The type of gradation processing to be performed depends on the gradation curve used during conversion, but in general, the gradation curve C _A with the upwardly convex curve in Figure 4 is used. If you use gradation curve C _B , which has a downwardly convex curve in Figure 4, you will reduce the number of black pixels and increase the frequency of low density areas. This is a conversion that reduces the frequency. Therefore, the gradation curve C _A is effective for a pale binary image, and the gradation curve C _B is effective for a darkened image. Of course, it is also possible to use a gradation curve, such as an S-shaped curve, which is a combination of the gradation curves C _A and C _B circles, and it is sufficient to select a gradation curve that matches the desired gradation processing. In the image processing apparatus, three to five types of typical gradation curves may be prepared and one of them may be selected depending on the image.

From the number of converted black pixels thus obtained, the density level of each block is determined to obtain a first density matrix pattern (step). Here, the block size is equivalent to the size (4 x 4 or 8 x 8) of the dither matrix (threshold value group) used to obtain the binarized image, preferably larger than the size of the dither matrix. Choose a smaller size. In this way, high resolution can be maintained while increasing the number of gradations. Figure 5(b) shows the number of converted black pixels in each block as the normalized average density level of each block, and Figure 5(c) shows the number of converted black pixels in each block as the normalized average density level of each block. In this example, the first density pattern is determined by copying the dither matrix DM2 (see Fig. 5A), which is the same as the dither matrix DM1 described above, and each block. This is done by comparing the concentration level of

For example, in the case of block BK1, its density level is 11, so the portion of the dither matrix DM2 in FIG. This results in a density matrix pattern like this.

After obtaining this first density matrix pattern, a second density matrix pattern of a size corresponding to the enlargement/reduction magnification is obtained for each block (step), and these are arranged in block order to form an enlarged/reduced image. Get (step). Figure 6A is an enlarged image obtained in this way with a magnification of 5/4.
Figure b is a reduced image with a reduction magnification of 3/4. here,
The size ratio of the first and second density matrix patterns corresponds to the vertical and horizontal enlargement/reduction magnification,
The vertical and horizontal sizes of the second density matrix pattern are the vertical and horizontal sizes of the first density matrix pattern multiplied by the vertical and horizontal expansion/reduction magnification. Therefore, in the example of FIG. 6, the size is 5×5 in the case of FIG. 6A, and the size is 3×3 in FIG. 6B.

In this example, when the mother pattern obtained by two-dimensionally arranging the corresponding patterns in the first density matrix pattern is divided by the size of the second density matrix pattern,
Cut out a pattern that has the same positional relationship as the second density matrix pattern that you are trying to find,
This is used as the corresponding second density matrix pattern. FIG. 7 is an explanatory diagram (magnification: 5/4) showing an example of obtaining a second density matrix pattern from a first density matrix pattern.
4) Blocks f ₁₁ , f ₁₂ , f ₁₃ ,..., f ₂₁ , f ₂₂ ,...,
The plane consisting of... is the block F ₁₁ , F ₁₂ , F ₁₃ , of the second density matrix pattern (size 5×5),
..., F ₂₁ , F ₂₂ , ..., ... is shown. First, as a second density matrix pattern corresponding to block F ₁₁ , all blocks f ₁₁ ,
The position of block F ₁₁ is determined from the mother pattern assuming that f ₁₂ , f ₁₃ , ..., f ₂₁ , f ₂₂ , ..., ... contain the same first density matrix pattern corresponding to block f ₁₁ . Use a pattern cut out from . Similarly, the second density matrix pattern corresponding to block _F12 includes all blocks.
Blocks are added to f ₁₁ , f ₁₂ , f ₁₃ ,…, f ₂₁ , f ₂₂ ,…,…
From the mother pattern, which is assumed to contain the same first density matrix pattern corresponding to f ₁₂ ,
Use the pattern cut out at block F ₁₂ . That is, as a second density matrix pattern corresponding to block Fij, the same first density matrix pattern corresponding to block fij is applied to all blocks f ₁₁ , f ₁₂ , f ₁₃ , ..., f ₂₁ , f ₂₂ , ..., ... A pattern at the position of block Fij is cut out from a mother pattern that is assumed to contain a density matrix pattern. The above-mentioned FIG. 6A shows the second density matrix pattern obtained in this way arranged on a plane. The same applies to Figure 6B.

Note that matrices DM1 and DM2 do not need to be composed of the same thing; for example, if matrix DM1 and DM2 are
2 may be of dot concentration type (spiral type).

Further, a specific method for obtaining the pattern of each block after scaling described above may be to actually configure the above-mentioned mother pattern in memory and read data at a predetermined address from it to obtain the pattern. , this would require an extremely large memory capacity. Therefore, instead of actually creating a mother pattern, attention may be paid to the periodicity of the pattern, and the density of each pixel may be determined in the following manner to obtain a pattern after scaling.

That is, in the case of enlargement (magnification m/n), the x-th pattern in the I-th block in the row direction of the new block (block after enlargement) is the same as the pattern in the I-th block in the row direction of the block before enlargement. AD1=mod[x+mod[(I-1)(m-n),n]+1-2,n]+1th row pattern and y column in the Jth block in the column direction of the new block. The eye pattern is equal to the pattern of the AD2=mod[y+mod[(J-1)(m-n),n]+1-2,n]+1st column in the Jth block in the column direction of the block before expansion. On the other hand, in the case of reduction (magnification m/n), the x-th pattern in the I-th block in the row direction of the new block (block after water reduction) is the same as that in the I-th block in the row direction before reduction. , AD1=mod[x+mod[(I-1)(n-|n-n
|) ,n]+1-2,n]+1 The pattern in the y-th column in the J-th block in the column direction and which is equal to the pattern in the J-th row in the column direction of the new block is the same as the pattern in the J-th block in the column direction of the block before reduction. , AD2=mod[y+mod[(J-1)(n-|n-m
|) ,n]+1-2,n]+1 Equivalent to the pattern in the 1st column.

Here, mod [p, q] is the remainder of p÷q,
Of course it is smaller than q.

Therefore, if the pixel density of the block before scaling is stored in memory, the new pixel density can be easily read by using AD1 and AD2 as addresses in the row and column directions and reading out the pixel density in the block before scaling. You can get the block pattern.

FIG. 8 is a diagram showing an example of an apparatus for realizing the method of the present invention. In the figure, 1 reads the binarized image stored in the memory 2, divides it into blocks whose size is less than the threshold value group used to obtain the binarized image, and counts the number of black pixels for each block. A black pixel counting means 2 stores the counted value in the memory 3; 2 reads the number of black pixels from the memory 3, converts it using the gradation curve, and stores the number of black pixels after the gradation conversion in the memory 5; The gradation processing means 6 reads the number of black pixels after gradation conversion from the memory 5, and from the number of black pixels, creates a first density matrix pattern corresponding to each number of black pixels for each block. A first density matrix pattern creating means 8 reads out the first density matrix pattern of each block from the memory 7 and creates a second density matrix pattern of a size corresponding to the magnification. This is second density matrix pattern creation means for conversion. In this second density matrix pattern creation means 8, when converting the first density matrix pattern into a second density matrix pattern,
The density value of the x-th row and y-th column in the second density matrix pattern of the block located at the
The density values of the aforementioned AD1 row and AD2 column in the first density matrix pattern of the block before enlargement/reduction located at the I-th row direction and J-th column direction are adopted. Then, the second density matrix pattern creating means 8 stores the second density matrix patterns in all blocks in the memory 9. In this way, on the memory 9, a binarized image reconstructed with the second density matrix pattern of each block,
In other words, it has been enlarged or reduced and gradation processing has been performed.
The digitized image will be stored. It should be noted that if the plurality of memories mentioned above have a large memory capacity, a single memory is sufficient.

(Effects of the Invention) As explained above, in the present invention, a second density matrix pattern having a size corresponding to the magnification is obtained for each block from the first density matrix pattern. is unchanged;
Unlike the conventional method of obtaining enlarged/reduced images by changing the sampling interval, moiré fringes are less likely to occur. Furthermore, since gradation processing is achieved by converting the average density level (number of black pixels) of a block, gradation processing can be easily performed.

[Brief explanation of drawings]

FIG. 1 is a flowchart showing an example of the method of the present invention, FIG. 2 is an explanatory diagram showing an example of binarization in FIG. 1, FIG. 3 is an explanatory diagram of gradation processing in FIG. 1, and FIG. 5 is an explanatory diagram of the gradation curve, FIG. 5 is an explanatory diagram of the first density matrix pattern in FIG. 1, and FIG. 6 is an explanatory diagram of the second density matrix pattern (enlarged/reduced image) in FIG. 1. Figure, 7th
The figure is an explanatory diagram of a method for obtaining a second density matrix pattern from a first density matrix pattern.
FIG. 8 is a diagram showing an example of an apparatus for realizing the method of the present invention. DM1, DM2...Dither matrix, A...Original image, B...Binarized image, _f11 , _f12 ,...,
f ₂₁ , f ₂₂ ,...Block of the first density matrix pattern, F ₁₁ , F ₁₂ ,..., F ₂₁ , F ₂₂ ,... Block of the second density matrix pattern C _A , C _B ... Gradation curve .

Claims (1)

[Claims] 1. Read out a binarized image stored in a memory, divide it into blocks whose size is less than or equal to the threshold value group used to obtain the binarized image, and calculate the number of black pixels or the number of black pixels for each block. A first step of counting at least one of the number of white pixels and storing the counted value in a memory, and reading out the number of pixels obtained in the first step from the memory and converting the number of pixels based on a gradation curve. , a second step of storing the number of pixels after the gradation conversion in the memory, reading out the number of pixels after the gradation conversion obtained in the second step from the memory, and calculating the number of pixels for each block from the number of pixels. , a third step of obtaining a first density matrix pattern corresponding to each number of pixels and storing it in the memory; and reading out the first density matrix pattern of each block obtained in the third step from the memory. When converting into a second density matrix pattern with a size according to the magnification m/n (where m and n are integers), the second density of the block located I-th in the row direction and J-th in the column direction is As the density value of the x-th row and y-th column in the matrix pattern, the first density matrix pattern of the block before enlargement/reduction located I-th in the row direction and J-th in the column direction.
Adopt the density value of AD1 row and AD2 column.
mod[p, q] is the remainder of p÷q. For magnification (magnification m/n>1), AD1=mod[x+mod[(I-1)(m-n),n]+1-2,n]+1 AD2=mod[y+mod[(J-1)( m-n) ,n]+1-2,n]+1 For reduction (magnification m/n<1), AD1=mod[x+mod[(I-1)(n-|n-m
|) ,n]+1-2,n]+1 AD2=mod[y+mod[(J-1)(n-|n-m
|) ,n]+1-2,n]+1 A fourth step of obtaining the second density matrix pattern in all blocks, and an image reconstructed with the second density matrix pattern of each block. An image processing method characterized in that an image is processed.