JPH01238373A - Picture signal processor - Google Patents

Abstract

PURPOSE:To improve the gradation and resolution characteristics of the title device and to make the picture element processing speed faster by binarizing the input correction level to a noticeable picture element considering an accumulated error corresponding to the noticeable picture element and accumulated errors of the surroundings and finding a new binarized error from the difference between the sum of the noticeable picture element and the accumulated errors and a binarized result. CONSTITUTION:The 1st input correcting means 5 adds an input level Lxy and error correction level exy to each other and outputs an input correction level I1xy. The corrected input level I1xy is binarized by means of a binarizing means 8 by using the fixed threshold T=R/2 of a signal terminal 7. Then a new binarized error is found by subtracting the binarized result of the correction level I1xy from the correction level I2xy to which an accumulated error Sxy is added. When the factor Ka to be used for multiplying an accumulated error Sxy and another factor Kb to be used for multiplying the total sum of accumulated errors SA, SB, and SD of surrounding picture elements areas are respectively made smaller within ranges of 0<Ka<1 and 0<Kb<1, the picture signal component of a noticeable picture element becomes relatively larger and an output picture with an emphasized contour is obtained.

Description

DETAILED DESCRIPTION OF THE INVENTION Field of the Invention The present invention relates to an image signal processing device having a function of binary-reproducing image information including gradation images.

Conventional technology In recent years, with the mechanization of office processing and the rapid spread of image communications, there has been an increasing demand for high-quality image reproduction of gradation images and printed images, in addition to conventional black-and-white binary originals. . In particular, pseudo gradation reproduction using a binary image of a gradation image is highly compatible with display devices and recording devices, and many proposals have been made.

The dither method is the most well-known method for reproducing these pseudo gradations. This method attempts to reproduce gradation based on the number of dots reproduced within a predetermined area, and compares a threshold value prepared in a dither matrix with input image information for each pixel. Therefore, binarization processing is performed. In this method, the gradation characteristics and resolution characteristics directly depend on the size of the IJ square, and are incompatible with each other. Furthermore, when used for printed images, it is difficult to avoid the occurrence of moiré patterns in the reproduced image.

As a method that achieves both the above gradation characteristics and high resolution, and has a large effect of suppressing the occurrence of moiré patterns, the error diffusion method (Reference: R. Freud and L. Steinbarb 1.1.1.1 Special Gray Scale "Niside-75" Digest pages 36-37) are proposed.

FIG. 4 is a block diagram of essential parts of an apparatus for realizing the above error diffusion method. The coordinates of the pixel of interest in the original image are (x
, y), 1 is the error storage means, 2 is the error distribution coefficient (ma), the unprocessed pixel area around the pixel of interest indicated by the IJx, and 3 is the integrated error Sx at the coordinates (X, y).
The storage location of y, 4 is the coordinate (x.

y), the input terminal of the input level Ixy, 5 is I'x
y (= Ixy + Sxy) input correction means, 6
is an output terminal of output level 0 or R binary level Pxy, 7 is a signal terminal for applying a constant threshold value R/2, 8 is an input signal Pxy = R when input signal I'xy≧R/2, yco and other os Binarization means outputs Pxy = 0 if 9 is E
This is a difference calculation means for calculating the binarization error for the pixel of interest of xy (=I'xy - Pxy).

Now, the integration error Sxy for the pixel of interest is the (ku (2)
It is expressed by the formula.

5xy=DKij-Ex-j+2. y-i-H---<
1> (However, i and j indicate the coordinates in the error distribution coefficient matrix.) This error distribution coefficient Kij weights the distribution of the error Exy to the surrounding pixels of the pixel of interest, and in the above literature (however, * is the position of the pixel of interest).

In the configuration shown in FIG. 4, the above calculation adds the binarization error Exy to the pixel of interest to each pixel A in the unprocessed surrounding pixel area 2.
This is realized by the error distribution calculation means 10 which multiplies -D by the corresponding distribution coefficient, adds it to the value in the error storage means 1, and stores it again at the corresponding position. However, the integrated error at pixel position B in the error storage means 1 is cleared to 0 in advance.

Problems to be Solved by the Invention The above-mentioned error diffusion method is superior to the systematic dither method in terms of gradation characteristics and resolution, and is extremely resistant to the appearance of moiré patterns when reproducing printed images. It has few features. However, the Correlative Density A redistribution method, which is a type of random dither method,
signment of Adjacent Pixc
els...CAPI% method), the gradation and resolution characteristics are still poor and texture is generated.

As a method of obtaining smooth gradation characteristics, it is known that the pixel area surrounding the pixel of interest is enlarged to reduce the average error as much as possible, but in this case, the resolution deteriorates. Another problem is that the number of addition operations is large and the multi-processing speed is slow.

The present invention solves the problem of the error diffusion method by taking into account the accumulation error at the pixel position of interest and the errors in its surroundings, and achieves fine and smooth gradation characteristics and high resolution, and also reproduces printed images with moiré patterns. The object of the present invention is to provide an image signal processing device in which the occurrence of error distribution coefficients is extremely small, all error distribution coefficients are uniform, and high-speed pixel processing is possible.

Means for Solving the Problems The present invention provides an error method that stores the binarization error of a pixel of interest in correspondence with its surrounding pixel positions when binarizing a multi-gradation image signal level sampled in pixel units. a storage means; a correction error calculation means for adding an integrated error corresponding to the pixel position of interest in the error storage means and errors in its surroundings and outputting an error correction level; and the error correction level and the input level of the pixel of interest. and a binarization unit that compares the first input correction level with a predetermined threshold value to determine a binarization level of the pixel of interest. input correction means for adding the input level of the method pixel and the integration error and outputting a second input correction level; a difference calculating means for calculating a conversion error, and calculating an error allocation value corresponding to unprocessed pixels around the pixel of interest from the binarization error and error allocation coefficient from the difference calculating means, and storing the error allocation value in the error storage means. Error distribution updating means is provided for adding the accumulated error of the corresponding pixel position within the total number of pixels and storing the result again.

In particular, the correction error calculation means multiplies the integrated error corresponding to the pixel of interest and the sum of surrounding errors by a coefficient 1/2n or 1--L (where n is a positive integer) and performs an addition operation. The above objective is achieved by determining the error correction level.

Effect of the Invention With the above configuration, the present invention binarizes the input correction level that takes into account the integration error corresponding to the pixel position of interest and the integration errors around it, and converts the new binarization error into the integration error between the pixel of interest and the integration error. By calculating the difference between the sum of and the binarization result and setting the error distribution coefficient to 100, the gradation characteristics and resolution characteristics are improved, and high-speed pixel processing is made possible. Furthermore, the contour enhancement effect can be controlled by appropriately selecting the calculation coefficients by the correction error calculation means.

Embodiment FIG. 1 shows the main block configuration of an image signal processing apparatus in an embodiment of the present invention.

In Figure 1, the coordinates of the pixel of interest in the original image are (x
, y), 1 is the error storage means for storing the error, 2 is the unprocessed pixel area around the pixel of interest indicated by the error distribution coefficient matrix, and 3 is the storage position of the integrated error Sxy at the coordinates (x, y). , 4 is the coordinate (x,
y), 5 is an input terminal for input level Ixy, and 5 is a first input correction means that inputs input level Ixy and a correction error level Exy which is an output from correction error calculation means 12 described later, and outputs an input correction level hxy; 6 is an output terminal for the binarization level Pxy of output level O or R, 7 is a signal terminal for applying a constant threshold value T=R/2, and 8 is a signal terminal for comparing the input correction level L xy with the constant threshold value T=R/2. te lxy≧T
Binarization means outputs Pxy=R when Pxy=R, and pxy=o in other cases; 101 is a second input correction means that inputs the input level Ixy and the integration error Sxy and outputs the input correction level I2xy; 9 is the binarization error Ex, which is the difference between the correction level l2Xy and the binarization output level Pxy.
A difference calculating means 11 outputs y, and 11 multiplies the error distribution coefficient corresponding to unprocessed pixels surrounding the pixel of interest by the binarization error, adds the integrated error of the surrounding pixel area 2, and calculates the new integrated error as an error again. Error allocation updating means 12 stores the accumulated error Sxy corresponding to the pixel position 3 of interest and the accumulated error in the surrounding pixel area 2 in the pixel positions A-D in the storage means 1, and outputs an error correction level exy. This is a correction error calculation means.

Now, the operation shown in FIG. 1 will be described in detail.

The input correction level hxy output by the first input correction means 5 is the result of multiplying the integrated error Sxy corresponding to the pixel position of interest by a coefficient Ka by the twelve correction error calculation means, and the peripheral pixel area of the pixel position of interest 3. A, B,
Each integration error S^* 3 corresponding to C and D
a, Sc, and So are added, and the addition result is multiplied by a coefficient Kb. These multiplication results are output as an error correction level exy, and the first input correction means 5 adds the input level xy to the error correction level exy to output an input correction level lxy. This corrected input level hxy is binarized by the binarizing means 8 using a constant threshold value T=R/2 of the signal terminal 7. At that time, the binary output Pxy
outputs R when hxy≧R/2, and outputs 0 when hxy<R/2. The binarization error Exy generated at this time is calculated from the input correction level l2xY obtained by adding the integrated error Sxy at the position corresponding to the pixel of interest 3 and the input level Ixy by the second input correction means 9. conversion output P
It is obtained by the difference calculation means 10 that differentiates xy. This binarization error is further converted into an integrated error S% in the pixel processing process up to that point, which is stored in the storage device corresponding to each position of this peripheral pixel region by the error distribution updating means 11.
S/c, St.

is read out and a new integrated error S^~RD is calculated.

Then, the new integrated error is stored at pixel position A in the error storage means 1.
-Perform update processing to store in the storage device corresponding to D.

Expressing the above one-pixel processing process in a formula, IIXY =
Ixy + exyllxy = Ixy+5xyKa + (SA+SC+
5o) Kb (however, 0<Ka<1.・
...(3) 0<Kb<1) Exy = hxy -Pxy -(Ixy + Sxy) -Pxy = 1
5).

Furthermore, input correction level bxy and new binarization error Exy
I will explain in detail.

Now, the error distribution coefficient KA corresponding to each position in the peripheral pixel area
-, and further set the coefficient Ka = Kb = 1, the correction error level exy corrected to the input level Ixy
The accumulation of errors in the previous processes is Sxy = 7(Ex-1, y-1+Ex, y-1+
Ex+ 1. y −10Ex−s, y) SA =7(Ex, y−1+EX+1.y−1+EX
+2. y-t) Ba = 0 ■ SD = 7 (Ex-1, y + Ex-2, so it can be expressed as exy = Sxy + (SA + SC + 5D) = 8 (Ex-
1, y-t+2Ex, y-t+2Ex+x, y-1+3
Ex-1,y+EX+2. y-t+Ex-2. Therefore, in the correlation between the pixel of interest and the integration error, the second
A surrounding area of the pixel of interest as shown in the figure is formed. The input level Ixy is corrected by the error component formed based on such correlation. Surco means to averagely correct the error components around the pixel of interest, and it is possible to obtain a smooth reproduced image. can. Further, by selecting the coefficients Ka and Kb to be small, the amount of correction in processing the pixel of interest becomes small, and as a result, the image signal component of the pixel of interest becomes large, and a reproduced image with an enhanced outline is obtained.

Now, the new binarization error is one of the features of the present invention, but the integration error 3xy is added to the input level Ixy! This is obtained by subtracting the binarized result of the above-mentioned correction level IIXy from the correction level I+xy, and is not obtained from the binarized correction level as in the conventional error diffusion method. The reason for this is that the input level Ixy in the present invention
The error level exy that is corrected is a superposition of a part of the error component that is calculated from the correlation between the pixel of interest and the errors in its surroundings, and the error obtained with this system does not satisfy the density conservation system. Therefore, the new error for maintaining the density preservation system is the integration error in a system where the sum of the pixel of interest and the error distribution coefficient is 1, that is, 5xy=DKij・Ex−j+z,
It is obtained from the addition value of y-i-H and input level/1zIxy.

Next, when calculating the error correction level exy, the integrated error S
For convenience of explanation, the coefficient Ka multiplied by
O<K, a<1., respectively. If it is made small within the range of O<Kb<1, the image signal component of the pixel of interest will become relatively large, and an output image with enhanced contours will be obtained.

For example, if the coefficient Ka is made large (that is, the influence of the integration error is made large) and Kb is made small (that is, the error component around the pixel of interest is made small), a precise reproduced image cannot be obtained. Furthermore, if Ka and Kb are also increased, the error component correction area becomes larger, resulting in a reproduced image that is entirely blurred. On the contrary, Ka.

If both Kb are made small, the reproduced image will have extremely emphasized contours. When Ka is made small and LKb is made large, a reproduced image with enhanced contours and high precision can be obtained. This means that, as mentioned above, by decreasing Ka, the image signal component of the pixel of interest becomes relatively large, which has the effect of emphasizing the outline, and by increasing Kb, the error component around the pixel of interest increases. This increases the correction ratio, which has the effect of obtaining a precise reproduced image. By setting these coefficients to 1/2n (n is an integer) or 1-≦L, logical operations are easy and high-speed processing is possible.

FIG. 3 is a block diagram of main parts of an image signal processing apparatus according to a second embodiment of the present invention, and only the points different from the first embodiment will be described.

In FIG. 3, 7 is a signal terminal to which a partial value T=% is applied. 8 is a comparator that inputs and compares the input level Ixy and the threshold correction value T', and when Ixy≧T', Pxy
= R1 and other times, this is a binarization means that outputs Pxy = O. Reference numeral 305 denotes a threshold value correction means for inputting the error correction level exy outputted by the correction error calculation means 12 and a fixed amount value T, and calculating the difference therebetween.

The operating principle is the same as the first embodiment, but the difference from the first embodiment is that in the first embodiment, the error correction level
y is that the input correction level added to the input level Ixy is binarized using a fixed threshold value, whereas in this embodiment the input level is binarized using a threshold correction value T'. That is, the feature of this embodiment is that the calculations of the binarization means 8 can be lightened. The binarization operation in the first embodiment requires a 10-bit operation, but the present embodiment allows a 9-bit operation.

Effects of the Invention As described above, the present invention binarizes the input correction level corrected by adding a part of the integration error corresponding to the position of the pixel of interest and a part of the total sum of the surrounding integration errors to the pixel of interest. , in order to satisfy the density conservation system, the gradation and resolution characteristics can be adjusted by subtracting the above-mentioned binarization result from the correction level obtained by adding the new binarization error to the pixel of interest and the accumulation error of the pixel of interest position. This made it possible to improve. Furthermore, by appropriately selecting the coefficients Ka and Kb of the correction error level exy, edge enhancement control is possible. Furthermore, even if the error distribution coefficient is set uniformly, textures and patterns flowing in one direction, which are seen with conventional error diffusion methods, do not occur, making it possible to obtain a detailed, high-resolution binary reproduced image. is big.

[Brief explanation of the drawing]

FIG. 1 is a block diagram of an image signal processing device according to an embodiment of the present invention, FIG. 2 is a conceptual diagram of the peripheral error region formed by the correction error calculation means which is the main part of the device, and FIG. FIG. 4 is a block diagram of an image signal processing device according to a second embodiment of the present invention. FIG. 4 is a block diagram of a device implementing the conventional error diffusion method. 1... Error storage means, 2... Surrounding pixel area, 3...
- Pixel position of interest, 4... Input terminal, 5... First input correction means, 6... Output terminal, 7... Partial value input terminal, 8... Binarization means, 9... Difference calculation means, 1
0.S.Error distribution calculation means, 101... Second input correction means, 11... Error distribution update means, 12... Correction error calculation means, 201... New surrounding pixel region, 30
5...Threshold value correction means. Name of agent: Patent attorney Toshio Nakao and one other person Figure 1 Figure 2 Figure 3 Figure 4

Claims (2)

[Claims] (1) Error storage means for storing the binarization error of the pixel of interest in correspondence with the surrounding pixel positions when binarizing the multi-gradation image signal level sampled in pixel units; and the error storage. a correction error calculation means for adding an integrated error corresponding to the pixel position of interest and errors in its surroundings in the means and outputting an error correction level; a first input correction means for outputting an input correction level; a binarization means for comparing the first input correction level with a predetermined threshold value to determine a binarization level of the pixel of interest; a second input correction means that adds the input level and the integrated error and outputs a second correction level; and a difference calculation that calculates a binarization error based on the difference between the second input correction level and the binarization level. and calculates an error distribution value corresponding to unprocessed pixels around the pixel of interest from the binarization error and error distribution coefficient from the difference calculation means, and stores the error distribution value at the corresponding pixel position in the error storage means. An image signal processing device comprising: an error distribution update means for adding the accumulated error of (2) The correction error calculation means performs an addition operation by multiplying the sum of the integrated error corresponding to the pixel of interest and the errors in its surroundings by a coefficient 1/2n or 1-1/2n (where n is a positive integer), respectively. Claim 1 characterized in that the error correction level is determined.
The image signal processing device described.