JPH0227872A - Image quality improvement method - Google Patents

Abstract

PURPOSE:To attain easy to see picture difficult to be read due to blur or deformation by applying contraction or spread of the picture selectively together with a binarizing level. CONSTITUTION:A picture spread means outputting 0 regardless of a signal of a noted picture element only when all surrounding picture elements are logical 0 in an area (e.g., noted picture element and 8 picture elements of upper/ lower/left/right/oblique directions) as to the picture after binarization and a picture contraction means outputting logical 1 regardless of a signal level of the noted picture element only when all surrounding picture elements are logical 1 are provided. Thus, each means is switched so that picture spread is applied when the binarized level is decreased and picture contraction is applied when the binarized level is increased. Thus, the picture quality of a character or a line drawing is improved and the system is utilized for the processing by making the width thick or thin as the processing of the line drawing or the character.

Description

DETAILED DESCRIPTION OF THE INVENTION [Technical Field] The present invention relates to an image quality improvement method, and more particularly to an image quality improvement method designed to improve image quality when processing line drawings and character images in digital copying machines and the like.

[Prior art]

In image processing of a digital copying machine or the like, in FIG. 16, when a figure as shown in FIG. 16(a) is read by a digital scanner, data as shown in FIG. 16(a) is obtained. Here, the output is considered to be 0 to 30. If this is binarized with 16 or more as 1, the result will be as shown in Fig. 16 (C), noise will occur in the surroundings, and if it is 18 or more, Fig. 16 (dl
As a result, chipping occurs.

This kind of thing should not normally happen, but in addition to the noise caused by dirt on the scanner and the accuracy of the input system, in the actual manuscript, when the lines and characters are handwritten characters other than printed ones, or output from a printer, etc. In general, digital copying machines change the binarization level, perform MTF correction on the optical system, and process edges to emphasize the input data. If there is a problem with this, this noise will be further emphasized.

In addition, when performing hollow processing on an image as shown in Fig. 17(a), if the input data is ideal as shown in Fig. 17(a), filter processing using the filter coefficients shown in Fig. Figure 17 (C1) If the negative number is 0, a 1-dot frame can be created.If the image is anything other than 0, including a negative number, a 2-dot frame can be created.However, in general, the scanner read data will be as shown in Figure 8(b). There are many cases where the output is 0 to 3.
Set to 0. This is due to problems with the input system, such as dirt on the scanner, but actual manuscripts often have scratches and blemishes due to handwritten characters, uneven printer printing, etc., and the background and text do not always have constant values.

If such an input is subjected to the filter shown in FIG. 18, the result will be a mess (not shown), so generally, the input is first binarized and then the filter processing is performed. However, if 16 or more is binarized to be 1, the result will be as shown in FIG. 8(C), and noise will occur around it, and if 18 or more is to be 1, the result will be as shown in FIG. 8(d), which will result in chipping.

〔the purpose〕

The present invention has been made in view of the above-mentioned disadvantages of the prior art, and its purpose is to selectively shrink and diffuse an image in addition to the binarization level, thereby making the image difficult to read due to scratches, blemishes, etc. An object of the present invention is to provide a method for improving image quality that can make it easier to read.

〔composition〕

In order to achieve this object, the present invention is an image quality improvement method designed to improve image quality when processing line drawings and character images in digital copying machines. comprising an image diffusion means that outputs 0 only when the pixel is 0, limiting the signal to the signal of the pixel of interest; and an image shrinking means that outputs 1, not only the signal of the pixel of interest only when all pixels in the circuit are 1; The present invention is characterized in that each of the above means is switched so that when the binarization level is lowered, image diffusion is performed, and when the binarization level is raised, image contraction is performed.

Hereinafter, a detailed explanation will be given based on one embodiment of the present invention.

Images referred to in the present invention can be roughly divided into 1, characters,
There are binary images such as line drawings, 2. Halftone images such as photographs, printed halftone images, etc., and the processing with a digital copy machine is as follows: 1. Text and line drawings are MTF, edge emphasis processing and then binarized, 2. Photographs. 3. The halftone image is subjected to gradation processing after MTF correction. 3. The halftone image is subjected to gradation processing after smoothing processing to prevent moiré. Here, a Laplacian filter is used for MTF and edge enhancement, and typical coefficients are shown in FIG. 1, and smoothing coefficients are shown in FIG.

As for gradation processing, although some printers are capable of converting one dot to multiple values, most use area gradation, such as a dither method or a density pattern method.

Next, an example will be described. In this case, the characters are as follows,
When line drawings are affected by normal character processing, such as blurring, blurring, or noise, the user can selectively make the width thicker or thinner.If this mode is selected, after normal filter processing, The binarization process is reversed, and after the binarization process, this filter processing circuit is used to perform contraction and diffusion.

First, a description will be given of how contraction and diffusion are performed by coefficient processing of the Laplacian filter shown in FIG.

When the binary image in FIG. 16(C) is processed, it becomes as shown in FIG. 3, and when the binary image in FIG. 16(d) is processed, it becomes as shown in FIG.

Here, contraction is set to 0 if there is even one 0, but conversely, the pixel of interest is set to 1 only when all of them are 1. In the filter shown in Figure 1, when all 1 is input, the output is 1. Since one output cannot be obtained with any other combination, a contracted image will be obtained if an image is formed only with one output. That is, if an image is formed only at output 1 in FIG. 3, it will match that shown in FIG. 6(a).

Similarly, when diffusing, it is sufficient to form an image except when the filter output is O, that is, from the output result of FIG.
) is obtained. Furthermore, even if the smoothing filter shown in FIG. 2 is used, diffusion and contraction can be performed simultaneously using a filter output of 0.1. That is, by using two filters, for FIG.
16(a) by shrinking after diffusion for d).
) images are obtained. Therefore, by changing the filter coefficients using the processing circuit shown in FIG. 5, all of the above processing can be performed. In the figure, l is a filter, 2 is a gradation process, and 3 is a filter.
is binarization. In addition, here we have focused on shrinking and diffusing one dot at a time, but it is also possible to further increase the number of dots.
This can also be done by increasing the number of stages or increasing the size, such as from 3x3 to 5x5.

In order to improve the image quality of such characters and line drawings, the present invention selectively shrinks and diffuses the image along with the binarization level to improve the image quality. Furthermore, this processing is executed in real time and is also used in common with the MTF, edge enhancement, or smoothing filter. Furthermore, the present invention can be used not only to improve image quality, but also to process line drawings and characters, such as making the width thicker or thinner.

First, talking about the contraction and diffusion of images, contraction means that if there is a 0 in the pixel of interest and 8 pixels above, below, left, right, and diagonally, the pixel of interest is set to 0. al
On the other hand, if there is even one 1, it becomes 1. By performing diffusion, Figure 16(d) becomes Figure 6(bl).The line width increases or decreases by one, and noise is removed, and the image quality improves. It is clear that improvements can be made.

Furthermore, the processing circuit is a known block circuit as shown in FIG. In the figure, 4 is smoothing,
5 is MTF/edge emphasis, 6 is dither processing, and 7 is binarization.

As explained earlier, text images are binarized after edge emphasis, photographs are subjected to edge emphasis and then dithered, and halftone images are smoothed and then dithered. Alternatively, it is also possible to switch the processing during l-copy by specifying an area. In order to improve the image quality of characters and line drawings according to the present invention, the processing circuit has the same configuration as in FIG.
This can be realized by changing the processing procedure.

Next, other aspects of the present invention will be explained. In this aspect, in order to improve the image quality of text and line drawing processing,
Diffuse and shrink images that have been binarized using different thresholds,
Image quality is improved by performing hollow processing based on the difference. The process is also executed in real time.

First, to give an overview of this method, the pixel of interest, top, bottom, left and right,
If there is even one 0 in eight diagonal pixels, the pixel of interest is set to 0. This is contraction, as shown in Figure 8 (C1 is shown in Figure 9 (a). Conversely, if there is even one 1, it is set to 1. By diffusion, Figure 8 (d
) is shown in FIG. 9(b).

First, we will explain how to perform contraction and diffusion in real time using the Laplacian filter shown in FIG. 1 mentioned above.

When the binary image of Fig. 8 tc+ is processed with this filter,
The result will be as shown in Figure 3, and Figure 8 (dl will be as shown in Figure 4.If there is even one 0, the contraction will be set to 0.In other words, if the pixel of interest is set to l only when all 1) good.

In the filter processing shown in Figure 1, the input can only be 0 or 1, so when all inputs are 1, the output is 1, and for other combinations, the output cannot be 1.
If an image is formed only at output 1 in the figure, it will match that shown in FIG. 9(a). Similarly, during diffusion, the output becomes O only when all values are 0, and if this part is not imaged, the output result shown in Fig. 4 will be obtained, and Fig. 9 (bl) will be obtained.Furthermore, even if the smoothing filter shown in Fig. 2 is used, , when all inputs are 1, the output is 1,
When all inputs are 0, the output is 0, and similar contraction and diffusion processing can be performed. Therefore, by using these filters, for FIG. 8(e), diffusion after contraction is performed, and for FIG. 8(dl, contraction after diffusion is performed, resulting in FIG.
) is obtained, and if the edge extraction shown in FIG. 18 is performed on this, an image from which noise has been removed is obtained.

-Digital copiers for boat fishing have a Laplacian filter as shown in Figure 1 to emphasize MTF and edges, and a smoothing filter to prevent moiré (Figure 7). Contraction, expansion, and spreading can be performed from the block. - In the block diagram of Fig. 10, as in Fig. 7, 4 is smoothing, specific gravity 5 is MTF/edge emphasis, 6 is dither processing, 7 is binarization, 8 is edge extraction. In image processing of a binarized digital image, an ideal image is created by extracting the pixel of interest and a specific area around it. Processing the pixel of interest (removal of middle blocks and noise). can get. The acquisition of this image will be explained below.

As shown in FIG. 11, in order to obtain this image, means 9 for extracting a specific area and means 10 for inputting and processing part or all of the area extracted by the means 9 are required. As shown in Fig. 12, this device extracts a 5 x 5 matrix, inputs that part, and when all the manually generated pixels are "11 (dots)", the pixel of interest is also set to "1". and enter another part as shown in Figure 13,
This device performs noise removal by setting the pixel of interest to "0" when all the input pixels are O'' (blank).

14 detailing the circuit of the specific area extracting means 9 of FIG. 11;
Referring to the block diagram in the figure, binary input image data enters the latch (9-1) every clock signal. The input pixel data is passed to the next latch (9-2) and line buffer (93). By repeating this process, a 5×5 matrix centered on the pixel of interest can be extracted.

In the circuit diagram of FIG. 15, which details the circuit of the processing means 10 of FIG. Set the reference pixel so that it can be used. In this case, the middle block is the 3X3 matrix (12th
In the noise removal process, the set reference pixel and the pixel of interest, which are a 5×5 matrix (FIG. 13) near the pixel of interest, are compared and output as shown in FIG. 15.

In the case of a medium block, when the pixel of interest is "1" (dot, H level), the OR gate (10-2) is output as "1", and when it is O", the AND gate (10-1) is output. Assign “l” only when all reference pixels are “1” OR game) (
10-2) is output. In the case of noise removal, when the output of the OR gate (10-2) is "0", the AND gate (10-4) is output as "O", and when the output is "1", the OR gate (10-4) is output as "O".
If one of the reference pixels is "1" at the gate (10-3), the AND gate (10-4) outputs "1". The specific area shifts by one for each clock signal input, and the pixel of interest also shifts. This allows processing to be performed on all pixels. If there is no input to the latch portion (undefined), the corner portion of the document can also be processed by setting the signal to “0”.

〔effect〕

As shown by Unegami, according to the present invention, in a digital copying machine, the image quality of characters and line drawings can be improved by shrinking and diffusing the image along with the binarization level, and by executing this in real time. Furthermore, it is possible to provide an image quality improvement method that can be used for line drawing and character processing such as thickening or thinning the width.

[Brief explanation of the drawing]

Fig. 1 is an explanatory diagram showing the coefficients of the Laplacian filter used in the present invention, Fig. 2 is an explanatory diagram showing the coefficients of smoothing, Fig. 3 is an explanatory diagram showing the output image during contraction, and Fig. 4 is an explanatory diagram showing the coefficients of smoothing. 5 is a block diagram of a processing circuit, FIG. 6(a) is a diagram illustrating contraction image formation,
FIG. 6(b) is a diagram explaining diffusion image formation, FIG. 7 is a block diagram showing other processing circuits, FIG. 8+8) is a diagram showing figures read by a digital scanner, and FIG. A diagram showing the data, FIG. 8 (C) is an explanatory diagram showing a binarized image with 16 or more as 1, and FIG. 8 (dl is an explanatory diagram showing a binarized image with 18 or more as 1) , FIG. 9(a) is a diagram for explaining contraction image formation, FIG. 9(b) is a diagram for explaining diffusion image formation, and FIG. 10 is a block diagram showing a processing circuit.
Figure 11 is a block diagram showing the circuit configuration for obtaining an ideal image, Figure 12 is an explanatory diagram showing an extraction 5x5 matrix, Figure 13 is an explanatory diagram showing a similar 5x5 matrix, and Figure 14 is an explanatory diagram showing a similar 5x5 matrix. 15 is a circuit diagram showing details of each circuit element in FIG. 11, FIG. 16(a) is a diagram showing a figure read by a digital scanner, FIG. 16(b) is a diagram showing the data, Figure 16 (C) is an explanatory diagram showing a binarized image with 16 or more as 1, Figure 16 (dl is an explanatory diagram showing a binarized image with 18 or more as 1, Figure 17 (a) 17 (bl is a diagram showing the data, FIG. 17 (C) is a diagram showing data after filter processing, and FIG. 18 is an explanatory diagram showing filter coefficients. 1... Filter, 2... Gradation processing, 3... Binarization, 4... Smoothing, 5... MTF/edge emphasis, 6...
... dither processing, 7 ... binarization, 8 ... edge extraction, 9 ... extraction means, 10 ... processing means. Figure 1 Figure 2 Figure 8999g999-10-19999 f11M9ee9f1) e 9-Q5-1-0.5
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La, Su Ra, 7-hitter Foote Fig. 16 (α) (b) Fig. 17 Fig. 18 Fig. 16 (C) Mouth (d) Fig. 17 (b) (C)

Claims (6)

[Claims] (1) In an image quality improvement method designed to improve the image quality when processing line drawings and character images in digital copying machines, etc., the image after binarization is converted into a pixel of interest only when all surrounding pixels in the area are 0. The image diffusion means outputs 0 regardless of the signal, and the image contraction means outputs 1 regardless of the signal of the pixel of interest only when all surrounding pixels are 1. An image quality improvement method characterized in that switching is performed so that image diffusion is performed when the level is lowered, and image contraction is performed when the binarization level is raised. (2) In an image quality improvement method designed to improve the image quality when processing line drawings and character images in digital copying machines, etc., the image after binarization is converted into a pixel of interest only when all surrounding pixels in the area are 0. An image quality improvement method characterized in that after outputting 0 regardless of the signal, the output is set to 1 regardless of the signal of the pixel of interest only when all surrounding pixels are 1. (3) In an image quality improvement method designed to improve the image quality when processing line drawings and character images in digital copying machines, etc., the image after binarization is converted into a pixel of interest only when all surrounding pixels in the area are 1. An image quality improvement method characterized in that after outputting 1 regardless of the signal, the output is set to 0 regardless of the signal of the pixel of interest only when all surrounding pixels are 0. (4) In an image quality improvement method designed to improve the image quality when processing line drawings and character images in digital copying machines, etc., the image after binarization is converted into a pixel of interest only when all surrounding pixels in the area are 0. After outputting 0 regardless of the signal, there is an image contraction/diffusion means that outputs 1 regardless of the signal of the pixel of interest only when all surrounding pixels are 1, and a pixel of interest only when all surrounding pixels are 1. An image contraction/diffusion means that outputs 1 regardless of the signal of the pixel of interest, and an image contraction/diffusion means that outputs 1 regardless of the signal of the pixel of interest only when all surrounding pixels are 1, and then outputs 1 regardless of the signal of the pixel of interest only when all surrounding pixels are 0. and an image diffusion/contraction means that outputs 0 regardless of the pixel signal, and is characterized in that the image diffusion/contraction means is selected when the binary level is low, and the image diffusion/contraction means is selected when the binary level is high. Image quality improvement method. (5) In an image quality improvement method designed to improve the image quality when processing line drawings and character images in digital copying machines, etc., the image after binarization is , an image quality improvement method characterized in that processing is performed to set the value to 0 only when all pixels are 0, and then to set the value to 1 only when all pixels are 1. (6) In an image quality improvement method designed to improve the image quality when processing line drawings and character images in digital copying machines, etc., the image after binarization is , an image quality improvement method characterized in that processing is performed to set the value to 1 only when all pixels are 1, and then to set the value to 0 only when all pixels are 0.