JPH0983794A - Method and device for processing image - Google Patents

Abstract

PROBLEM TO BE SOLVED: To suppress the generation of a texture pattern and process an image with high picture quality by providing a pattern generating process and a selecting process which selects an arbitrary density pattern out of patterns generated by the pattern generating process. SOLUTION: Rasterized image data are inputted from an image input part 101. A following addition part 102 adds an error value which is diffused up to a front element and the pixel value of currently inputted image data together. A threshold value decision part 103 compares the value of the data added by the addition part 102 with plural threshold values to decide which density of density patterns to be outputted the data corresond to. Then different phase density patterns having the same density are generated by the pattern generation part 107 and an arbitrary density pattern is selected out of the generated patterns with the switching signal from a switching signal generation part 108, e.g. a signal which changes periodically, pixel by pixel, or at random.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus for outputting a density pattern of a plurality of dots from multi-valued densities of input pixels and distributing errors generated at that time to peripheral pixels.

[0002]

2. Description of the Related Art There is an error diffusion method as a method of expressing a halftone with binary dots. This method diffuses the error that occurs when each pixel is binarized to the peripheral pixels, and the halftone-processed image is excellent in the preservation of the halftone density and the image quality is also high quality. However, this error diffusion method has a problem in that the processing is more complicated than other binarization processing methods, and the processing load increases as the input resolution increases.

There is a density pattern method as another binarization processing method. This method uses n depending on the density value of the input pixel.
It outputs a binary pattern of × n. The number of gradations that can be expressed by this is determined by the pattern matrix size.

Further, for each input pixel, n × n 2
Since the value pixels are output, resolution conversion is also performed at the same time. This process is simpler than the error diffusion method, and since the resolution conversion is performed at the same time as described above, the number of input data is small with respect to the image size to be output, and the processing load is not imposed. However,
In the case of an n × n matrix, the number of gray scales that can be expressed is limited to the square of n, and when the size of the matrix is small, there is a problem that pseudo contours occur and image quality deteriorates.

Therefore, a method in which the above two binarization processing methods are combined has been proposed. This is equivalent to performing multi-valued error diffusion, and expresses the multi-values that are output as a density pattern. According to the density value of the input pixel, an n × n density pattern having the density closest to the density value is output. Further, the error generated there is diffused to the peripheral pixels that have not been processed (binarized).

According to this processing, the resolution conversion is performed as in the case of the density pattern method, so that the increase of the processing load accompanying the higher resolution can be minimized. Further, since the generated error is diffused, it is possible to suppress the generation of the pseudo contour by the density pattern method.

[0007]

However, the above-mentioned conventional example has the following problems.

By using the above-mentioned error diffusion method, dots are connected in a uniform density portion, which is visually perceived as a texture pattern. Although this depends on the diffusion coefficient and the processing method, such development is seen because the timing at which the dots are turned on is cyclical because errors are accumulated. This point is the same as in the above-mentioned conventional example, and since the texture is not a connection of dots but a connection of output patterns, it becomes visually more conspicuous and the image quality is significantly impaired.

The present invention has been made to solve the above problems, and an object of the present invention is to provide an image processing method and apparatus for suppressing the generation of texture patterns and processing images with high image quality.

[0010]

In order to achieve the above object, the image processing method of the present invention has the following steps.

That is, in the image processing method of outputting the density pattern of a plurality of dots from the multi-value density of the input pixel and distributing the error generated at that time to the peripheral pixels, the phase showing the same density from the multi-value density of the input pixel. Of the different density patterns, and a selection step of selecting an arbitrary density pattern from the patterns generated by the pattern generation step.

In order to achieve the above object, the image processing apparatus according to the present invention has the following configuration.

That is, in an image processing apparatus that outputs a density pattern of a plurality of dots from multi-valued densities of an input pixel and distributes an error generated at that time to peripheral pixels, a phase showing the same density from the multi-valued densities of the input pixels. Pattern generating means for generating different density patterns, and selecting means for selecting an arbitrary density pattern from the patterns generated by the pattern generating means.

In the above structure, density patterns having different phases showing the same density are generated from the multi-valued density of the input pixel,
By selecting an arbitrary density pattern from the generated patterns, while suppressing the occurrence of texture patterns,
It is possible to process an image with high image quality.

[0015]

Embodiments of the present invention will be described below in detail with reference to the drawings.

(First Embodiment) FIG. 1 is a view showing the arrangement of an image processing apparatus according to the first embodiment. In the figure, 101 is an image input unit, 102 is an addition unit, 103 is a threshold value determination unit, 104 is an error memory, 105 is a pattern density calculation unit, 106 is a subtraction unit, 107 is a pattern generation unit, and 108 is a switching signal generation unit. Reference numeral 109 is an image output unit.

In the above structure, rasterized image data is input from the image input unit 101. The input image data has multi-valued information, for example, monochrome 256
8-bit data is input in the case of gradation and 24-bit data is input in the case of 256 gradations for each color. In the following, in order to simplify the description, monochrome 256 gradations, that is, the pixel value is 0.
.About.255 (this is Pi).

In the next addition unit 102, the error value diffused up to the previous pixel (this is Ei) and the pixel value Pi of the currently input image data are added. Then, the threshold value judging unit 103 compares the value of the data Si (= Pi + Ei) added by the adding unit 102 with a plurality of threshold values THj, and which density of the density pattern to be output corresponds to. To judge. For example, if the density pattern to be output is 2
Assuming × 2, the number of gradations that can be expressed is 5 as shown in FIG.
Gradation (generally, the pattern matrix is n ×
If n, the number of gray levels that can be expressed is the square of n + 1.

Therefore, there are the following four threshold values.

TH0 = 51 TH1 = 102 TH2 = 153 TH3 = 204 That is, when the relationship between the above threshold value and Si is as follows:
Any one of the five gradations (a) to (e) shown in is selected.

0 ≦ Si ≦ TH 0 (a) TH 0 ≦ Si ≦ TH 1 (b) TH 1 ≦ Si ≦ TH 2 (c) TH 2 ≦ Si ≦ TH 3 (d) TH 3 ≦ Si ≦ 255 (e) Threshold The value determination unit 103 outputs the determination result from (a) to
It is output as index information indicating the density pattern of (e). For example, in the example of the above 2 × 2 pattern, the values of the numbers 0 to 4 at which pixels are printed are output as an index.

Next, the pattern density calculation unit 105 calculates the density value corresponding to the index value of the density pattern selected and output by the threshold value judgment unit 103. For example, when the pattern (c) shown in FIG. 2 is selected, the index value 2 indicating (c) is input to the pattern density calculation unit 105. At this time, since the density corresponding to one dot is 64, 2 × 64 = 128 is output. In this embodiment, the calculation is performed, but this portion may be configured by a table.

Then, in the subtracting section 106, the density value Di output from the pattern density calculating section 105 and the adding section 102 are added.
The output Si is input and the error Ei is calculated by the following equation.

Ei = Si-Di As a result, the difference between the Si input to the threshold value judging section 103 and the density value Di of the density pattern actually selected is output as an error Ei.

Next, the error Ei calculated by the subtraction unit 106
Are stored in the error memory 104 prepared for a plurality of lines for distribution to peripheral pixels, and are spread to corresponding addresses in each line memory with a predetermined weight. For this weighting, as shown in FIG. 3, a matrix having a higher weight around the target pixel is usually used. In the case of the matrix shown in FIG. 3, a memory for 3 lines is required.

The index value indicating the density pattern output from the threshold value judging unit 103 is input to the pattern generating unit 107, and a binary density pattern is output based on the value. At this time, the density pattern output is
As shown in FIG. 2, instead of one for each concentration,
Multiple patterns with different phases are output. For example, in the case of a 2 × 2 pattern as shown in FIG. 2, patterns with different phases as shown in FIG. 4 are output.

The different patterns described above are switched to patterns having the same density but different phases of dot positions by the switching signal generated by the switching signal generator 108.
The switching signal may change periodically for each pixel or may change randomly.

As a result, a binary density pattern is output from the image output unit 109, and adjacent patterns output different phases even though the density is the same.

As described above, according to the present embodiment, it is possible to suppress a texture pattern due to continuous patterns having the same density in a uniform density portion.
Further, since only the circuit for generating the signal for switching the pattern is required, the hardware configuration is simple.

(Second Embodiment) Next, a second embodiment of the present invention will be described in detail with reference to the drawings.

The second embodiment is characterized in that the dot position of the pattern of the pixel currently being processed is changed according to the peripheral density pattern.

FIG. 5 is a block diagram showing the arrangement of the image processing apparatus according to the second embodiment. Components having the same functions as those in the first embodiment described above are designated by the same reference numerals, and the description thereof will be omitted.

In the figure, reference numeral 501 is a pattern memory for storing the already output density pattern. Here, in order to simplify the explanation, it is assumed that only the density pattern output immediately before is stored. A pattern generation unit 502 reads the previous density pattern stored in the pattern memory 501. If the previous density pattern is equal to the current density pattern, the number of dots is not changed, and the phase of the dots of the pattern is output in a phase different from that of the previous pattern.

Here, the pattern stored in the pattern memory 501 is one before, but the pattern of the previous line is stored in the pattern memory 501 in order to consider the connection of the two-dimensional patterns. May be.

In this case, as shown in FIG.
Since it is possible to examine one density pattern and the density pattern immediately before the left one, it is possible to change the phase of the pattern so that the texture is less likely to occur.

As described above, according to the second embodiment, by referring to the already output pattern in the periphery, the pattern can be adaptively switched according to the situation in which the actual pattern is continuous. Texture is hard to occur.

(Third Embodiment) Next, a second embodiment of the present invention will be described in detail with reference to the drawings.

FIG. 7 is a diagram showing the structure of an image processing apparatus according to the third embodiment. Components having the same functions as those in the first embodiment described above are designated by the same reference numerals, and the description thereof will be omitted.

In the third embodiment, the threshold value judging section 103 is used.
The feature is that a plurality of threshold values to be changed in step 1 are changed randomly instead of being fixed.

When the threshold value is fixed, in the uniform density portion, the density patterns selected are the same,
The texture is generated by arranging them periodically. Therefore, as shown in FIG. 7, a random threshold value generation unit 701 is provided, the threshold value is randomly changed and output, and the threshold value determination unit 103 is input.

As a result, the selected density pattern changes randomly even in the uniform density portion, and the same density pattern does not continue, so that a texture pattern is less likely to occur.

As described above, according to the third embodiment, by changing the threshold value for selecting the density pattern, it is difficult to generate a texture pattern due to the continuation of the same density pattern, and the phase at the same density is obtained. It is not necessary to prepare different patterns of, and the amount of hardware can be reduced.

The present invention may be applied to a system including a plurality of devices such as a host computer, an interface and a printer, or may be applied to an apparatus including a single device such as a copying machine. Further, it goes without saying that the present invention can be applied to a case where the program stored in a storage medium is achieved by being supplied to a system or an apparatus.

[0044]

As described above, according to the present invention,
It is possible to suppress the occurrence of texture patterns and process an image with high image quality.

[0045]

[Brief description of drawings]

FIG. 1 is a diagram showing a configuration of an image processing apparatus according to a first embodiment.

FIG. 2 is a diagram showing gradation of a 2 × 2 density pattern.

FIG. 3 is a diagram showing a diffusion matrix of the error diffusion method.

FIG. 4 is a pattern in which the phase of a dot position of a 2 × 2 density pattern is changed.

FIG. 5 is a diagram showing a configuration of an image processing apparatus according to a second embodiment.

FIG. 6 is a diagram showing positions of peripheral density patterns according to the second embodiment.

FIG. 7 is a diagram showing a configuration of an image processing apparatus according to a third embodiment.

[Explanation of symbols]

 103 Threshold Value Judgment Unit 104 Error Memory 105 Pattern Density Calculation Unit 107 Pattern Generation Unit 108 Switching Signal Generation Unit 501 Pattern Memory 701 Random Threshold Value Generation Unit

Claims (8)

[Claims] 1. An image processing method for outputting a density pattern of a plurality of dots from multi-valued densities of an input pixel and distributing errors generated at that time to peripheral pixels, wherein a phase showing the same density from the multi-valued densities of input pixels A pattern generating step of generating different density patterns of, and among the patterns generated by the pattern generating step,
And a selecting step of selecting an arbitrary density pattern. 2. The image processing method according to claim 1, wherein the selecting step selects based on a predetermined timing. 3. The image processing method according to claim 1, wherein in the selecting step, a density pattern which has already been output is stored and a pattern different from the stored density pattern is selected. 4. The image processing method according to claim 1, further comprising the step of randomly changing a threshold value used when a density pattern is generated from the multi-value density of the input pixel. 5. An image processing apparatus for outputting a density pattern of a plurality of dots from multi-valued densities of an input pixel and distributing an error generated at that time to peripheral pixels, a phase showing the same density from the multi-valued densities of input pixels. Pattern generating means for generating different density patterns, and among the patterns generated by the pattern generating means,
An image processing apparatus comprising: a selecting unit that selects an arbitrary density pattern. 6. The image processing apparatus according to claim 5, wherein the selection unit makes a selection based on a predetermined timing. 7. The image processing apparatus according to claim 5, wherein the selecting means stores the already output density pattern and selects a pattern different from the stored density pattern. 8. The image processing apparatus according to claim 5, further comprising means for randomly changing a threshold value used when generating a density pattern from multi-valued densities of the input pixels.