JPH03186063A - Picture processor - Google Patents

Abstract

PURPOSE:To prevent a phenomenon, which is generated at the part of low picture density, to close and hit dots by varying a threshold value for error dispersion stop corresponding to the density of an input picture element. CONSTITUTION:Read picture data are successively converted to digital data by an A/D converter 2 and signals 100, which are corrected by shading correction, etc., are simultaneously outputted to a threshold value setting circuit 4 for error dispersion stop and a binarizing processing circuit 5. In the threshold value setting circuit 4, a threshold value for error dispersion stop is set by the corrected signal 100 and on the other hand, in the binarizing processing circuit 5, a binarizing processing is executed to the corrected signal 100. Then, an error dispersion processing at the time of binarizing is executed by a threshold value signal 200 outputted from the threshold value setting circuit 4. Namely, the variably set threshold value corresponding to input picture element data is compared with binarizing error and according to the compared result, error dispersion is executed. Thus, the phenomenon to close and hit the dots is prevented from being generated in the part of the low picture density.

Description

Detailed Description of the Invention [Field of Industrial Application] The present invention relates to an image processing device, and in particular, binarizes a pixel of interest based on the average density value of a predetermined area, and converts the generated binarization error to surrounding pixels. The present invention relates to an image processing device that can diffuse images and store the density of images.

[Prior Art] In recent years, as a binarization method for reproducing halftones in image processing devices such as digital printers and facsimile machines, error diffusion methods have been used to disperse errors generated in the binarization process to surrounding pixels. A method called ε is attracting attention.

[Problems to be Solved by the Invention] A similar method called the average concentration preservation method has been proposed. This average density preservation method binarizes the pixel of interest using the average density calculated from the arrangement of dots in the already processed area around the pixel of interest as a threshold, and converts the binarization error that occurs at this time into surrounding pixels. This is a method of preserving concentration by dispersing it. However, if the binarization error is larger than a predetermined threshold, error diffusion processing is stopped (adaptive error correction).
is configured to do so.

However, in the above average concentration preservation method, since it is determined whether or not to perform error diffusion processing based on a predetermined threshold value,
For example, in areas where the density of the original is low, dots are generated close to each other in the reproduced image, and these dots are connected in a linear manner, resulting in a significant deterioration of the quality of the image. In addition, there is also the drawback that white noise is generated in areas where the document density is high because no dots are printed.

The present invention was made to solve the above problems, and
By varying the threshold for stopping error diffusion according to the input pixel density, it is possible to prevent the phenomenon of dots being placed close to each other, which occurs in areas with low image density, and also to reduce the image density. It is an object of the present invention to provide an image processing device capable of preventing white noise caused due to no dots being struck in high areas.

[Means for Solving the Problems] In order to achieve the above object, an image processing device of the present invention has the following configuration. That is, the image processing device is capable of binarizing a pixel of interest based on the average density value of a predetermined area, diffusing the binarization error that occurs to surrounding pixels, and storing the density of five images. 2 according to the concentration of
a setting means for variably setting a threshold value for specifying whether or not to perform diffusion of the digitization error; a comparison means for comparing the threshold value set by the setting means with the binarization error; and a binarization means for performing error diffusion and binarization processing according to the result.

[Operation] In the above configuration, when binarizing the pixel of interest based on the average density value of a predetermined area and diffusing the generated binarization error to surrounding pixels, the settings are variably set according to the input pixel data. The threshold value and the binarization error are compared, error diffusion is performed according to the result, and the binarization process is performed.

[Embodiment] Hereinafter, a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a schematic block diagram showing the configuration of an image processing apparatus in this embodiment.

First, image data read by an input device 1 including a charging conversion element such as a CCD and a drive system for scanning it is sequentially sent to an A/D converter 2. The converter 2 converts the analog data of each pixel into, for example, 8-bit digital data, which is then quantized into data having 256 levels of gradation.

Next, in the correction circuit 3, corrections such as shading correction are performed by digital calculation processing in order to correct unevenness in sensitivity of the CCD sensor and unevenness in illuminance due to the illumination light source. Then, the corrected signal (corrected signal) 100 is simultaneously output to the threshold value setting circuit 4 for stopping error diffusion and the binarization processing circuit 5. This threshold setting circuit 4 sets a threshold for stopping error diffusion using the corrected signal 100 from the correction circuit 3, and outputs a threshold signal 200.

On the other hand, the binarization circuit 5 binarizes (quantizes) the corrected signal (8-bit multivalued image data) 100 output from the correction circuit 3 into a 1-bit binary signal 300. , an error diffusion process during binarization is performed using the threshold signal 200 output from the threshold setting circuit 4, and an output device 6 configured with a laser beam printer, an inkjet printer, etc. value signal 300
Image formation is performed by turning on and off the dots.

FIG. 2 is a block diagram showing details of the above-mentioned threshold value setting circuit 4 for stopping error diffusion.

In the figure, a corrected signal 10 output from the correction circuit 3
0 is input to the ROM 7, and the corresponding value is the threshold signal 200.
Table 1 is an example showing the relationship between input and output.

Margin Table 1 Below, four threshold values are used in the ROM 7 as described above, but more threshold values may be used. At that time, it is better to lower the threshold value in areas where the image density is low.

FIG. 3 is a block diagram showing the configuration of the binarization circuit 5 described above.

In the figure, a corrected signal 10 input from the correction circuit 3
0 (image density of interest) is added by the adder 8 to the binarization error EIJ (sum of errors allocated to the pixel of interest) stored in the error buffer memory 9, and as a result, the error corrected signal 210 is output.

The error-corrected signal 210 is then input to the comparator 10, and the average concentration signal 220 calculated by the average concentration calculator 12
compared to Here, if the error corrected signal 210 is larger than the average density signal 220, it is 1", and if it is smaller, it is "O".
is output as a binary signal 300. Further, this binary signal 300 is input to the output device ff16 and also to a predetermined pixel position in the binary memory 11.

Next, the average density calculator 12 weights (αXL) the binary memory 11 to calculate an average density signal 220. This average density is the sum of binary data multiplied by a weighting coefficient. FIG. 4 shows an example of the weighting coefficient (αKL). However, "*" corresponds to the pixel position of interest (I, J).

This average density signal 220 is input to the above-mentioned comparator 10 as well as to the arithmetic unit 13.

The arithmetic unit 13 also includes the above-mentioned error corrected signal 210.
is entered. Here, the difference between these two signals is calculated and outputted as a signal 230 (ΔE1). This signal 230 is then input to the comparator 14 and the threshold signal 200 outputted from the threshold setting circuit 4 described above. compared to As a result, if the signal 230 is larger than the signal 200, "O" (stop error diffusion) is output, and if the signal 230 is equal to or smaller than the signal 200, the same value is output as the signal 240. This signal 240 is input to the weighting circuit 15, where it is weighted (β□) and then the error buffer memory 9
It is added to the error at a predetermined pixel position within. FIG. 5 shows an example of the weighting coefficient (β□), where “*” corresponds to the pixel position of interest (I, J).

By repeating the above operations, binarization processing using the average density preservation method is performed.

The reason why the dots can be prevented from connecting in this way can be considered as follows.

For example, in an extreme case, the threshold for stopping error diffusion is “O”.
Consider the case of Then, error diffusion does not occur, so
For pixels with low image density, we check the binarized data applied to the weighting coefficients around the pixel of interest, and if there is a signal that turns on the dot, the pixel of interest will always be "0". This means that the weighting coefficient plays a higher role in binarization. In other words, with such a configuration, no dots will be placed around the area where the dots were placed in areas with low density.

For the above reasons, by lowering the threshold for stopping error diffusion, it is possible to prevent dots from being placed close together in areas of low image density.

It is also possible to prevent white noise that occurs when dots are not placed in areas with high image density.

[Other Embodiments J Next, other embodiments according to the present invention will be described below with reference to the drawings.

In this embodiment, a case will be described in which a part of the threshold value setting circuit 4 described above is changed.

A signal 100 output from the correction circuit 3 is input to the ROM 7. In this ROM7, the threshold signal 200 is calculated by the following formula.
is output.

(Signal 200) = (Signal 100) / (Ll + L2) ... (If (Signal 100)≦128) (Signal 200
) = (255 - (signal 100)) / (L1 + L2) ... (if (signal 100) > 128) Here, L
1=2. L2=40.

Although the relationship between the signal 100 and the signal 200 is shown in FIG. 6, this is just an example, and the relationship is not limited to this as long as the relationship that the signal 200 becomes smaller as the signal 100 approaches "O" or '255' is satisfied. .

With the above configuration, it is possible to set a threshold for stopping error diffusion, as in the case of the above-described embodiment.

[Effects of the Invention] As explained above, according to the present invention, by setting the threshold for stopping error diffusion according to the input pixel density, dots that occur in areas with low image source intensity can be brought closer to each other. This can prevent the phenomenon of being hit.

In addition, it is possible to prevent white noise that occurs when dots are not printed in areas with high image density.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing the configuration of the image processing device in this embodiment, FIG. 2 is a block diagram showing the configuration of the threshold setting circuit 4, and FIG. 3 is a block diagram showing the detailed configuration of the binarization circuit 5. , FIG. 4 is a diagram showing weighting coefficients for average density calculation, FIG. 5 is a diagram showing weighting coefficients for error diffusion calculation, and FIG. 6 is a diagram showing the relationship between signal 100 and signal 200 in another embodiment. be. In the figure, 1... input device, 2... A/D converter, 3...
. . . Correction circuit, 4 . . . Threshold value setting circuit, 5 . . . Binarization circuit, 6 . . . Output device. Patent applicant Canon Co., Ltd. Figure 4 Figure 5 Factors

Claims (1)

[Claims] An image processing device capable of binarizing a pixel of interest based on the average density value of a predetermined area, diffusing the generated binarization error to surrounding pixels, and preserving the density of the image. , a setting means for variably setting a threshold value for specifying whether or not to perform diffusion of the binarization error according to the density of input pixel data; An image processing device comprising a comparison means for making a comparison, and a binarization means for performing error diffusion and binarization processing according to the result of the comparison means.