JPH0595474A - Picture processor - Google Patents

Abstract

PURPOSE:To improve the picture quality at a highlight part and to improve the picture quality at a low density part by binarizing low-order data of a noted picture element in terms of probability. CONSTITUTION:A computing element 24 divides noted multi-value picture data into high-order data and low-order data. The low-order data are binarized by a comparator 25 by using a normalized uniform random number generated by a random number generator 26 as a threshold level. Then the binarized data are added to the high-order data of a picture signal of the noted picture element at an adder 22, and binarized at a comparator 18 by using a weighted mean value of plural picture elements in the vicinity of the noted picture element as a threshold level based on binary data of binarized picture elements prior to the processing of the noted picture element by an arithmetic unit 600. In this case, a density error caused when the picture elements are binarized with a subtractor 17 - an adder 22 is shared to unbinarized picture elements around the noted picture element to preserve the density.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus for quantizing multi-valued image data into binary data.

[0002]

2. Description of the Related Art As a pseudo intermediate processing method used in digital copying machines, facsimile machines, etc.
An image processing apparatus such as "-210959" has been proposed. In this image processing apparatus, the pixel of interest is binarized into black or white by using the binary data of the pixel which has already been binarized in the vicinity of the pixel of interest, and the error generated when binarizing the pixel of interest is detected. An operation of adding to multi-valued data of unbinarized pixels in the vicinity is sequentially performed for each pixel.

That is, the average density is calculated using only the binary data that has been binarized, and the input multi-valued data is binarized using the average density as a threshold. Therefore, it is possible to perform binarization with a relatively small amount of processing, and since the error between the input multi-valued data and the average density that occurs when binarizing the input multi-valued data is corrected, an image with good gradation can be obtained. The binarization method has the advantage of being obtained.

[0004]

However, in the above-described binarizing method, since the pixel of interest is binarized depending on the conditions of the neighboring pixels, it is unavoidable that dots are connected in the highlight portion. There is a problem that the image quality of the highlight part is deteriorated. Further, there is a problem that the image quality is deteriorated in the low density portion.

[0005]

The present invention has been made to solve the above-mentioned problems, and has the following structure as one means for solving the above-mentioned problems. That is, in an image processing device for quantizing multi-valued image data into binary data,
Mean value calculating means for obtaining a weighted average value of a plurality of pixels in the vicinity of the target pixel based on binary data of the pixel already binarized before the target pixel, and a random number for generating a standardized uniform random number Pay attention to the generating means, the lower binarizing means for binarizing the lower data of the pixel of interest based on the random number value generated by the random number generating means, and the lower data binarized by the lower binarizing means. An adding means for adding to the upper data of the image signal of the pixel and an upper binarizing means for binarizing the upper data of the image signal of the pixel of interest based on the plurality of weighted average values obtained by the average value calculating means. Prepare

[0006]

In the above structure, the lower-order data of the target pixel is stochastically binarized to improve the image quality in the highlight area and the image quality in the low-density area.

[0007]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment according to the present invention will be described in detail below with reference to the drawings.

[0008]

[First Embodiment] FIG. 1 is a block diagram of an image processing apparatus according to an embodiment of the present invention. In FIG. 1, an input sensor unit 101 is composed of a photoelectric conversion element such as a CCD and a driving device that operates the photoelectric conversion element, and performs an operation of reading a document.
The document image data read by the input sensor unit 101 is multivalued analog image data. This multivalued analog image data is sequentially sent to the A / D converter 102, and the analog data of each pixel is converted into corresponding multivalued digital data. Next, in the correction circuit 103, correction processing such as shooting correction is performed in order to correct sensitivity unevenness of the CCD sensor and illuminance unevenness due to the illumination light source.

The multi-valued image data input to the subsequent binarization circuit 104 is quantized into binary data by a binarization method described later. The printer 105 is a printer configured by a laser beam or inkjet method,
The dot is ON / OFF controlled based on the binary data sent from the binarization circuit 104, and the image is reproduced on the recording paper.

2 and 3, the binarization circuit 1 shown in FIG.
The detailed block configuration of No. 04 is shown. In FIGS. 2 and 3, reference numerals 1 and 2 denote binary image data that has been binarized.
A line memory for storing lines, 3 to 12 and 21 are D-type flip-flops DF / F for delaying image data by one pixel, and 13 and 14 are weighted averages of predetermined areas from binary image data around a pixel of interest. It is an arithmetic unit for obtaining a value.

Reference numeral 15 is a comparator for comparing the quantized data from the adder 22 with a predetermined value β, and 16 is one of a plurality of weighted average values from the arithmetic units 13 and 14 based on the signal from the comparator 15. A selector that selects one of them as a threshold,
Reference numeral 17 is a subtractor that calculates the difference between the threshold value output from the selector 16 and the quantized data of the target pixel, and 18 is the selector 1
The comparator 19 compares the threshold value output from 6 with the quantized data of the pixel of interest from the adder 22 to binarize the pixel of interest, and 19 is the quantized data of the pixel of interest output from the subtractor 17. An error ROM that calculates error data based on a difference from a threshold value, 20 is a line memory that stores one line of error data from the error ROM 19, and 22 is a quantum from an adder 23 for performing density correction on the quantized data. An adder for adding the error data from the line memory 20 and the DF / F 21 to the digitized data, and 23 is an adder for adding the binarized lower bit data to the upper bit data of the pixel and outputting the quantized data. is there.

Further, 24 is an arithmetic unit for dividing the multi-valued pixel data input from the correction circuit 103 into upper bit data and lower bit data, and 25 is a threshold value output from the random number generator 26 and an arithmetic unit 24. A comparator for binarizing the lower bit data by comparing it with the lower bit data, 26
Is a random number generator that generates uniform random numbers. The principle of the binarization method in this embodiment having the above configuration will be described below.

(1) shown in FIG. 4 shows the multi-value density for each pixel of the input image. In (1) of FIG. 4, f (i, j) represents multi-valued image data of the input image at the target pixel position to be binarized, and takes a value of "0 to 255" in an 8-bit configuration. Further, the image data at the pixel position above the broken line has already been binarized, and when the binarized image of the pixel of interest is performed,
After that, the same binarization process as f (i + 1, j), f (i + 2, j), ... Is sequentially performed.

FIG. 4B is a diagram showing the binarized image data. In FIG. 4B, B (i, j) is 2 of the target pixel.
The data (0 or 1) after binarization is shown. The portion surrounded by the broken line is pixel data that has already been binarized when the pixel of interest is processed, and these are used in the binarization process of the pixel of interest. FIG. 4C is a diagram showing weighting. R ₁ R ₂ is an example of a weighting mask for obtaining the average density and is represented by a matrix of 5 × 3 and 3 × 2 sizes.

Here, as the weights for the unbinarized pixels, R ₁ (0,0) = R ₁ (1,0) = R ₂ (2,0) = 0, R ₂ (0,0) = R Used as ₂ (1,0) = 0. Then, first, 8-bit input image data f (i,
j) is divided into upper 6-bit data f _H (i, j) and lower 2-bit data f _L (i, j). The lower-order data is binarized to 0 or 1 using a uniform random number in which values 0 to 3 occur with the same probability as a threshold. Binarized lower data B _L (i, j) is upper data
It is added to f _H (i, j) to obtain quantized data h (i, j).

Next, the weighted average densities m ₁ (i, j) and m ₂ (i, j) in the vicinity of the pixel of interest are obtained from the pixel data that has already been binarized by the following equation. Depending on the quantized data h (i, j) of the pixel of interest and the binarization correction value E (i, j) assigned to that pixel, either m ₁ (i, j) or m ₂ (i, j) select. Here, β is a predetermined value for determining whether or not it is a low density portion, and is set to about 10% of the maximum density value. Since the upper 6 bits are used in this embodiment, the maximum density value is 64. Therefore, the value corresponding to 10% thereof is used. That is β =
It becomes 6.

The quantized data h (i, j) of the target pixel is the selected m (i, j) and the binary correction value assigned to the target pixel.
It is binarized according to the following equation using E (i, j). Further, the correction value of the binarization error generated at this time is calculated in the same manner.

E ₁ (i + 1, j) = E ₂ (i, j + 1) = {h (i, j) + E (i, j) -m (i, j)} / 2 (4 ) E ₁ (i + 1, j) is the correction value assigned to the pixel (i + 1, j) next to the pixel of interest, and E ₂ (i, j + 1) is the pixel one line after the pixel of interest. This is the correction value assigned to (i, j + 1). The binarized correction value E (i, j) assigned to the pixel of interest is obtained by the following equation, and is the pixel one pixel before the pixel of interest by the above method.
Error E ₁ (i, j) generated when binarizing (i-1, j) and pixel (i, j-1) one line before the pixel of interest binarized It is the sum with the error E ₂ (i, j).

E (i, j) = E ₁ (i, j) + E ₂ (i, j) (5) The above operation is sequentially performed for each pixel to binarize the entire image. As described above, in the lower bit, the density is moderately dispersed by quantizing the random number as the threshold value, and there is an effect that the connection of the dots in the low density portion can be effectively prevented. Further, since the density becomes the quantization probability, the density is statistically stored.

In the upper bit, binarization is performed on the basis of the peripheral pixel information and the binarization error is corrected so that the density is preserved and an image excellent in gradation and resolution is obtained. At low densities, widening the average density calculation area is effective in preventing dot connection, and together with the effect of using the random numbers, high-quality image quality in the highlight portion can be obtained. In this case, a line memory is required for a wide average density calculation area for the low density portion, but by using the above method, the memory for storing the correction amount of the binarization error is a high-order bit. Since it only requires minutes, it can be realized without increasing the total memory.
The binarization process of the pixel of interest (i, j) based on the principle of the binarization method described above in the configuration of the present embodiment shown in FIGS. 1 to 3 will be described below.

In the line memories 1 and 2 shown in FIG. 2, the comparator 18 of FIG.
Binary data is stored. When the pixel of interest is binarized, the line memory 2 outputs the binary data B (i + 2, j-1) one line before, and the line memory 1 outputs the binary data B (i +) two lines before. 2, j-2) is output. DF / F 3 to 12 each output data delayed by one pixel. Ie D
F / F 3 is B (i + 1, j-2), DF / F 4 is B (i, j-2), and DF / F 5 is
B (i-1, j-2), DF / F 6 is B (i-2, j-2), DF / F 7 is B (i + 1,
j-1), DF / F 8 is B (i, j-1), DF / F 9 is B (i-1, j-1), D
F / F 10 is B (i-2, j-1), DF / F 11 is B (i-1, j), DF / F
12 outputs B (i-2, j), respectively.

The binary data from these DF / Fs 3 to 12 are input to the calculator 13. Of these, DF / F 7
B (i + 1, j-1), DF / F 8 B (i, j-1), DF / F 9
B (i-1, j-1) from DF / F 11 and B (i-1, j) from DF / F 11 are also input to the calculator 14. The arithmetic unit 13 and the arithmetic unit 14 calculate the weighted average density value m ₁ (i, j) indicated by the symbol A and the weighted average density value indicated by the symbol B based on the respective weight masks from the binary data in the vicinity of the pixel of interest. Figure 3 by calculating m ₂ (i, j)
To the selector 16.

On the other hand, the multi-valued data f (i, j) of the pixel of interest sent from the correction circuit 103 is input to the calculator 24 of FIG. The arithmetic unit 24 divides the input 8-bit multivalued data f (i, j) of the target pixel into upper 6-bit data f _H (i, j) and lower 2-bit data f _c (i, j) and outputs them. To do. The random number generator 26 also generates a uniform random number having a value of 0 to 3 for each pixel.

The comparator 25 binarizes the lower 2-bit data f _L (i, j) using the value of the random number 0 to 3 generated by the random number generator 26 as a threshold, and the lower binary data B _L. Output (i, j). The adder 23 outputs the bit data from the arithmetic unit 24.
The quantized data is obtained by adding f _H (i, j) and the lower binary data B _L (i, j) which is binarized to 1 or 0 from the comparator 25.
Output h (i, j).

The adder 22 adds the error correction data E ₁ from the line memory 20 and DF / F 21 to the quantized data h (i, j).
Add (i, j) and E ₂ (i, j) and output h (i, j) + E (i, j). The comparator 15 compares the error-corrected quantized data h (i, j) + E (i, j) with a predetermined value β, and outputs a select signal to the selector 16 based on the comparison determination result. Output.

Based on the select signal sent from the comparator 15, the selector 16 weights the average density value m ₁ (i, j) indicated by the symbol A and the weighted average density value m ₂ indicated by the symbol B.
Select one of (i, j) and output it as the threshold m (i, j). The subtracter 17 calculates the difference between the error-corrected quantized data h (i, j) + E (i, j) from the adder 22 and the threshold m (i, j). Further, the comparator 18 binarizes the error-corrected quantized data h (i, j) + E (i, j) using m (i, j) as a threshold, and the code C
The binary data B (i, j) indicated by is output. This binary data B
(i, j) is sent to the printer 105 and also input to the line memory 2 and the DF / F 11 shown in FIG. 2 and becomes peripheral pixel information for pixels to be binarized in the future.

On the other hand, h (i, j) + E output from the subtractor 17
(i, j) -m (i, j) is input to the error ROM 19. Error R
The OM 19 uses the error data E ₁ (i
Outputs + 1, j), E ₂ (i, j + 1). E ₁ (i + 1, j) is DF / F 21
Is delayed by one pixel and assigned to pixel (i + 1, j), and E ₂ (i, j + 1) is stored in the line memory 20 and assigned to pixel (i, j + 1) one line later. ..

By repeating the above series of processing, the binarization processing of the image data is sequentially performed for each pixel. By performing the binarization process described above and binarizing the lower data of the pixel of interest stochastically, the way dots are hit in the highlight portion is appropriately dispersed, and the image quality can be improved.

[0029]

Second Embodiment In the first embodiment described above, only the lower two bits of the pixel of interest are binarized using random numbers,
The binarized data and the upper bits were added. However, the present invention is not limited to the above example, and may be controlled so that a random number is processed according to the level of the upper bit of the pixel of interest. Second control according to the present invention controlled in this way
Examples will be described below.

The second embodiment has substantially the same construction as that of the first embodiment described above, and is slightly different from the construction of the first embodiment shown in FIG. 3 but has the construction shown in FIG. Figure 1
The parts shown in FIG. 2 are the same as those in the first embodiment. In other configurations, the same components as those in the first embodiment are designated by the same reference numerals, and detailed description thereof will be omitted. 5 is different from the first embodiment shown in FIG. 3 in that the arithmetic unit 424 and the comparator 42 are different.
5, only the configuration of the arithmetic unit 426 and the random number generator 427.

In the second embodiment, as shown in FIG. 5, the calculator 424 converts the multi-valued data f (i, j) of the 8-bit pixel of interest sent from the correction circuit 103 into the high-order bit data. And lower bit data. The upper bit and the lower bit may be distributed to the upper 4 bit data and the lower 4 bit data, or may be distributed to the upper 2 bit and the lower 6 bit, contrary to the first embodiment.

After that, in the second embodiment, the high-order bit data is input to the calculator 426 together with the random number value generated by the random number generator 427. The output from the calculator 426 is
It serves as a threshold for binarizing the lower bit data in the comparator 425. The arithmetic unit 426 outputs the output value (2 bits of the lower bit data) in the low density area where the upper bit data from the random number generator 427 becomes 0 according to the value of the upper bit data.
The dot printing probability is reduced by increasing the value of the random number which is the threshold for binarization, and the connection of dots in the highlight portion is suppressed.

By controlling as described above, it is possible to change the way the peripheral pixel information is transmitted by changing the average density calculation mask in the low density portion, and it is possible to prevent dots from being spotted in close proximity. It is also possible to improve the image quality in the low density portion.

[0034]

Third Embodiment In the first embodiment described above, a plurality of weighted average values are calculated, and one of the plurality of weighted average values is selected as the threshold value based on the quantization level of the pixel of interest. However, the same effect can be achieved by configuring the threshold value directly based on the quantization level of the pixel of interest. A third embodiment according to the present invention configured to directly calculate the threshold value based on the quantization level of the pixel of interest will be described below.

FIG. 6 is a block diagram of the binarization circuit of the third embodiment according to the present invention, and the other parts are the same as the first embodiment shown in FIG.
The configuration is the same as that of the embodiment. The same components as those in the first embodiment are designated by the same reference numerals and detailed description thereof will be omitted. In the third embodiment, as shown in FIG. 6, the select signal from the comparator 14 is directly input to the arithmetic unit 600 instead of the selector 16 to calculate a weighted average value as a threshold value. The arithmetic device 600 has the functions of the arithmetic units 13 and 14 and the selector 16 of the first embodiment and the function of calculating a weighted average value serving as a threshold value including the select signal from the comparator 14 described above. It is a configuration having both of them, and by making the arithmetic device 600 have a table configuration, it is possible to perform an extremely high-speed operation.

Even with the above configuration, by probabilistically binarizing the lower data of the pixel of interest, the way dots are hit in the highlight portion is appropriately dispersed, and the image quality can be improved. According to the above-described embodiments, the lower bits are stochastically quantized, and the weighted average density value calculation area is widened in the low density portion. , Dot connection that occurs in the low density portion is prevented, and a high quality image can be obtained.

In the above description, in the first embodiment, only the lower two bits of the pixel of interest are randomized by using random numbers.
The binarization process was performed and the binarized data and the upper bit were added. In the second embodiment, an example in which control is performed so that random numbers are processed in the low-density area according to the level of the upper bit of the pixel of interest has been shown, but these are not provided separately and independently. The structure having both the function of the first embodiment and the function of the second embodiment is provided. In the highlight portion, as in the first embodiment, in the low concentration region as in the second embodiment,
It may be configured to perform the binarization process. By performing the optimum binarization processing by switching in this way, a very high quality binarized image can be obtained.

The present invention may be applied to a system composed of a plurality of devices or an apparatus composed of a single device. Further, it goes without saying that the present invention can also be applied to the case of being achieved by supplying a program to a system or an apparatus.

[0039]

As described above, according to the present invention, by binarizing the lower data of the pixel of interest stochastically, the way dots are hit in the highlight portion is appropriately dispersed.
The image quality can be improved.

[Brief description of drawings]

FIG. 1 is a block diagram showing the configuration of an image processing apparatus according to an embodiment of the present invention.

[Fig. 2]

FIG. 3 is a detailed circuit diagram of the binarization circuit shown in FIG.

FIG. 4 is a diagram showing an example of a multi-valued image for each pixel, a binarized image, and an average density calculation weighting mask in the present embodiment.

FIG. 5 is a circuit diagram showing a portion different from the configuration of the first embodiment in the binarization circuit of the second embodiment according to the present invention.

FIG. 6 is a detailed circuit diagram of a binarizing circuit according to a third embodiment of the present invention.

[Explanation of Codes] 1,2,20 Line Memory 3-12,21 D Type Flip Flop DF / F 13, 14, 24, 424, 426 Operation Unit 15, 18, 25, 425 Comparator 16 Selector 17 Subtractor 19 Error ROM 23 Adder 26,427 Random number generator 101 Input sensor unit 102 A / D converter 103 Correction circuit 104 Binarization circuit 105 Printer 600 An arithmetic unit.

Claims (6)

[Claims] 1. An image processing apparatus for quantizing multi-valued image data into binary data, wherein a plurality of pixels in the vicinity of the target pixel are weighted based on binary data of pixels already binarized before the target pixel. Average value calculating means for obtaining the average value, random number generating means for generating a standardized uniform random number, and lower order data of the pixel of interest based on the random number value generated by the random number generating means. Lower-order binarizing means, adding means for adding the lower-order data binarized by the lower-order binarizing means to the upper-order data of the image signal of the pixel of interest, and a plurality of weighted averages calculated by the average value calculating means. An image processing apparatus comprising: an upper binarization unit that binarizes upper data of an image signal of a pixel of interest based on a value. 2. A correction means for preserving the density by distributing a density error generated when the upper binarizing means binarizes the upper data of the target pixel to the unbinarized pixels around the target pixel. The image processing apparatus according to claim 1, further comprising: 3. The upper binarization means includes a selection means for selecting one of a plurality of weighted average values obtained by the average value calculation means, and the weighted average value selected by the selection means is used as a threshold value. The image processing device according to claim 1, wherein the image processing device is binarized as. 4. The image processing apparatus according to claim 3, wherein the selecting means selects one of the weighted average values based on multi-valued data of the target pixel before binarization. 5. The image processing apparatus according to claim 1, wherein the average value calculating means calculates the average value based on a plurality of weight masks having different sizes. 6. The lower binarizing means binarizes the generated random number value of the random number generating means as a threshold value.
The image processing device described.