JP2001136389A - Picture processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a picture processor for improving the contrast of a halftone picture by storing a threshold for dither processing and a threshold for error diffusion processing in a common data table. SOLUTION: In this picture processor 21 where a dither picture processing means and an error diffusion picture processing means can be selected and used, plural thresholds set as matrix data by the dither picture processing means and a threshold set by the error diffusion picture processing means are stored in a common threshold value register 23 and when picture processing is executed by the error diffusion picture processing means, the threshold is periodically varied for each processing pixel.

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, and more particularly to an image processing apparatus for processing a halftone image by an error diffusion method.

[0002]

2. Description of the Related Art Recently, in an information-oriented society, devices handling image data are increasing. In an apparatus that handles such image data, an image processing apparatus that converts pixel data read by a scanner or the like into a binary image signal is required. Recently, the image processing apparatus handles not only monochrome binary images such as characters but also halftone images such as photographs. Therefore, conventionally, as a processing method of a halftone image, a level of each pixel of multi-valued pixel data is compared with matrix data in which a plurality of predetermined threshold values are set, and binarization processing is performed based on the comparison result. A dither method for outputting binary pixel data to represent a halftone image, and converting a binary error between output pixel data and input pixel data quantized for each pixel of multi-value pixel data into peripheral pixel data. There is an error diffusion method in which a result of the diffusion is binarized based on a predetermined set threshold value, and output binary pixel data is output to express a halftone image. Attention has been focused on an error diffusion method that achieves a balance between resolution and resolution. For example,
Japanese Patent Application Laid-Open No. 64-32765 discloses a dither matrix for performing binarization of the dither method and a threshold value for simple binarization for performing binarization of the error diffusion method. It discloses a matrix memory having a fixed threshold value at the time of error diffusion processing.

[0003]

However, in such a conventional error diffusion system, when the input pixel data is at all black levels or all white levels, no binarization error occurs, If the accumulated error of the pixel data up to that time is stored and the threshold value for binarization is always constant, a texture peculiar to error diffusion (an image tailing phenomenon that occurs when error diffusion is not sufficient) occurs. To eliminate this, there is a method of periodically changing the threshold value of binarization. However, a white point is generated near a black background, a black point is easily generated near a white background, and an output image is easily blurred. There was a problem.

[0004] In addition, for example, Japanese Patent Laid-Open Publication No.
In the error diffusion process executed by the image processing apparatus described in Japanese Patent Application Publication No. 72-72, the remainder (after the decimal point) of an error generated when a binarization error is obtained by a weighting operation.
Is added to the next pixel data to be correlated, corrected, the corrected pixel data is binarized by a certain threshold value, and the process of storing the input image density and the output image density and reproducing the image is performed. However, this apparatus cannot remove the above-mentioned texture peculiar to error diffusion.

Accordingly, an object of the present invention is to provide an image processing apparatus which stores a threshold value for dither processing and a threshold value for error diffusion processing in a common data table to improve the contrast of a halftone image. I do.

[0006]

According to the first aspect of the present invention,
The level of each pixel of the multi-valued pixel data input for each line is compared with matrix data in which a plurality of predetermined threshold values are set, and binarization processing is performed based on the comparison result to output binary pixel data. A dither image processing means for outputting and expressing a halftone image, and an error between output pixel data quantized for each pixel of multi-valued pixel data input for each line and input pixel data diffused to peripheral pixel data Error diffusion image processing means for binarizing the result based on a predetermined threshold value and outputting output binary pixel data to express a halftone image; and dither image processing means and error diffusion In an image processing apparatus which can be used by selecting an image processing means, a plurality of threshold values set as matrix data by the dither image processing means and setting by the error diffusion image processing means Stores the the thresh value to a common data table, when performing image processing in said error diffusion image processing unit, is characterized by periodically changing the thresh value for each processed pixel.

[0007]

According to the first aspect of the present invention, in an image processing apparatus which can select and use a dither image processing means and an error diffusion image processing means, a plurality of threshold values and error values set as matrix data by the dither image processing means are provided. The threshold value set by the diffusion image processing means is stored in a common data table, and when the error diffusion image processing unit performs image processing, the threshold value is periodically changed for each processing pixel.

Accordingly, it is possible to reduce the hardware configuration of the image processing apparatus including the dither image processing means and the error diffusion image processing means, to eliminate the occurrence of texture peculiar to error diffusion, and to reduce the image quality of the halftone image. Can be improved.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be specifically described below based on embodiments.

FIGS. 1 to 4 show an embodiment of a facsimile apparatus to which the image processing apparatus according to the first aspect of the present invention is applied.

FIG. 1 is a block diagram of a facsimile apparatus 1. The facsimile apparatus 1 includes an image sensor 2, A
It comprises a / D converter 3, a timing controller 4, a RAM 5, a digital image processing unit 6, and the like.

The image sensor 2 converts the reflected light from the original into an electric signal and outputs a predetermined analog signal to the A / D converter 3. The A / D converter 3 is input from the image sensor 2. The analog signal is converted into a predetermined digital signal and output to the digital image processing unit 4.

The timing controller 4 outputs a control signal for controlling the operation timing of each section to each section,
(Random Access Memory) 5 holds and updates various kinds of reference data, and holds and updates error data necessary for error diffusion processing described later.

As shown in FIG. 2, the digital image processing section 6 comprises an error calculation section 7, a density correction section 8, a binarization section 9, a binarization error generation section 10, and a latch section 11.
The error diffusion processing unit is configured as a whole.

The error calculator 7 calculates an error amount for the current pixel based on the previous binarized error data stored in the RAM 5 and outputs the calculation result to the density corrector 8.

The density correction section 8 adds the error amount calculation result input from the error calculation section 7 to the read data (digital signal) input from the A / D converter 3 and binarizes the density correction data. And outputs the result to the binarization error calculating unit 10.

The binarization section 9 binarizes the density correction data input from the density correction section 8 with a predetermined threshold value input thereto, and converts the binarized data to a binarization error generating section 10 outside the figure. Output.

The binarization error calculator 10 includes a density difference corrector 8
The binarization error in the pixel is calculated according to the binarization data input from the binarization unit 9 based on the density correction data input from the CPU 11 and output to the latch unit 11.

The latch section 11 adjusts the output timing of the binarized error data input from the binarized error generating section 10 and outputs the adjusted data to the RAM 5 and the error calculating section 7.

Next, the operation will be described.

An analog signal corresponding to one line of the original image read by the image sensor 2 is converted into a digital signal by the A / D converter 3 and output to the digital image processing unit 6, where the analog signal is output. Error diffusion processing is performed for each pixel of one line. FIG. 3 shows an example of an error diffusion filter used in the error diffusion processing. FIG. 3 (a)
Indicates the distribution ratio of the current pixel * and its surrounding pixels.
(B) shows error data of the current pixel density.

[0022] Assuming that corrected density _{a'm, n} for the current pixel density a _{m, n,} the following calculation is performed. a ′ _{m, n} = am _{, n} + (2ε _{m, n−1} + 2ε _{m−1, n} + ε _{m−1, n−1}
+ Ε _{m-1, n + 1} ) / 6

That is, an error amount for the current pixel am _{, n} is calculated by the error calculator 7 based on the error data of the previous pixel of the previous line obtained by the binarized error generator 10 and held in the RAM 4. The error amount is calculated by the density correction unit 8 at the current pixel a.
_m, is added at a predetermined ratio to the _n density correction performed by the corrected density data _{a'm, after n} has been determined, the corrected density data _{a'm, n} are, binarization section 9 Binarization processing is performed.

Here, the binarized signal based on the corrected density data a ' _{m, n} is represented by ad _{m, n} , and the threshold level of the binarization is represented by T
Assuming that H, when a ′ _{m, n} ≧ TH, ad _{m, n} = 1, ε _{m, n} = (a ′ _{m, n} −
M) When a ′ _{m, n} <TH, ad _{m, n} = 0, ε _{m, n} = a ′ _{m, n} where ε _{m, n} : a binarization error with respect to the current pixel density a _{m, n} M: Number of gradations (a ' _{m, n} -M): Complement of a' _{m, n} , and the number of gradations M is 16 and the total black level is 1
5, if the total white level is 0, a ' _{m, n} = 11, and TH = 8, ad _{m, n} = 1 (black), ε _{m, n} = 11-15 = -4
Becomes That is, by binarizing a pixel having a density of 11 into black (15), a density difference (error) of (-4) between input and output pixels is obtained.
Is generated, and this error is successively diffused to subsequent pixels for liquidation. Note that ε _{m, n} is calculated by the binarization error generation unit 10 and is stored in the RAM 5 at a predetermined timing via the latch unit 11.
Is forwarded to

However, if the threshold value at the time of binarization is kept constant, a pixel having a density near the threshold value cannot fully diffuse the error and a tailing (texture) phenomenon occurs.
This phenomenon can be eliminated by periodically changing the threshold value for each pixel.

In the case of an image processing apparatus that also shares a dither processing unit, the load on the hardware / software of the image processing apparatus can be reduced by sharing a threshold value setting register for dither. FIG. 4 shows a configuration example of the image processing apparatus 21 sharing the threshold value setting register.

In FIG. 4, an image processing device 21 comprises a multiplexer 22, a threshold value register 23, a system control unit 24 and a comparator 25. One of the signal and the error diffusion pixel signal input after error diffusion processing is selected and output to the comparator 25, and the threshold value is compared from the threshold value register (data table) 23 in which the threshold value for each pixel is set. When the dither pixel signal or the error diffusion pixel signal is output to the comparator 25 based on the threshold value input by the comparator 25, it is binarized and output as binary data. The system control unit 24 controls the operations of these units, and specifies a threshold value to be read from the threshold value register 23.

Now, the pixel density of the read data is all black level (15), the accumulated error is (-6),
Assuming that the threshold value is changed in the range of 6 to 10,
Since the data after the density correction is 9, the threshold value is 6
-9, the binarized output is 1 (black), 2
The binarization generation error is stored as 15-9 = 6. When this state continues and the threshold value is set to 10, the binary output becomes 0 (white), and the output side is output as all white on the output side even though the input data is at all black levels. Further, even when the threshold value is not changed, white spots are likely to be generated around the black background portion, giving an impression that the contrast of the image is blurred.

FIGS. 6 to 9 show an embodiment of an image processing apparatus to which an image processing method for eliminating such blurring of an image is applied.
Shown in

FIG. 6 is a block diagram of a main part of an image processing apparatus 31 having an error diffusion processing function. The same components as those of the image processing apparatus shown in FIG. Omitted.

In FIG. 6, an all-black / all-white judging section (all-black all-white judging means) 32 judges whether the read data is all black or all white. , 1) all white, (0,
0) The signals of non-all black and all white are converted to the binary error generators 9 and 2
Output to the value conversion unit 11.

The system control unit 33 controls the operation of each unit and inputs threshold value data for binarization to the binarization unit 11.

Next, the operation will be described.

The signals of (1,0) all black, (0,1) all white, (0,0) non-all black, and all white are output from the all black / all white determination section 32 to the binarization error generation section 9 and When output to the binarization unit 11, the binarization error is set to “0” in the case of all black or all white. Regardless of the threshold value input from the unit 33, the binarized data is output as black or white.
This binarized output may be obtained by converting the data after binarization, or by setting the threshold level to an all white level for all black data and to an all black level for all white data. Is also good.

The correction for all black and all white may not be performed when the accumulated error is small. That is, when the cumulative error is equal to or more than (−5), 6 to 1
It does not affect a threshold value of zero. Further, the determination of all black and all white may be made by performing only one of the determinations.

FIGS. 6 to 8 show specific examples of circuit configurations for processing the determination of all black and all white.

FIG. 6 shows a logic circuit configuration applied to the binarization error generating section 9 of FIG. 5, and includes a plurality of pixels input from the density correcting section 8 in response to all black and all white inputs. The binarization errors of the density data of
5 and output to the error calculator 6.

FIG. 7 shows a logic circuit configuration applied to the binarization unit 11 of FIG. 5, and not the threshold value input from the system control unit 33 but the all black / all white determination unit 32.
The density data input from the density correction unit 8 is compared with the all black and all white data input from the CPU, and the binarized data is output.

FIG. 8 shows a logical circuit configuration of a portion for changing the threshold value applied to the binarizing section 11 of FIG. The threshold value input from the system control unit 33 is selected according to the white data, the threshold value is output, and the binarization operation is performed in the binarization unit 11 (not shown).

FIG. 9 shows a flowchart of the binarization processing procedure involved in the above all black and all white determination processing in the image processing apparatus 31.

In FIG. 9, it is determined whether the data input from the all black / all white determining section 32 is all black or all white (step S).
l) If the image is all black or all white, the binarization error is set to “0” (step S2), the threshold value is converted according to the accumulated error (step S3), and the binarization process is performed (step S2).
4) Calculate the binarization error (step S5) and change to black or white binary data regardless of the binarization error (step S6) to calculate the binarization error (step S7).

If it is not all black or all white in step Sl, density correction calculation is performed to obtain corrected density data (step S8), and the corrected density data is set to a threshold value input from the system controller 33. And binarize to 2
In addition to outputting the value data, a binarization error is calculated using the corrected density data (step S10).

Accordingly, the contrast of the halftone image can be improved by setting the binarization error to "0" when the all-black or all-white pixel data is inputted, and the all-black or all-white pixel can be improved. When the data is input, the binarization error is set to “0” according to the accumulated error amount. Therefore, even if the threshold value of the binarization is periodically changed, the white point in the black background or the white background , And conversion to binary data according to all black and all white data, it is possible to improve the contrast of a halftone image while preserving the accumulated error.

When calculating the binarization error, there is a case where a fraction is rounded. If the fraction is rounded in a direction approaching “0”, the conversion of the error into an integer can be expedited, and the image quality can be improved. Can be improved. In addition, when the result of the two's complement operation when calculating the binarization error is a negative value, the error is converted to an integer by adding “1” after rounding the fraction. And the image quality can be improved earlier.

For example, when −11 ÷ 2 = −5.5, 00101 (two's complement) is shifted by 1 bit to 0
010 (−6) is increased by 1 and corrected to (−5).

Therefore, since the fraction of the error calculation is converted to an integer in a direction approaching "0", the conversion of the error into an integer is quick and a sharp halftone image can be reproduced.

[0047]

According to the first aspect of the present invention, in an image processing apparatus which can select and use dither image processing means and error diffusion image processing means, a plurality of dither image processing means set as matrix data The threshold value and the threshold value set by the error diffusion image processing means are stored in a common data table, and when the error diffusion image processing unit performs image processing, the threshold value is periodically changed for each processing pixel. Therefore, the hardware configuration of the image processing apparatus including the dither image processing unit and the error diffusion image processing unit can be reduced, and the generation of texture unique to error diffusion can be eliminated, and the image quality of the halftone image can be improved. Can be done.

[Brief description of the drawings]

FIG. 1 is a block diagram of a facsimile apparatus to which an image processing apparatus according to the first embodiment is applied.

FIG. 2 is a block diagram of a digital image processing unit in FIG. 1;

FIG. 3 is a diagram showing an example of an error diffusion filter used at the time of error diffusion processing in the digital image processing unit in FIG. 2;

FIG. 4 is a block diagram of an image processing apparatus according to the first embodiment;

FIG. 5 is a main block diagram of the image processing apparatus.

FIG. 6 is a diagram showing a configuration of a logic circuit applied to a binarization error generation unit in FIG. 5;

FIG. 7 is a diagram showing a configuration of a logic circuit applied to the binarization unit in FIG. 5;

FIG. 8 is a diagram showing a logic circuit configuration of a part that changes a threshold value applied to the binarization unit in FIG. 5;

FIG. 9 is a flowchart of an error diffusion process.

[Explanation of symbols]

 Reference Signs List 1 facsimile device 5 RAM 6 digital image processing unit 7 error calculation unit 8 density correction unit 9 binarization unit 10 binarization error generation unit 21 image processing unit 22 multiplexer 23 threshold value register 24 system control unit 25 comparator 31 image processing Device 32 All black / all white judgment unit 33 System control unit

Claims (1)

[Claims] 1. A method for comparing the level of each pixel of multi-valued pixel data input for each line with matrix data in which a plurality of predetermined threshold values are set, binarizing based on the comparison result, and outputting the result. Dither image processing means for outputting binary pixel data to represent a halftone image; and detecting an error between output pixel data quantized for each pixel of multi-valued pixel data input for each line and input pixel data. Error diffusion image processing means for binarizing the result of diffusion into pixel data based on a predetermined threshold value, outputting output binary pixel data and expressing a halftone image, In an image processing apparatus capable of selecting and using a processing unit and an error diffusion image processing unit, a plurality of threshold values set as matrix data by the dither image processing unit and the error diffusion image The threshold value set by the processing means is stored in a common data table, and when the error diffusion image processing unit performs image processing, the threshold value is periodically changed for each processing pixel. Processing equipment.