JP2000236445A - Image processing unit - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain an image with excellent quality without causing a stripe pattern depending on a structure of a threshold value matrix and a dot pattern in a specific density level area in an image processing unit adopting the error spread method. SOLUTION: This image processing unit is provided with a selection means 32 that selects input image data SB1 whose gradation number N is 2n (n is an integer being 3 or over) into 1st image data S11 and 2nd image data S12, a low level processing means 34 that applies low level processing to the 1st image data S11 into low level data SG1 whose gradation number M is 2m (m is an integer being 2 or over less than the integer n) and outputs prescribed gradation data with a prescribed gradation level corresponding to the 2nd image data, and an error spread processing means 37 that conducts error spread processing so that a print result has a prescribed screen angle on the basis of a 1st error S2 that is an error between a gradation level of the 1st image data S11 and the gradation level of the low level data SG1 corresponding to the gradation level and of a 2nd error S12 that is an error of the gradation level between the 2nd image data S12 and the prescribed gradation data.

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 performing pseudo halftone expression by applying an error diffusion method.

[0002]

2. Description of the Related Art Conventionally, in a laser printer or a digital copying machine, a low-value processing method such as a dither method or an error diffusion method has been used to faithfully reproduce a halftone original image such as a photographic image. Have been.

[0003] The dither method is a method of binarizing original image data by making each element of a threshold matrix in which a series of gradation values are randomly arranged correspond to each pixel of the original image. In the dither method, if the size of the threshold matrix is small, sufficient gradation cannot be obtained. If the size of the threshold matrix is increased to obtain sufficient gradation, the resolution may decrease,
A high-quality image cannot be obtained because the texture structure generated from the periodic structure of the threshold matrix is conspicuous.

A multi-value dither method has been proposed as a method for solving this problem. The multi-value dither method is a method of multi-value original image data using a plurality of different threshold matrices. However, according to the multi-value dither method, although the image quality is improved, a complicated circuit configuration is required for synchronizing the respective threshold matrices, and the apparatus becomes large.

The error diffusion method is one of pseudo halftone expression methods capable of reproducing a halftone original image such as a photographic image at a low value. In the error diffusion method, the tone level of the original image is reduced to low-value data by a certain threshold, and the error between the tone level of the pixel of interest and the corresponding tone level of the low-value data is within a certain range. A plurality of peripheral pixels are weighted and distributed (Japanese Patent Publication No. 7-93684).

According to the error diffusion method, since the density of the original image is maintained, a relatively faithful image can be obtained. Further, since the image data of the original image is compressed by lowering the value, the processing can be performed with a small memory capacity.

[0007]

However, in an image obtained by the error diffusion method, a specific dot pattern (texture) occurs in a region of a specific density level, or a unique fringe depending on the structure of a threshold matrix. In some cases, a pattern (worm-like dot pattern) is generated, and the image quality is degraded. Such a dot pattern or a striped pattern is considered to be caused by a lack of predetermined regularity in the arrangement of dots to be printed.

SUMMARY OF THE INVENTION The present invention has been made in view of the above-described problem. In an image processing apparatus to which the error diffusion method is applied, a dot pattern in a specific density level region or a stripe pattern depending on the structure of a threshold matrix is generated. An object of the present invention is to provide an image processing apparatus capable of obtaining a high-quality image without any problem.

[0009]

An image processing apparatus 1 according to the first aspect of the present invention, as shown in FIGS.
Is 2 ⁿ (n is an integer of 3 or more) input image data S1,
Selecting means 32 for selecting the first image data S11 and the second image data S12; and converting the first image data S11 to low-value data having a gradation number M of 2 ^m (m is an integer of 2 or more smaller than n). SG1 and the second image data S1
2, a lowering means 34 for outputting predetermined gradation data of a predetermined gradation level corresponding to the gradation level of the first image data S11 and the gradation level of the lowering data SG1 corresponding thereto. Based on the first error S2, which is the error of the second image data, and the second error S12, which is the error between the gradation level of the second image data S12 and the gradation level of the predetermined gradation data, Error diffusion processing means 37 for performing an error diffusion process.

An image processing apparatus 1 according to a second aspect of the present invention
It has a storage means 37M1 for storing the first error S2 and the second error S12.

An image processing apparatus 1B according to a third aspect of the present invention.
Has a smoothing processing unit 40 for performing a smoothing process for each predetermined pixel unit of the input image data S1, as shown in FIG.

An image processing apparatus 1C according to a fourth aspect of the present invention.
Has a discriminating unit 50 for discriminating an edge portion and a non-edge portion of the input image data S1 as shown in FIG. 7, and the selecting unit 321 has been discriminated as a non-edge portion by the discriminating unit 50. The input image data in the portion is selected as the first image data S11.

The error diffusion processing referred to in the present specification means a broad concept of processing for pseudo-halftone expression for reducing an error between a read signal and a recording signal on average, and includes an average error minimum method, a multi-level error, and the like. The diffusion method is also treated as included in this concept.

[0014]

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

The image processing apparatus 1 performs various digital signal processing including error diffusion processing on image data of a read document or image data input from the outside, and print data for performing pseudo halftone expression. Output.

As shown in FIG. 1, the image processing apparatus 1
CD image sensor 11, interface 12, A / D
It comprises a conversion unit 13, a shading correction unit 14, and an image signal processing unit 20. The image signal processing unit 20
og converter 21, HVC converter 22, UCR processor 2
3, BP processing unit 24, color correction unit 25, error diffusion processing unit 3
0, a γ correction unit 27, and a D / A conversion unit 29.

The CCD image sensor 11 reads a document and converts it into an electric signal. That is, the reflected light of the document irradiated by an exposure lamp (not shown) is photoelectrically converted for each of R (red), G (green), and B (blue) color components, and an analog signal is output.

The A / D converter 13 corrects the offset and gain of the analog signal input from the CCD image sensor 11, and converts the corrected signal into 8 bits (256 bits) for each of R, G, and B colors. Image data (r,
g, b).

The shading correction section 14 corrects the image data of each color according to the uneven light distribution of the exposure lamp and the variation in sensitivity between pixels of the CCD image sensor 11. The interface 12 captures image data from an external device. From the shading correction unit 14 or the interface 12, image data S1 (r ′, g ′, b ′) of each of R, G, and B representing luminance is output.

The log converter 21 converts the image data S1 into image data (Dr, D
g, Db). The HVC converter 22 converts the image data S1 into a brightness signal (V data) and a color difference signal (C data). The UCR processing unit 23 converts a dark color component to be reproduced with black toner into image data (Dr, Dg, D
b), and correct the R, G, B data values according to the extracted value. The BP processing unit 24 generates black data (K data) based on the data from the HVC conversion unit 22 and the log conversion unit 21.

The color correction unit 25 includes R, G,
B. Image data (Dr ', Dg', D
b ') is converted into image data of each color of C (cyan), M (magenta), and Y (yellow) which match the characteristics of the toner. In the present embodiment, the image data SB1 of four colors of C, M, Y, and K obtained from the color correction unit 25 and the BP processing unit 24 has 8 bits for each pixel and 256 density gradations. And

The error diffusion processing unit 30 has 256 gradation levels (8
Bit) image data SB1 is subjected to an error diffusion process, which will be described later, to obtain 8-gradation (3 bits) reduced value data SG1
To lower.

The γ correction section 27 performs γ correction based on the background color and density gradient of the document. The D / A converter 29 converts the digital low value data SG1 into analog print data by a D / A converter.
A conversion and output.

In the image processing apparatus 1, image data S 1 (256 gradations) obtained from the CCD image sensor 11 or the interface 12 is input to the image signal processing unit 20 and reduced by the error diffusion processing unit 30. Data S
The value is reduced to G1 (the number of gradations is 8). Low price data SG
1, a pseudo halftone image is formed by a predetermined printing unit.

Next, the configuration and function of the error diffusion processing unit 30 will be described.

FIG. 2 is a block diagram of the error diffusion processing unit 30,
FIG. 3 is a diagram showing an example of a dot pattern PT1 formed when there is no operation of the selector 32, and FIG. 4 is a diagram showing an example of a dot pattern PT2 formed when the input image data SB1 has a high density. FIG. 5 is a diagram showing an example of a dot pattern PT3 formed when the input image data SB1 has a low density. 3 to 5
There is no commonality in the content of the image between the two. In these figures, the horizontal direction is the main scanning direction, and the vertical direction is the sub-scanning direction.

In FIG. 2, since the configuration corresponding to each of the four colors C, M, Y, and K is the same, the configuration for one color is shown here.

As shown in FIG. 2, the error diffusion processing unit 30
Are an input correction unit 31, a selector 32, a counter 33, a value reduction unit 34, a threshold data setting unit 35, a difference calculation unit 36,
And an error acquisition value calculation unit 37.

The input correction unit 31 adds the accumulated error S3 obtained from peripheral pixels to the target pixel of the image data SB1.

The counter 33 counts the number of pixels in the main scanning direction and the number of pixels (the number of lines) in the sub-scanning direction, and outputs a count signal CT.

The selector 32 selects the image data SB1 having 256 gradations into the following image data S11 and image data S12 for each pixel based on the count signal CT.

That is, of the input image data SB1, the image data of the even-numbered pixels in the image data of the odd-numbered line and the image data of the odd-numbered pixels in the image data of the even-numbered line are defined as image data S11. . In the image data SB1, the image data of the odd-numbered pixel in the image data of the odd-numbered line and the image data of the even-numbered pixel in the image data of the even-numbered line are referred to as image data S12. The image data S1
It is also possible to reverse the selection conditions for 1 and the image data S12.

The lowering unit 34 uses the threshold value set by the threshold value data setting unit 35 to generate image data S of 256 gradations.
11 is converted to low-value data SG1 having eight gradation levels and output. At this time, a level closest to the gray level of the image data S11 is selected as the gray level of the low-value data SG1. In addition, for the image data S12, data with a gradation level of “0” is output as the reduced value data SG1.

The difference calculator 36 calculates an error S between the gradation level of the image data S11 and the gradation level of the low-value data SG1.
2 is calculated.

The error acquisition value calculator 37 is provided with a memory 37M
1,37M2. The memory 37M1 stores the error S2 and the image data S12. As described above, for the image data S12, the data with the gradation level “0” is output as the low-value data SG1, so that the image data S12 is the same as the data with the gradation level “0”. Equal to the error. Therefore, the memory 37M1 stores all errors due to the lowering of the value.

The memory 37M2 stores the error diffusion matrix 3
7X and a divider 37D. Error diffusion matrix 3
7X is a functional element for allocating an error due to the lowering of the value according to the weight assigned to each pixel. The divider 37D divides the output of the error diffusion matrix 37X by the sum of the weights.

The error diffusion processing unit 30 configured as described above
Is the image data S1 of the input image data SB1.
11, the lowering unit 34 lowers the value and outputs the lowering data SG1. For the image data S12, the data having the gradation level “0” is converted to the lowering data SG1.
Output as 1. As described above, since the error diffusion process is performed based on the error between the image data S11 and S12 before the lowering and the lowering data SG1 after the lowering, the density of the original image is maintained.

Since the gradation levels of the pixels adjacent to each other in the main scanning direction and the sub-scanning direction alternately become "0", the dot patterns PT2 and PT3 to be printed are as shown in FIG.
And as shown in FIG. 5, it becomes a staggered pattern. That is, black dots appear due to the reduced value data SG1 corresponding to the image data S11, and white dots appear due to the reduced value data SG1 corresponding to the image data S12. The gradation of the black dot portion is reproduced by dividing each pixel into a plurality of sections, giving each pixel or each section a gradation in density. Thereby, a predetermined screen angle is provided.

For this reason, a high-quality image can be obtained without a phenomenon of image quality deterioration peculiar to the error diffusion processing, that is, a phenomenon in which a dot pattern or a stripe pattern depending on the structure of a threshold matrix in a specific density level region occurs. Will be reproduced. By changing the condition for switching the selector 32,
Various screen angles can be formed. Therefore, it is possible to form a good image which is not easily affected by noise generated by a mechanical error or fluctuation of the printing unit. Also, various dot printing controls can be easily performed. [Second Embodiment] FIG. 6 is a block diagram of an image processing apparatus 1B according to a second embodiment.

As shown in FIG. 6, the image processing apparatus 1B
The image processing apparatus 1 includes an image signal processing unit 20B instead of the image signal processing unit 20.

The image signal processing unit 20B differs from the image signal processing unit 20 in that a smoothing processing unit 40 is provided before the error diffusion processing unit 30. The other components are the image processing device 1
Therefore, the same components are included in the image processing apparatus 1.
Are given the same reference numerals as in, and description thereof is omitted. The same applies hereinafter.

The smoothing processing section 40 includes a color correction section 25 and B
The image data of four colors of C, M, Y, and K obtained from the P processing unit 24 is subjected to a smoothing process for blurring the density in units of two pixels, for example.

The error diffusion processing unit 30 performs the above-described error diffusion processing on the image data SB2 that has been subjected to the smoothing processing. This gives a faithful image. That is,
For a low-density original image in which dark-level image data and light-level image data coexist, dark-level image data corresponds to white dots and light-level image data corresponds to black dots. In such a case, the resulting image may be lighter than the original image as a result. By performing the smoothing process before the error diffusion processing unit 30, it is possible to prevent the image from becoming lighter than the original image. Third Embodiment FIG. 7 is a block diagram of an image processing apparatus 1C according to a third embodiment, and FIG. 8 is a block diagram of an error diffusion processing section 30C.

As shown in FIG. 7, the image processing apparatus 1C
An image signal processing unit 20C is provided in place of the image signal processing unit 20 in the first embodiment.

The image signal processing unit 20C is different from the image signal processing unit 20 in that the error diffusion processing unit 30
C, and a region discriminating unit 5 is provided before the error diffusion processing unit 30C.
It is different from the image signal processing unit 20 in having 0.

The region discriminating section 50 discriminates whether the image data S1 is an edge portion or a non-edge portion, and outputs a discrimination signal S
31 and image data SB3. Image data SB
Reference numeral 3 includes image data SE of an edge portion and image data SN of a non-edge portion.

As shown in FIG. 8, the error diffusion processing unit 30C
In this example, a selector 321 is provided at a stage preceding the selector 32.

The selector 321 selectively outputs the image data SE and the image data SN based on the determination signal S31. That is, the image data output from the input correction unit 31 is output as image data SE when it is determined to be an edge portion, and as image data SN when it is determined to be a non-edge portion. . The same processing as in the case of the error diffusion processing unit 30 is performed on the image data SN of the non-edge part. That is, the image data SN
Are separated into image data SN1 and image data SN2 by the selector 32. Image data SN1 having 256 tones is reduced to low-value data SN1G having 8 tones and output. At this time, the low price data SN1G
Is selected as the gray level of the image data SN1. Further, for the image data SN2, data with a gradation level of “0” is output. On the other hand, for the image data SE of the edge portion, the selector 3
2, the error diffusion processing is performed without performing the processing performed in the error diffusion processing unit 30 of the first embodiment, and the low-value data SEG is output. As a result, the same effect as in the first embodiment can be obtained for the non-edge portion, and a sharper image can be obtained for the edge portion.

In the above-described first to third embodiments, since the processing is performed in units of pixels, the effective resolution does not change.

In the above embodiment, the image processing apparatuses 1, 1B. Number of gradations N of input image data S1 in 1C
Has been described as 256, that is, 2 ⁸ , and the number of tones M of the output image data SG has been set as 8, that is, 2 ³ , but the bit numbers n and m of the image data are arbitrarily selected within a range satisfying the relationship of N> M. be able to.

In the above embodiment, the image processing apparatuses 1, 1B, 1C, the error diffusion processing units 30, 30B, 30C
The configuration, shape, arrangement, circuit, etc. of each part or the whole can be appropriately changed in accordance with the gist of the present invention.

[0052]

According to the present invention, in an image processing apparatus to which the error diffusion method is applied, in an image processing apparatus to which the error diffusion method is applied, a stripe pattern dependent on the structure of a dot pattern or a threshold matrix in a specific density level region. A high quality image can be obtained without the occurrence of.

According to the third aspect of the present invention, a good image can be obtained even for a low-density original image in which image data of a dark level and image data of a light level are mixed.

According to the fourth aspect of the present invention, a better image can be formed on the edge portion and the non-edge portion.

[Brief description of the drawings]

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

FIG. 2 is a block diagram of an error diffusion processing unit.

FIG. 3 is a diagram showing an example of a dot pattern formed when there is no operation of a selector.

FIG. 4 is a diagram illustrating an example of a dot pattern formed when input image data has a high density.

FIG. 5 is a diagram illustrating an example of a dot pattern formed when input image data has a low density.

FIG. 6 is a block diagram of an image processing apparatus according to a second embodiment.

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

FIG. 8 is a block diagram illustrating another example of the error diffusion processing unit.

[Explanation of symbols]

1, 1B, 1C Image processing device 30 Error diffusion processing unit 32 Selector (selection unit) 34 Low-value unit (Low-value unit) 37 Error acquisition value calculation unit (Error diffusion processing unit) 37M1 Memory (Storage unit) 40 Smoothing Processing section 50 area discriminating section (discriminating means) S1 image data (input image data) S2 error (first error) SG1, SEG, SN1G reduced value data S11, SN1 image data (first image data) S12, SN2 image Data (second image data, second error)

 ──────────────────────────────────────────────────続 き Continuing on the front page F-term (reference) 2C062 AA24 2C262 AA05 AA17 AA24 AA26 AB03 AC02 AC04 BA02 BB03 BB08 DA03 5B057 CA01 CA08 CB01 CB08 CE05 CE13 DC16 5C077 LL02 MP01 MP08 NN11 PP28 PP32 PP33 PQ17 EE08 9 KK54

Claims (4)

[Claims] A selecting means for selecting input image data having a gradation number N of 2 ⁿ (n is an integer of 3 or more) into first image data and second image data; The value M is 2 ^m (m is an integer of 2 or more smaller than n), and the value is reduced to lower value data and output.
A low-value means for outputting predetermined gradation data of a predetermined gradation level corresponding to the second image data; and a gradation level of the first image data and a gradation of the low-value data corresponding thereto. The printing result has a predetermined screen angle based on a first error that is an error with respect to the level and a second error that is an error between the gradation level of the second image data and the gradation level of the predetermined gradation data. And an error diffusion processing means for performing error diffusion processing as described above. 2. The image processing apparatus according to claim 1, further comprising storage means for storing said first error and said second error. 3. The image processing apparatus according to claim 1, further comprising a smoothing processing unit for performing a smoothing process for each predetermined pixel unit of the input image data. 4. A discriminating means for discriminating between an edge portion and a non-edge portion of the input image data, wherein the selecting means converts the input image data in a portion discriminated as a non-edge portion by the discriminating portion into the first image data. The image processing apparatus according to claim 1, wherein the image processing apparatus is selected as one image data.