JP2000022944A - Image processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve gradation repeatability and to output an image with excellent image quality by performing gradation processing for gradation conversion of a part with low density by means of binary processing and performing gradation processing of a part with high density by means of multivalued processing. SOLUTION: This image processor consists of a line memory 1 which stores gradation image data D1 before gradation processing to be inputted, a frame memory 2 which outputs gradation processed data D2 after the gradation processing and a CPU 3 which carries out the gradation processing. In such a case, e.g. the data D1 before the gradation processing is assumed to 8 bits and the data D2 after the gradation processing is assumed to 4 bits. The memory 1 is provided, e.g. for six lines. This is because a 6×6 gradation processing matrix is assumed. Thus, it is possible to reproduce optimum dots, to reproduce stable density and to output a smooth image by performing gradation processing for gradation conversion of a part with low density by means of binary processing and performing gradation processing of a part with high density by means of multivalued processing.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

2. Description of the Related Art In a case where a multi-tone density expression is performed by a plurality of dots, an error diffusion process is generally performed. For example, Japanese Patent Application Laid-Open No. 7-226841 discloses a general error diffusion matrix process. In the case of using such an error diffusion processing matrix, the error is distributed according to the weight value to the pixels that have not been binarized around the target pixel without discarding the quantization error generated at the time of binarization. Thus, continuous gradation expression is possible despite high resolution.

[0002]

By the way, in such a method, when the error is diffused (distributed), a pattern in which dots are connected in a chain is noticeable by narrowing the range in which the error is diffused. There is a problem that image quality is deteriorated. Further, error diffusion processing in an output device capable of multi-value output has not been generalized yet.

The present invention has been made in view of the above points, and a first object of the present invention is to provide an image processing apparatus capable of improving tone reproduction and outputting an image of excellent image quality. It is in.

Another object of the present invention is to provide an image processing apparatus capable of processing in a short time.

A third object is to provide an image processing apparatus which requires a small memory size.

[0006]

In order to achieve the above object, a first means modulates dot density or dot size with respect to input image data, and expresses a density gradation by a plurality of dots. In an image processing apparatus provided with gradation processing means for performing tone processing, the gradation processing means performs binary conversion for gradation conversion of a low-density part and multi-value processing for gradation processing of a high-density part. It is characterized in that gradation processing is performed.

A second means is the first means, wherein the gradation processing means diffuses a processing error based on a threshold value in a matrix format composed of a plurality of dots.

The third means is characterized in that in the second means, the processing error is diffused in units of a matrix composed of a plurality of dots.

A fourth means is the third means, further comprising a line buffer for each matrix.

[0010]

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

FIG. 1 is a block diagram showing a main part of an image processing apparatus according to an embodiment of the present invention. In the figure, an image processing apparatus receives input gradation image data D before gradation processing.
1, a line memory 1 for storing gradation processing data 1, a frame memory 2 for outputting gradation processing data D2 after gradation processing, and a CPU 3 for executing gradation processing. In this embodiment, it is assumed that the gradation processing data D1 before gradation processing is 8 bits and the gradation processing data D2 after gradation processing is 4 bits.

The line memory 1 is provided for six lines. This is 6 in the present embodiment as can be seen from the following description.
This is because a × 6 gradation processing matrix is assumed.
Therefore, if the matrix size is larger than this size, the number of line memories naturally increases. The frame memory 2 has a 4-bit weight in order to store the data after the gradation processing. Further, the CPU 3 executes gradation processing from the line memory 1 to the frame memory 2 after gradation processing. This gradation processing is performed by software processing in the CPU 3.

FIG. 2 is a diagram showing a part of a dither matrix when the CPU 3 performs software processing. Although the matrix size is 6 × 6, the basic matrix is 3 × 6, and the matrix shifted horizontally by 3 lines and processed at 45 degrees is a 6 × 6 matrix. When the input image is 90 or less, binarization conversion is performed at a threshold level as shown in FIG. Since the multi-valued number of dots is 15 values, if the input value is smaller than the threshold level, it is set to "0".
If it is above the threshold level, it is converted to "15". If the input image is 90 or more, it is converted from 1 value to 15 values at a threshold level as shown in FIG. Similarly, if the value is 180 or more, the value is converted from 1 value to 15 values at the threshold level shown in FIG.

FIG. 5 and FIG. 6 show a reference configuration of the gradation error.

FIG. 6 shows a pixel configuration, and FIG. 5 shows a matrix section corresponding to this error configuration. As shown in FIG. 6, all frames are conceptually divided in a 6 × 6 matrix unit, and an error between the input value of the sum for each matrix and the sum after dither processing is diffused in a matrix unit. . FIG. 5 shows an example in which the data is divided into four rows and four columns, and is a diffusion example in the matrix 11 of the first row and the first column to the matrix 44 of the fourth row and the fourth column. Here, the error diffusion in the right direction is indicated by er, the error diffusion in the downward direction is indicated by ed, and the oblique right direction is indicated by es. In this embodiment, the error diffusion is
er: es: ed = 1: 1: 1: 1.

FIGS. 7 to 10 are flowcharts showing the processing procedure in the present embodiment.

First, as shown in the flow chart of FIG. 7, the matrix 11 calculates the input sum S11 of the matrix 11 (step 701). Then, dither conversion processing of the matrix 11 is performed (step 70).
2). This dither processing is processing performed in accordance with a pattern for gradation processing, and detailed processing contents are known, and thus description thereof will be omitted. Then, the sum Sd11 after the dither processing is calculated (step 703), the error e = Sd11−S11 between the sum Sd11 after the dither processing and the input sum S11 is calculated (step 704), and the error division e1 = e / 3. = Er1 = ed1 = es1 is executed (step 705).

When the processing shown in FIG. 7 is executed in the matrix 11, the input sum S21 of the matrix 21 is first calculated in the matrix 21 on the right side as shown in the flowchart of FIG. 8 (step 801). This input sum S21 is a total sum Si21 of inputs of only the matrix 21 part.
To which the diffusion error from the matrix 11 is added, that is, S21 = Si21 + er1. The input sum S2 to which the diffusion error is added in this way
When 1 is calculated, a dither conversion process is executed (step 802), and a sum Sd21 after the dither process is calculated (step 803). When the sum Sd21 after the dither processing is calculated, the error e = Sd21−S21 between the sum Sd21 after the dither processing and the input sum S21 is calculated (step 804), and then the error division e2 = e / 3 = er2 = ed2 = es2 is executed (step 805).

After the matrix 31, the same processing as the processing shown in the flowchart of FIG. 9 is executed.

On the other hand, the processing shown in the flowchart of FIG. 10 is executed in the lower matrix 12 section of the matrix 11 section. That is, in the lower matrix 12 of the matrix 11, first, the input sum S 1 of the matrix 12 is obtained.
2 is calculated (step 901). This input sum S12
Is obtained by adding the diffusion error from the matrix 11 to the total sum Si12 of the inputs of the matrix 12 alone, that is, S12 = Si12 + ed1. The input sum S1 to which the diffusion error is added in this way
When 2 is calculated, a dither conversion process is executed (step 902), and a sum Sd12 after the dither process is calculated (step 903). When the sum Sd12 after the dither processing is calculated, an error e = Sd12−S12 between the sum Sd12 after the dither processing and the input sum S12 is calculated (step 904), and then the error division e4 = e / 3 = er4 = ed4 = es4 is executed (step 905).

The matrix 22 on the right of the matrix 12 section
In the unit, the processing shown in the flowchart of FIG. 10 is executed. That is, the matrix 22 first calculates the input sum S22 of the matrix 22 (step 100).
1). The input sum S22 is obtained by adding the matrix 11 and the matrix 1 to the total input Si22 of only the matrix 22.
Diffusion errors es1, e from two parts and 21 parts of matrix
The sum of d2 and er4, that is, S22 = Si22 + es1 + ed2 + er4. The input sum S2 to which the diffusion error is added in this way
When 2 is calculated, a dither conversion process is executed (step 1002), and a sum Sd22 after the dither process is calculated (step 1003). Sum Sd2 after dither processing
When 2 is calculated, an error e = Sd22−S22 between the sum Sd22 after the dither processing and the input sum S22 is calculated (step 1004), and then error division e4 = e / 3 = er5 = ed5 = es5 is executed. (Step 1005).

In this way, the error diffusion is performed up to the matrix 44 portion. By performing such processing, error diffusion can be performed in units of a matrix composed of a plurality of dots, so that error diffusion in gradation processing can be performed over a wide area, and deterioration in image quality can be suppressed.

[0023]

As described above, according to the first aspect of the invention, the gradation processing means performs the binary conversion for the gradation conversion of the low density portion and the multi-valued gradation processing for the high density portion. Image processing that enables optimal dot reproduction, stable density reproduction, and smooth image output by performing gradation processing, thereby improving gradation reproduction and outputting images with excellent image quality An apparatus can be provided.

According to the second aspect of the present invention, the gradation processing means diffuses a processing error based on a matrix-type threshold composed of a plurality of dots, so that it is possible to avoid image quality deterioration peculiar to the error diffusion method. Thus, it is possible to provide an image processing apparatus capable of improving tone reproducibility and outputting an image of excellent image quality.

According to the third aspect of the present invention, since the processing error is diffused in a matrix unit composed of a plurality of dots, the error diffusion can be performed in a wide area, so that the image quality deterioration can be reduced. Further, since the processing unit is smaller than the dot unit, it is possible to provide an image processing apparatus capable of performing processing in a short time.

According to the fourth aspect of the present invention, since the line buffer is provided in matrix units, the processing can be performed with a minimum memory, thereby providing an image processing apparatus requiring a small memory size. be able to.

[Brief description of the drawings]

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

FIG. 2 is a diagram illustrating a part of a dither matrix when software processing is performed by a CPU;

FIG. 3 is a diagram illustrating a state in which multi-level processing is performed according to an input value of an input image and a threshold level.

FIG. 4 is a diagram illustrating a state where multi-level processing is performed according to an input value of an input image and a threshold level.

FIG. 5 is a diagram showing matrix divisions when a tone error is diffused.

FIG. 6 is a diagram illustrating a configuration of a pixel that has been subjected to matrix division in FIG. 5;

FIG. 7 is a flowchart illustrating a processing procedure of a diffusion process of matrix error diffusion of a matrix 11 in the embodiment.

FIG. 8 is a flowchart illustrating a processing procedure of a diffusion process of matrix error diffusion of a matrix 21 in the embodiment.

FIG. 9 is a flowchart showing a processing procedure of a diffusion process of matrix error diffusion of a matrix 12 in the embodiment.

FIG. 10 is a flowchart showing a processing procedure of diffusion processing of matrix error diffusion of a matrix 22 in the embodiment.

[Explanation of symbols]

 1 line memory 2 frame memory 3 CPU

Claims (4)

[Claims] 1. An image processing apparatus comprising: gradation processing means for performing gradation processing for modulating dot density or dot size with respect to input image data and expressing density gradation with a plurality of dots. An image processing apparatus characterized in that the gradation processing means performs gradation processing for low-density parts by binary processing and performs gradation processing for high-density parts by multi-value processing. 2. An image processing apparatus according to claim 1, wherein said gradation processing means diffuses a processing error based on a matrix-type threshold comprising a plurality of dots. 3. The image processing apparatus according to claim 2, wherein the diffusion of the processing error is performed in a matrix unit composed of a plurality of dots. 4. The image processing apparatus according to claim 3, further comprising a matrix unit line buffer.