JP2008306400A - Image processing method, image processing apparatus, image forming apparatus, computer program, and recording medium - Google Patents

Abstract

An image processing method, an image processing apparatus, and an image forming method capable of generating a halftone image with less unevenness of density or roughness, and in which dots in a highlight area are difficult to perceive and improving image quality. An apparatus, a computer program, and a recording medium on which the computer program is recorded are provided.
A peripheral pixel determination unit 289 extracts a peripheral pixel block around a pixel of interest composed of a plurality of quantized pixels, and based on a quantized value of each pixel of the extracted peripheral pixel block A low gradation level around the pixel is specified and a determination signal is output. The quantization processing unit 282 selects an appropriate quantization table from the plurality of quantization tables stored in the quantization threshold storage unit 288 based on the determination signal, and the plurality of quantization tables in the selected quantization table. Multi-value quantization is performed based on the quantization threshold, and the quantized value is output as output image data.
[Selection] Figure 3

Description

  The present invention uses an error diffusion method in which an error from a pixel value generated when quantizing each pixel of an input image is diffused to surrounding pixels that are not quantized based on a diffusion coefficient. The present invention relates to an image processing method for generating an output image, an image processing apparatus, an image forming apparatus including the image processing apparatus, a computer program for realizing the image processing apparatus, and a recording medium on which the computer program is recorded.

  In recent years, digitalization of office automation equipment has been rapidly progressed, and demand for color image output has increased, so that output devices such as electrophotographic digital color copying machines and ink jet or thermal transfer color printers have become widely available. It is popular. For example, an image input from an input device such as a digital camera or an image scanner, or an image created by a computer is output using these output devices. In these output devices, since the number of gradations that can be output is generally smaller than the number of gradations of the input image input from the input device, the pseudo gradation reproduction processing may be performed on the input image. Many.

  One method of pseudo gradation reproduction processing is error diffusion processing. In the error diffusion process, there is a binary error diffusion process in which the quantized value is binary. However, because of the binary value, the density difference between pixels increases. For example, when the output resolution is about 600 dpi × 600 dpi, a texture or a worm is generated. It is easy to see and individual dots can be confirmed in the highlight area, resulting in poor graininess. In order to suppress this problem, there is a multi-value error diffusion process in which the number of thresholds for quantization is increased and quantization is performed on three or more quantized values by using these threshold values.

  In an electrophotographic image output device, gradation is generally recorded according to the degree of modulation of the exposure pulse width, but when the exposure pulse width is narrow, the frequency of low latent image potentials with unstable development characteristics increases, and the output In order to cause density unevenness or roughness in an image, a technique has been proposed in which control is performed so that a signal having a narrow exposure pulse width is not generated. (Refer nonpatent literature 1).

Also, in the multi-level error diffusion process, among the already quantized pixels around the pixel of interest, the arrangement state of the quantized pixels in a predetermined window is examined, and the continuity of pixels having the same quantized value is checked. There has been proposed an image processing apparatus that determines a quantization threshold of a pixel of interest so as to prevent continuity when detected (see Patent Document 1).
Japanese Patent No. 2756308 Naofumi Yamamoto, Kazuhiko Higuchi, Eiichi Sakagami, Hidekazu Sekizawa, “New Multilevel Error Diffusion Processing Method with Improved Reproducibility of Highlight Region”, Journal of Electrophotographic Society, 1998, Vol. 37, No. 1, p. 25-30

  However, in the technique of Non-Patent Document 1, when the control is performed so that a signal having a narrow exposure pulse width is not generated in order to suppress the frequency of a low latent image potential with unstable development characteristics, the highlight area is binary. Although it is reproduced with smaller dots than in the error diffusion process, there is a problem that individual dots are still easily confirmed. Even if the single pulse does not continue in the main scanning direction, it may continue in the sub-scanning direction or in the oblique direction, and the continuous dots are likely to be perceived. Furthermore, even if the quantization threshold value for quantizing the pixel of interest is controlled based on the quantization value of the pixel immediately before the pixel of interest, a plurality of pixels around the pixel of interest are not considered. Therefore, depending on the situation of pixels around the pixel of interest, the output image may have uneven density or roughness.

  In the image processing apparatus disclosed in Patent Document 1, since the continuity of pixels having the same quantized value of the peripheral pixels of the target pixel is detected, it is possible to suppress the texture due to the specific quantized value. However, the quantized value (pixel value) representing a low gradation that causes uneven density or roughness cannot be controlled at all. That is, when the continuity of pixel values is not detected, there is a problem that even if there is a cause of uneven density or roughness, this cannot be prevented. In an actual image, not only the pixel values are continuous in one direction, but also there are various patterns. If these patterns cannot be detected reliably, the quality of image quality can be improved. Have difficulty.

  The present invention has been made in view of such circumstances, and based on the quantized value of each pixel in the peripheral pixel block around the target pixel composed of a plurality of multi-value quantized pixels, A gradation level is specified, a quantization table (a set of quantization thresholds) for multi-value quantization of the pixel of interest is determined in accordance with the specified gradation level, and multiple quantization thresholds are determined using the determined quantization threshold. By performing value error diffusion processing, it is possible to generate a halftone image with less uneven density or roughness, and in which dots in the highlight area are difficult to perceive, and an image processing method capable of improving image quality, An object of the present invention is to provide an image processing apparatus, an image forming apparatus including the image processing apparatus, a computer program for realizing the image processing apparatus, and a recording medium on which the computer program is recorded.

  The image processing method according to the present invention scans each pixel of an image composed of a plurality of pixels in a predetermined direction, multi-quantizes the pixel value of each pixel based on a quantization threshold, and generates a halftone image. In the image processing method to be generated, a plurality of quantization tables in which a plurality of quantization threshold values and quantization values are associated with each other are stored in advance, and a quantization value of each pixel subjected to multi-value quantization is stored. A peripheral pixel block around the target pixel composed of converted pixels is extracted, and the gradation level around the target pixel is specified based on the quantized value of each pixel of the extracted peripheral pixel block, and the specified floor A quantization table for multi-level quantization of the target pixel is determined according to a degree of key, and the pixel value of the target pixel is multi-level quantized using the determined quantization table .

  The image processing apparatus according to the present invention scans each pixel of an image composed of a plurality of pixels in a predetermined direction, multi-quantizes the pixel value of each pixel based on a quantization threshold, and generates a halftone image. In the image processing device to be generated, means for storing a plurality of quantization tables in which a plurality of quantization thresholds and quantization values are associated, means for storing the quantization values of each pixel subjected to multi-value quantization, Extraction means for extracting a peripheral pixel block around the target pixel composed of multi-value quantized pixels, and based on the quantized value of each pixel of the peripheral pixel block extracted by the extraction means Means for determining the gradation level of the image, a determination means for determining a quantization table for multi-level quantization of the pixel of interest according to the gradation level specified by the means, and determined by the determination means Using the quantization table described above, Characterized in that it comprises a quantizing means for multilevel quantized pixel values of the pixels.

  The image processing apparatus according to the present invention includes an area determination unit that determines at least one of a character area, a halftone dot area, and a photographic area based on a pixel value of each pixel of an image, and the determination unit Determining a quantization table according to the gradation level around the target pixel specified based on the quantization value of each pixel of the peripheral pixel block and the determination result determined by the region determination unit It is configured.

  The image processing apparatus according to the present invention is characterized in that the determining means is configured to determine a quantization table based on a color component of an image.

  The image processing apparatus according to the present invention includes a unit that weights each pixel according to a distance from the target pixel of each pixel of the peripheral pixel block, and a quantization value of each pixel of the peripheral pixel block. Means for assigning a stability coefficient indicating the degree of stability of pixel density, and the determining means is configured to determine a quantization table based on the assigned weighting and stability coefficient. To do.

  An image processing apparatus according to the present invention includes: means for storing an identifier for identifying each quantization table in association with a combination of quantization values of each pixel of a peripheral pixel block; and the peripheral pixel block extracted by the extraction means Means for specifying an identifier based on a quantization value of each pixel of the pixel, and the determining means is configured to determine a quantization table identified by the identifier specified by the means. And

  The image processing apparatus according to the present invention includes an erasing unit that erases the quantized value of the first multi-value quantized pixel in the peripheral pixel block every time the target pixel is scanned.

  The image processing apparatus according to the present invention is characterized in that an integer value from 0 to N−1 is associated with each of N different quantized values.

  The image processing apparatus according to the present invention is characterized in that an integer value from 0 to M−1 (M <N) is associated with each of N different quantized values.

  The image processing apparatus according to the present invention is characterized in that an integer value from 0 to M−1 (M ≦ 2 to the power of <N) is associated with each of N different quantized values.

  The image processing apparatus according to the present invention includes means for setting an integer value to be associated according to the color component of the image.

  The image processing apparatus according to the present invention includes means for setting a quantization threshold according to a color component of an image.

  In the image processing apparatus according to the present invention, a common quantization threshold among a plurality of quantization tables is stored in one quantization table having the quantization threshold, and quantization other than the common quantization threshold is performed. The threshold value is stored in each quantization table.

  An image forming apparatus according to the present invention includes an image processing apparatus according to any one of the above-described inventions, and an image forming unit that forms an output image on a sheet based on image data generated by the image processing apparatus. It is characterized by that.

  The computer program according to the present invention scans each pixel of an image composed of a plurality of pixels in a predetermined direction, multi-quantizes the pixel value of each pixel based on a quantization threshold, and performs halftone processing. In a computer program for generating an image, means for causing a computer to extract a peripheral pixel block around a pixel of interest composed of a plurality of multi-value quantized pixels, and a computer for each of the extracted peripheral pixel blocks Means for specifying a gradation level around the target pixel based on a quantization value of the pixel, and a quantization table for causing the computer to perform multi-level quantization on the target pixel according to the specified gradation level And a means for causing the computer to perform multi-value quantization of the pixel value of the pixel of interest using the determined quantization table And wherein the door.

  A recording medium readable by a computer according to the present invention records the computer program according to the above-described invention.

  In the present invention, a plurality of quantization tables (a set of quantization thresholds) in which a plurality of quantization thresholds and quantization values are associated are stored in advance. Further, each pixel of an image composed of a plurality of pixels is scanned in a predetermined direction, and the pixel value of each pixel is multi-value quantized based on the quantization threshold, and the quantized value of each pixel is stored. When performing multi-level quantization, the peripheral pixel block around the target pixel composed of a plurality of multi-level quantized pixels is extracted, and the target pixel is based on the quantized value of each pixel of the extracted peripheral pixel block Specify the surrounding gradation level. In this case, the size or shape of the peripheral pixel block can be set as appropriate. Assume that the number of gradations of an image is, for example, 0 to 255, and the number of gradations 0 to 255 is quantized to 8 quantization values based on the quantization threshold. When the quantized values are represented by quantized value numbers of 0 to 7 in order from the smallest, the quantized value number “0” indicates that the gradation of the generated image (output image) is “0” and there is no output. Since dots are not printed, the image is most stable (there is no uneven density). The quantized value number “1” is the lowest gradation except “0” for the output image, and the dot formation state is the most unstable when the dots are printed. . Further, as the quantization value number becomes “2” to “7”, the gradation level of the output image becomes higher, and when dots are printed, the dot formation state is gradually stabilized.

  In order to specify the gradation level around the target pixel (for example, the level of lower gradation), for example, the quantization value in the peripheral pixel block is a value with a low gradation (for example, “1”, “2”). ”Etc.) or the position of the pixel. A quantization table (a set of quantization thresholds) for performing multi-level quantization of the pixel of interest is determined according to the specified gradation level (degree of lower gradation), and the determined quantization table is used. The pixel value of the target pixel is subjected to multi-value quantization. That is, when the gradation level in the peripheral pixel block is low (for example, when the number of pixels having the quantized value “1” is large), the output of low gradation that further causes uneven density or roughness is suppressed. Therefore, quantization is performed using a set of quantization thresholds at which low-tone quantization values are difficult to output. Further, when the gradation level in the peripheral pixel block is not so low (for example, when there are no or few pixels having quantized values “1”, “2”, etc.), adjacent low gradation dots Even when printing is performed, the density unevenness or roughness is unlikely to occur, and therefore, quantization is performed using a set of quantization thresholds that can also output low-tone quantized values. Accordingly, it is possible to generate a halftone image with less density unevenness or roughness and in which the dots in the highlight area are difficult to perceive, and the image quality can be improved.

  In the present invention, the area determination unit determines whether the area is at least a character area, a halftone dot area, or a photographic area based on the pixel value of each pixel of the image. The region determination is performed by, for example, a maximum density difference which is a difference between a minimum density value (minimum pixel value) and a maximum density value (maximum pixel value) in an n × m pixel block including the target pixel (for example, 15 × 15), and Calculates the total density busyness, which is the sum of absolute values of density differences between adjacent pixels, and compares it with a plurality of predetermined thresholds to determine the background area, text area, dot area, photo area, etc. can do.

  The determining means determines the quantization table according to the determination result (region identification signal). For example, when it is determined that the area is a character area or a halftone dot area, pixels with small quantized values that tend to cause uneven density or roughness are not continuously present, and adjacent low-tone dots are printed. Even if is performed, density unevenness or roughness is unlikely to occur. Therefore, a set of quantization thresholds that can output quantized values of low gradation regardless of the gradation level around the pixel of interest is used. In addition, when it is determined that the area is a photograph area (an area that is neither a character area nor a dot area), there may be continuous pixels with small quantized values that tend to cause uneven density or roughness in the highlight area. Quantization threshold that makes it difficult for low-tone quantization values to be output with reference to the degree of gradation around the pixel of interest, in order to further suppress low-tone output that causes uneven density or roughness. Select a pair. As a result, the quantized value of the output image can be controlled based on the result of the region determination and the gradation level around the target pixel, and the image output from the image output apparatus can be compared with the conventional multilevel error diffusion processing. In an area where density unevenness or roughness is conspicuous, the density unevenness or roughness can be reduced, and the image quality can be improved so as not to deteriorate the graininess.

  In the present invention, the quantization table is determined based on the color component of the input image. The output characteristics of the image output device may differ for each color component CMYK (C: cyan, M: magenta, Y: yellow, K: black), and even when an image is output with the same quantization value, Depending on the color component, the density unevenness or the appearance of roughness looks different. Therefore, the image quality can be improved by determining a set of quantization thresholds in accordance with the output characteristics of each color component.

  In the present invention, each pixel in the peripheral pixel block is given a weight (weighting coefficient) according to the distance from the target pixel, and according to the quantization value of each pixel in the peripheral pixel block. Thus, a stability coefficient indicating the degree of stability of the density of each pixel is given. In this case, the degree of stability is related to the quantization value. For example, if the quantized value is “0”, dots are not printed, so the output image is the most stable. If the quantized value is “1”, the dot formation state is the most unstable and the output is This is the case where the image density is also most unstable. As the quantized value changes from “2” to “7”, the degree of stability of the density of the output image increases. The determining means determines the quantization table based on the assigned weighting coefficient and stability coefficient. For example, for each pixel in the peripheral pixel block, the stability coefficient corresponding to the quantization value of the pixel and the weighting coefficient assigned to the pixel are integrated, and the integrated value is obtained for all the pixels in the peripheral pixel block. A quantization table (a set of quantization thresholds) is determined based on the magnitude of the evaluated value.

  If the evaluation value is large, the gradation level around the pixel of interest is not so low, and even if dots of low gradation are printed adjacently, uneven density or roughness is unlikely to occur. Quantization is performed using a set of quantization thresholds that can also output a key quantization value. On the other hand, if the evaluation value is small, the gradation level around the pixel of interest is low, and a low gradation quantization value is output to suppress low gradation output that causes uneven density or roughness. Quantization is performed using a set of quantization thresholds that are difficult to be performed. As a result, not only the state of the pixel adjacent to the target pixel, or the state of the pixel in only one direction, but also a wide range of quantized values in the periphery can be referred to, and even for an image in which various patterns exist, The image quality can be improved by preventing density unevenness or roughness.

  In the present invention, an identifier for identifying each quantization table in association with a combination of quantization values of each pixel in the peripheral pixel block (for example, a low gradation degree corresponding to the combination of quantization values is set. A determination signal) is stored, an identifier is specified based on the quantized value of each pixel of the extracted peripheral pixel block, and a quantization table identified by the specified identifier is determined. The association between the combination of the quantized values and the identifier can be configured by, for example, a lookup table. As a result, it is possible to select a corresponding quantization table from the quantization value of each pixel in the peripheral pixel block only by referring to the lookup table, and it is not necessary to configure an arithmetic circuit, and the circuit scale is increased. Can be suppressed.

  In the present invention, each time the target pixel is scanned, the quantized value of the first multi-value quantized pixel in the peripheral pixel block is erased. Thereby, when referring to the quantized values of the peripheral pixels of the target pixel, it is not necessary to store the quantized values of all the pixels of the input image, and the storage area can be reduced.

  In the present invention, an integer value from 0 to N−1 is associated with each of N different quantized values. As a result, the quantized value can be stored with a small number of bits, so that the required amount of storage area can be reduced.

  In the present invention, an integer value from 0 to M−1 (M <N) is associated with each of N different quantized values. As a result, the quantized value can be stored with a small number of bits, so that the required amount of storage area can be reduced.

  In the present invention, an integer value from 0 to M−1 (M ≦ 2 to power <N) is associated with each of N different quantized values. Thereby, the quantized value can be expressed by a smaller number of bits, and the storage area can be further reduced.

  In the present invention, an integer value to be associated is set according to the color component of the image. Thereby, it is possible to output a quantized value in consideration of the characteristics of each color component of the output image.

  In the present invention, the quantization threshold is set according to the color component of the image. Thereby, it is possible to output a quantized value in consideration of the characteristics of each color component of the output image.

  In the present invention, a common quantization threshold value among a plurality of quantization tables is stored in one quantization table having the quantization threshold value, and quantization values other than the common quantization threshold value are stored. The threshold value is stored in each quantization table. Thereby, a storage area can be reduced.

  In the present invention, the peripheral pixel block around the target pixel composed of a plurality of multi-value quantized pixels is extracted, and the target pixel is based on the quantized value of each pixel of the extracted peripheral pixel block Specify the surrounding gradation level. A quantization table (a set of quantization thresholds) for multilevel quantization of the pixel of interest is determined according to the specified gradation level, and the pixel value of the pixel of interest is multivalued using the determined quantization table By quantizing, it is possible to generate a halftone image with little density unevenness or roughness and in which dots in the highlight area are difficult to perceive, and the image quality can be improved.

  Further, in the present invention, based on the pixel value of each pixel of the image, it is determined whether it is at least a character area, a halftone dot area, or a photographic area, and the gradation of peripheral pixels of the target pixel By determining the quantization table according to the degree and the determination result (region identification signal), the quantization value of the output image is controlled based on the gradation degree of the surrounding pixels of the target pixel and the region determination result. Compared with the conventional multi-value error diffusion processing, the density unevenness or roughness of the image output from the image output apparatus can be reduced, and the graininess is not deteriorated. Image quality can be improved.

  In the present invention, by determining the quantization table based on the color component of the image, a set of quantization thresholds can be determined in accordance with the output characteristics of each color component, and the image quality can be further improved. Can do.

  In the present invention, each pixel in the peripheral pixel block is given a weight (weighting coefficient) according to the distance from the target pixel, and according to the quantization value of each pixel in the peripheral pixel block. By adding a stability coefficient indicating the degree of density stability of each pixel and determining a quantization table based on the assigned weighting coefficient and stability coefficient, only the adjacent pixel to the target pixel or only in one direction In addition to the state of pixels, the surrounding quantized values can be referenced, and even for images with various patterns, density unevenness or roughness is prevented to improve image quality. be able to.

  In the present invention, an identifier for identifying each quantization table is stored in association with a combination of quantization values of each pixel of the peripheral pixel block, and each pixel of the extracted peripheral pixel block is stored. By specifying the identifier based on the quantized value and determining the quantization table identified by the specified identifier, it is not necessary to configure an arithmetic circuit in particular, and an increase in circuit scale can be suppressed.

  In the present invention, each time the target pixel is scanned, the quantization value of the first multi-value quantized pixel in the peripheral pixel block is deleted, thereby quantizing the peripheral pixel of the target pixel. When referring to the values, it is not necessary to store the quantized values of all the pixels of the input image, and the storage area can be reduced.

  In the present invention, since the integer values from 0 to N-1 can be associated with each of N different quantized values, the quantized values can be stored with a small number of bits. The required amount of area can be reduced.

  In the present invention, an integer value from 0 to M-1 (M <N) is associated with each of N different quantized values so that the quantized value is stored with a small number of bits. Therefore, the necessary amount of storage area can be reduced.

  Further, in the present invention, an integer value from 0 to M−1 (M ≦ 2 to the power of <N) is associated with each of N different quantized values, whereby the quantized value is further reduced in the number of bits. The storage area can be further reduced.

  In the present invention, by setting an integer value to be associated according to the color component of the image, it is possible to output a quantized value in consideration of the characteristics of each color component of the output image.

  In the present invention, by setting the quantization threshold according to the color component of the image, it is possible to output a quantization value in consideration of the characteristics of each color component of the output image.

  In the present invention, a common quantization threshold value among a plurality of quantization tables is stored in one quantization table having the quantization threshold value, and quantization values other than the common quantization threshold value are stored. The storage area can be reduced by storing the threshold in each quantization table.

Embodiment 1
Hereinafter, the present invention will be described with reference to the drawings illustrating embodiments. FIG. 1 is a block diagram illustrating a configuration of an image forming apparatus 100 including an image processing apparatus according to the present invention. The image forming apparatus 100 (for example, a digital color copier, a multi-function machine, a multi-function machine having a printer function, a fax function or an e-mail delivery function) includes a color image input device 1, a color image processing device 2 (image processing device), an image A color image output device 3 as a forming unit, an operation panel 4 for performing various operations, and the like are provided. Image data of RGB (R: red, G: green, B: blue) analog signals obtained by reading a document with the color image input device 1 is output to the color image processing device 2, and the color image processing device 2. Then, a predetermined process is performed and output to the color image output device 3 as a digital color signal of CMYK (C: cyan, M: magenta, Y: yellow, K: black).

  The color image input device 1 is, for example, a scanner including a CCD (Charged Coupled Device), reads a reflected light image from a document image as an RGB analog signal, and outputs the read RGB signal to the color image processing device 2. . The color image output device 3 is an image forming unit using an electrophotographic system or an inkjet system that outputs image data of a document image onto a recording sheet. The color image output device 3 may be a display device such as a display.

  The color image processing apparatus 2 includes processing units to be described later, and is configured by an ASIC (Application Specific Integrated Circuit) or the like.

  The A / D converter 20 converts the RGB signal input from the color image input device 1 into a digital signal having a predetermined number of bits, and outputs the converted RGB signal to the shading correction unit 21.

  The shading correction unit 21 performs correction processing for removing various distortions generated in the illumination system, imaging system, imaging system, and the like of the color image input apparatus 1 on the input RGB signal.

  The input tone correction unit 22 adjusts the color balance of the RGB signal (RGB reflectance signal) from which various distortions have been removed by the shading correction unit 21 and is adopted in the color image processing apparatus 2 such as a density signal. The image processing system is converted into a signal that is easy to handle. The input tone correction unit 22 performs image quality adjustment processing such as background density removal or contrast, and outputs the processed RGB signal to the region separation processing unit 23.

  Based on the input RGB signal, the region separation processing unit 23 determines whether each pixel in the input image is a base region, a character region, a halftone region, or a photographic region, and performs region separation. Based on the determination result, the region separation processing unit 23 outputs a region identification signal indicating to which region each pixel belongs to a color correction unit 24, a black generation and under color removal unit 25, a spatial filter processing unit 26, a gradation reproduction. The data is output to the processing unit 28. The region separation processing unit 23 outputs the input RGB signal as it is to the subsequent color correction unit 24.

  As the region separation processing, for example, a maximum density difference which is a difference between a minimum density value (minimum pixel value) and a maximum density value (maximum pixel value) in an n × m pixel block (for example, 15 × 15) including the target pixel. And calculating the total density busyness, which is the sum of absolute values of density differences between adjacent pixels, and comparing each pixel with a plurality of predetermined thresholds, thereby making each pixel a background area, a photographic area (continuous tone area) ), Character area or halftone dot area.

  Since the density distribution of the background region usually has little density change, both the maximum density difference and the total density busyness are very small. The density distribution in the photographic area has a smooth density change, and the maximum density difference and the total density busyness are both small but larger than the background area. The density distribution in the halftone dot area varies depending on the halftone dots, but the total density busyness changes by the number of halftone dots, so the ratio of the total density busyness to the maximum density difference is large. Become. Therefore, when the total density busyness is larger than the product of the maximum density difference and the character / halftone determination threshold, it is determined that the area is a halftone area. In the density distribution of the character area, the maximum density difference is large and the total density busyness increases accordingly. However, since the density change is smaller than that in the halftone dot area, the total density busyness is smaller than that in the halftone dot area. Accordingly, when the total density busyness is smaller than the product of the maximum density difference and the character / halftone dot determination threshold, the character area is determined.

  Comparing the calculated maximum density difference with the maximum density difference threshold, and comparing the calculated total density busyness with the total density busyness threshold, the maximum density difference is smaller than the maximum density difference threshold, and the total When the density busyness is smaller than the total density busyness threshold, it is determined that the target pixel is a background / photo area, and otherwise, it is determined as a character / halftone area. If it is determined to be the background / photo area, the calculated maximum density difference is compared with the background / photo determination threshold. If the maximum density difference is smaller, it is determined to be the background area, and the maximum density difference is determined. If is larger, it is determined to be a photo area. When it is determined that the area is a character / halftone area, the calculated total density busyness is compared with the integrated value of the maximum density difference and the character / halftone determination threshold value. If the total density busyness is smaller If the total density busyness is larger, it can be determined that the area is a halftone dot area.

  The color correction unit 24 performs a process of removing color turbidity based on the spectral characteristics of the CMY color material including unnecessary absorption components in order to faithfully reproduce the color. As a processing method, a method of storing the correspondence between the RGB signal on the input side and the CMY signal on the output side as an LUT (Look Up Table), or the value of (R, G, B) is set to (C, M , Y), a color masking method using a conversion matrix for conversion into values.

For example, when the color masking method is used, an L ^* a ^* b ^* value (CIE 1976 L ^* a ^* b ^* signal (CIE: Commission ^{) of} a color output when certain CMY data is given to the color image output device 3. International de l'Eclairage; let the color image input device 1 read a color patch having the same L ^* a ^* b ^* as L ^* : brightness, a ^* , b ^* : chromaticity)) A large number of sets of RGB data and CMY data given to the color image output device 3 are prepared, each coefficient of the above-described conversion matrix is calculated from the combination, and color correction processing is performed using the calculated coefficient. . If you want to increase the accuracy, you can add higher-order terms of second order or higher.

  The black generation and under color removal unit 25 generates a K (black) signal based on the CMY signal input from the color correction unit 24, and subtracts the K signal from the input three-color CMY signal to generate a new CMY signal. A signal is generated, and the generated four-color CMYK signals are output to the spatial filter processing unit 26.

  An example of processing in the black generation and under color removal unit 25 is shown. For example, in the process of generating black by skeleton black, the input / output characteristic of the skeleton curve is y = f (x), the input data is C, M, Y, and the output data is C ′, M ′. , Y ′, K ′, and the UCR (Under Color Removal) rate is α (0 <α <1), the data output by the black generation and under color removal processing is K ′ = f {min (C, M, Y)}, C ′ = C−αK ′, M ′ = M−αK ′, and Y ′ = Y−αK ′.

  The spatial filter processing unit 26 performs spatial filter processing using a digital filter based on the region identification signal on the CMYK signal input from the black generation and under color removal unit 25. As a result, the spatial frequency characteristics of the image data are corrected, and blurring of the output image in the color image output device 3 or deterioration of graininess is prevented. For example, the spatial filter processing unit 26 performs sharp enhancement processing on the regions separated into character regions by the region separation processing unit 23 to enhance the reproducibility of black characters or color characters, and emphasizes high frequency components. In addition, the region separated as the halftone dot region by the region separation processing unit 23 is reproduced by the spatial filter processing unit 26 as much as possible without performing the low-pass filter processing for removing the halftone dot component. As possible, high-frequency components are emphasized by passing through (prohibiting) spatial filtering or sharpening enhancement. For the halftone area, the dithering process is smoothed to prevent moire. However, when the smoothing process is performed, the halftone dot shape is lost, which is not preferable in reproducing the halftone dots. Therefore, in the present invention, the halftone dot form is preserved by performing no processing on the halftone dot region (through the spatial filter processing) or by performing weak enhancement processing.

  FIG. 2 is an explanatory diagram showing an example of filter coefficients used for weak enhancement processing. The spatial filter processing in the spatial filter processing unit 26 is a through process or a sharp enhancement process in the case of a halftone dot area, but a common filter process can be performed regardless of the area. The output tone correction unit 27 performs an output tone correction process for converting the CMYK signal input from the spatial filter processing unit 26 into a halftone dot area ratio that is a characteristic value of the color image output device 3, and The CMYK signal after the tone correction processing is output to the gradation reproduction processing unit 28.

  The gradation reproduction processing unit 28 applies gradation to the image data of the CMYK signal input from the output gradation correction unit 27 so that the image can finally reproduce the gradation in a pseudo manner based on the region identification signal. Reproduction processing (halftone generation) is performed. In the present invention, a halftone is generated using a multilevel error diffusion method.

  The color image processing apparatus 2 temporarily stores the image data (CMYK signal) processed by the gradation reproduction processing unit 28 in a storage unit (not shown), and stores the image data in the storage unit at a predetermined timing for image formation. And the read image data is output to the color image output device 3. The color image output device 3 outputs an image on a recording medium (for example, paper), and is an electrophotographic or inkjet color image output device, but is not limited thereto. is not.

  The operation panel 4 includes, for example, a touch panel in which a display unit such as a liquid crystal display and an operation unit such as a setting button are integrated. Based on information input from the operation panel 4, the color image input device 1, color The operations of the image processing device 2 and the color image output device 3 are controlled. Each of the above processes is controlled by a CPU (Central Processing Unit: control means) not shown.

  FIG. 3 is a block diagram showing the configuration of the gradation reproduction processing unit 28. The gradation reproduction processing unit 28 includes an adder 281, a quantization processing unit 282 having a comparator, a quantization error calculating unit 283 having a subtractor, a diffusion error calculating unit 284 having a multiplier, a RAM (Random Access Memory), and the like. An accumulation error storage unit 285 composed of ROM, a diffusion coefficient storage unit 286 composed of ROM (Read Only Memory), a random number generator 287, a quantization threshold storage unit 288 composed of ROM, etc., and a surrounding pixel determination unit 289 Etc. The gradation reproduction processing unit 28 scans the target pixel (processing target pixel) of the input image composed of the input image data in a predetermined direction, and performs predetermined processing for each scanned target pixel.

  Each pixel of the input image data input to the gradation reproduction processing unit 28 is composed of four color components CMYK, and halftone generation using a multi-value error diffusion method is performed for each color component. For this reason, multi-value error diffusion processing can be performed in order for each color component by a common circuit, or multi-value error diffusion processing for each color component of CMYK can be performed in parallel by separate circuits. Since multi-level error diffusion of each color component is performed in the same manner, the following description will be made on the processing for one color component, and only the differences will be described for the processing on other color components.

  The adder 281 adds a storage error (diffusion error) corresponding to the position of the target pixel acquired from the storage error storage unit 285 to the pixel value (density value) of the target pixel, and calculates the pixel value to which the storage error has been added. The data is output to the quantization processing unit 282 and the quantization error calculation unit 283.

  Based on the determination signal input from the surrounding pixel determination unit 289, the quantization processing unit 282 selects a corresponding quantization table (quantum) from among a plurality of quantization tables stored (stored) in the quantization threshold storage unit 288. Select a threshold value set). The quantization processing unit 282 compares the input pixel value with a plurality of quantization thresholds in the selected quantization table, performs multi-value quantization, and outputs the quantization value as output image data. For example, assuming that the number of gradations of the input image is 0 to 255, the number of gradations 0 to 255 is changed to 8 quantized values (for example, 0, 36, 73, 109, 146, 182) based on the quantization threshold. 219, 255. These may be replaced with quantized value numbers of 0 to 7.) Also, the quantization processing unit 282 outputs the calculated quantization value to the quantization error calculation unit 283 and the surrounding pixel determination unit 289.

  The quantization processing unit 282 selects a corresponding quantization table from a plurality of quantization tables according to the region identification signal input from the region separation processing unit 23. The relationship between the determination signal and the quantization table will be described later. For example, when it is determined that the area is a character area or a halftone dot area, pixels with small quantized values that tend to cause uneven density or roughness are not continuously present, and adjacent low-tone dots are printed. Since the density unevenness or roughness is hardly generated even if the above is performed, a quantization table capable of outputting a quantized value of low gradation is selected. In addition, when it is determined that the area is a photograph area (an area that is neither a character area nor a dot area), there may be continuous pixels with small quantized values that tend to cause uneven density or roughness in the highlight area. Therefore, in order to further suppress the output of low gradation that causes density unevenness or roughness, a quantization table that does not easily output a low gradation quantization value is selected.

  Also, the quantization processing unit 282 can determine the quantization table according to the combination of the determination signal and the region identification signal. In this case, for example, when it is determined that the region is a character region or a halftone dot region, pixels with small quantized values that tend to cause unevenness in density or roughness do not exist so continuously, and adjacent to low gradations. Even if dots are printed, uneven density or roughness is unlikely to occur, so a quantization table that can output a quantized value of low gradation is selected regardless of the determination signal. On the other hand, when it is determined that the area is a photograph area (an area that is neither a character area nor a dot area), a quantization table is selected in accordance with a determination signal as will be described later.

  FIG. 4 is an explanatory diagram showing the structure of the quantization table. The quantization table includes a quantization threshold, a range of pixel values quantized by the quantization threshold, a quantization value, a quantization value number, a corresponding value associated with the quantization value, and the like. If the number of quantized values is N, it is not the quantized value itself that is stored (stored) in the quantized threshold value storage unit 288, but from the smallest quantized value in order from 0 to N It can correspond to an integer value of -1. As a result, the number of bits of information to be stored can be reduced and the required amount of storage area can be suppressed. In the figure, the range of pixel values is provided for explanation, and is not necessarily a component of the quantization table.

  When the number of gradations of each pixel of the input image is, for example, 256 gradations from 0 to 255, the number of gradations is set by setting the quantization threshold to 18, 55, 91, 128, 164, 201, 237. Can be quantized into eight quantized values 0, 36, 73, 109, 146, 182, 219, 255 (quantized value numbers of 0 to 7). As shown in FIG. 4, when the pixel value is 0, the quantization value is 0 because it is equal to or less than the quantization threshold value 18. When the pixel value (density value) is 19 to 55, the quantized value is 35 (quantized value number 1). Hereinafter, similarly, the quantization value number becomes 2 to 7 according to the pixel value of each pixel.

  When the quantization value number is 0, the gradation of the output image is 0, that is, there is no output and dot printing is not performed, so that the image is most stable (no density unevenness or the like). Further, when the quantization value numbers are 1 and 2, the gradation of the output image is low, and when dots are printed, the dot formation state is least stable. Further, as the quantization value number becomes 3 to 7, the gradation level of the output image becomes higher, and when dots are printed, the dot formation state is gradually stabilized.

  The corresponding value is for integrating the eight quantized value numbers with a smaller integer value. For example, there is no output, dot printing is not performed, and the quantized value that is most stable as an output image Corresponding value 0 is assigned to number 0. Corresponding value 1 is assigned collectively to quantized value numbers 1 and 2 that have low gradation and the best stability of the output image. Hereinafter, correspondence values 2 and 3 are assigned in the same manner. As a result, the correspondence value 0 is the most stable image (no output), the correspondence value 1 is the most unstable image with the low gradation, and the stability of the image increases as the correspondence value increases. become. In addition, when a correspondence value consisting of four integer values is assigned in association with a quantization value number consisting of eight integer values, the number of bits can be reduced from 3 to 2, and the quantization table The storage capacity when storing can be further reduced.

  The quantization error calculation unit 283 calculates an error (quantization error) between the quantization value input from the quantization processing unit 282 and the pixel value input from the adder 281 and diffuses the calculated quantization error. The data is output to the error calculation unit 284.

  The diffusion error calculation unit 284 is a peripheral pixel of the pixel of interest based on the quantization error input from the quantization error calculation unit 283 and each diffusion coefficient of the error diffusion matrix acquired from the diffusion coefficient storage unit 286. A diffusion error that is diffused to each unprocessed pixel is calculated. The diffusion error calculation unit 284 stores the calculated diffusion error in the accumulation error storage unit 285.

  FIG. 5 is an explanatory diagram showing an example of an error diffusion matrix. The error diffusion matrix includes, for example, a right pixel (pixel to be scanned next), a lower left pixel, a pixel immediately below, and a lower right pixel (all of which are the target pixels) with respect to the target pixel (* in the figure). Corresponding to each position of a pixel on the next line of a certain line of interest), it is composed of diffusion coefficients of 7/16, 3/16, 5/16, and 1/16. Thereby, the quantization error in the pixel of interest is 7/16, 3/16, 5/16, and 1/16 of the quantization error for the right pixel, the lower left pixel, the immediately lower pixel, and the lower right pixel. Each value is diffused.

  A plurality of error diffusion matrices having different diffusion coefficients are stored, and the error diffusion matrix to be used is an area identification signal (for example, a halftone area or a photographic area) input from the area separation processing unit 23. And / or a random number generated by the random number generator 287 for each pixel of interest.

  The surrounding pixel determination unit 289 sequentially stores the quantization value of each pixel obtained by the quantization processing unit 282. Each time the target pixel is scanned, the peripheral pixel determination unit 289 extracts a peripheral pixel block including a plurality of quantized pixels of the target pixel. The surrounding pixel determination unit 289 specifies the low gradation level around the target pixel based on the quantized value of each pixel of the extracted surrounding pixel block.

  FIG. 6 is an explanatory diagram illustrating an example of a peripheral pixel block. The peripheral pixel block is, for example, a pixel a in the upper left, a pixel b immediately above, and a pixel c in the upper right with respect to the target pixel (marked * in the figure). 4), and the left pixel d (the most recently quantized pixel).

  The neighboring pixel determination unit 289 determines the situation (low gray scale level) of the neighboring pixel of the target pixel based on the quantized value of each pixel in the neighboring pixel block (more specifically, the corresponding value associated with the quantized value). The determination signal that can determine the degree) is specified, and the specified determination signal is output to the quantization processing unit 282. The surrounding pixel determination unit 289 outputs a determination signal for each pixel by scanning the target pixel in a predetermined direction.

  Each time the target pixel is scanned, the quantized value (corresponding value) of the pixel first quantized in the peripheral pixel block is no longer necessary to determine the status of the peripheral pixel. By deleting the quantized values (corresponding values), it is not necessary to store the quantized values of all the pixels of the input image when referring to the quantized values of the peripheral pixels of the target pixel, and the storage area is reduced. can do.

  The determination signal can be divided into several stages according to the degree of low gradation in which the situation of the pixels in the peripheral pixel block causes density unevenness or roughness. For example, the determination signal can be divided into 0 to 4 according to the situation of the pixels in the peripheral pixel block.

  For example, the peripheral pixel determination unit 289 determines that there is no factor such as uneven density or roughness and the image is most stable when there is no pixel having a corresponding quantization value of 1 in the peripheral pixel block. The determination signal 0 is output. In addition, when there is one pixel having a corresponding quantization value of 1 in the peripheral pixel block, the peripheral pixel determination unit 289 has some factors such as uneven density or roughness, and the stability of the image is slightly reduced. As a result, the determination signal 1 is output.

  In addition, when the corresponding value of the pixels a and c in the peripheral pixel block is 1, the peripheral pixel determination unit 289 determines that a factor such as density unevenness or roughness increases and the stability of the image is deteriorated. Is output. In addition, when the corresponding value of the pixels b and d in the peripheral pixel block is 1, the peripheral pixel determination unit 289 determines that factors such as uneven density or roughness further increase and the stability of the image is significantly reduced. Signal 3 is output. In this case, there are two pixels having the corresponding value 1 in the peripheral pixel block, but the case where the corresponding value 1 is present in the pixels b and d is greater than the case where the corresponding value 1 is present in the pixels a and c. This is likely to cause uneven density. Further, when the corresponding value of all the pixels in the peripheral pixel block is 1, the peripheral pixel determination unit 289 determines that the image stability is the worst due to factors such as density unevenness or roughness. 4 is output. Note that the determination signals 0 to 4 are examples, and are not limited to numbers, and the number of determination signals is not limited to five. Further, the corresponding value 1 is used for the determination of the low gradation level of the peripheral pixel block. However, the present invention is not limited to this, and other corresponding values such as a combination of the corresponding values 1 and 2 may be used. it can.

  The quantization threshold storage unit 288 stores (stores) quantization tables having different quantization thresholds corresponding to the determination signal output from the neighboring pixel determination unit 289.

  FIG. 7 is an explanatory diagram showing the structure of the quantization table corresponding to the determination signal 0. When the determination signal is 0, there is no low gradation pixel that is likely to cause density unevenness or roughness around the target pixel (the most stable state in which the gradation is 0 and no dots are printed). is there. In this case, the quantization threshold of the quantization table is, for example, seven values of 18, 55, 91, 128, 164, 201, and 237, which are the same values as the eight quantization thresholds shown in FIG. is there.

  In this case, when the pixel value (density value) of each pixel of the input image is 0 to 18, the quantized value is 0 (quantized value number 0). When the pixel value (density value) of each pixel of the input image is 19 to 55, the quantized value is 36 (quantized value number 1). Thereafter, the quantization is performed in the same manner, the corresponding value 0 is assigned to the quantized value number 0, the corresponding value 1 is assigned to the quantized value numbers 1 and 2, and the corresponding value is similarly assigned. As a result, even if the pixel value (density value) of the pixel of the input image has a low gradation, the pixel value (density value) is quantized with a small quantized value, and dots are printed at a density corresponding to the pixel value (density value). Is called.

  FIG. 8 is an explanatory diagram showing the structure of the quantization table corresponding to the determination signal 1. When the determination signal is 1, there are some factors such as uneven density or roughness around the pixel of interest. In this case, the quantization threshold values of the quantization table are, for example, six values 55, 91, 128, 164, 201, and 237.

  In this case, when the pixel value (density value) of each pixel of the input image is 0 to 55, the quantized value is 0 (quantized value number 0). When the pixel value (density value) of each pixel of the input image is 56 to 91, the quantized value is 73 (quantized value number 2). Thereafter, the quantization is performed in the same manner, the corresponding value 0 is assigned to the quantized value number 0, the corresponding value 1 is assigned to the quantized value number 2, and the corresponding value is assigned in the same manner. As a result, when the pixel value (density value) of the pixel of the input image has a low gradation, the quantized value is set to 0 so that a low quantized value that tends to cause uneven density or roughness is not output. .

  FIG. 9 is an explanatory diagram showing the structure of the quantization table corresponding to the determination signal 2. When the determination signal is 2, factors such as density unevenness or roughness increase around the pixel of interest. In this case, the quantization threshold values of the quantization table are, for example, five values 91, 128, 164, 201, and 237.

  In this case, when the pixel value (density value) of each pixel of the input image is 0 to 91, the quantized value is 0 (quantized value number 0). When the pixel value (density value) of each pixel of the input image is 92 to 128, the quantized value is 109 (quantized value number 3). Thereafter, the quantization is performed in the same manner, and the corresponding value 0 corresponds to the quantized value 0 (integer value 0), and corresponds to the quantized value 109 (quantized value number 3) and the quantized value 146 (quantized value number 4). The corresponding value is assigned to value 2 in the same manner. As a result, when the pixel value (density value) of the pixel of the input image has a low gradation, the quantized value is set to 0 so that a low quantized value that tends to cause density unevenness or roughness is not output. To do.

  FIG. 10 is an explanatory diagram showing the structure of the quantization table corresponding to the determination signal 3. When the determination signal is 3, factors such as density unevenness or roughness around the target pixel are further increased. In this case, the quantization threshold values of the quantization table are, for example, four values of 128, 164, 201, and 237.

  In this case, when the pixel value (density value) of each pixel of the input image is 0 to 128, the quantized value is 0 (quantized value number 0). When the pixel value (density value) of each pixel of the input image is 129 to 164, the quantized value is 146 (quantized value number 4). Hereinafter, the quantization is performed in the same manner, the corresponding value 0 is applied to the quantized value 0 (quantized value number 0), the corresponding value 2 is applied to the quantized value 146 (quantized value number 4), and the corresponding value is similarly applied. Is assigned. As a result, when the pixel value (density value) of the pixel of the input image has a low gradation, the quantized value is set to 0, and a low quantized value that tends to cause density unevenness or roughness is not output. To do.

  FIG. 11 is an explanatory diagram showing the structure of the quantization table corresponding to the determination signal 4. When the determination signal is 4, factors such as density unevenness or roughness increase further around the pixel of interest, which is the most unstable state when dots are printed. In this case, the quantization threshold value of the quantization table is, for example, two values 201 and 237.

  In this case, when the pixel value (density value) of each pixel of the input image is 0 to 201, the quantized value is 0 (quantized value number 0). When the pixel value (density value) of each pixel of the input image is 202 to 237, the quantized value is 219 (quantized value number 6). Hereinafter, it is quantized in the same manner, the corresponding value 0 is given to the quantized value 0 (quantized value number 0), the corresponding value 3 is given to the quantized value 219 (quantized value number 6), and the corresponding value is also given below. Is assigned. Accordingly, since the peripheral pixels of the target pixel are only low gradation pixels (small quantized values) and the dot formation state is the most unstable state, the target pixel has a low gradation, that is, a small gradation. Image quality deterioration is prevented by not outputting quantized values or printing dots.

  Note that the above-described determination signal and the quantization table determined thereby are examples, and the quantization threshold, the quantization value, the quantization value number, the corresponding value, and the like are not limited thereto. In each quantization table, a common quantization threshold (or corresponding value) is stored in one quantization table having the quantization threshold (or corresponding value), and a common quantization threshold (or corresponding value) is stored. By storing other quantization threshold values (corresponding values) in each quantization table, the storage area can be reduced.

  The quantization table can also be determined according to the color component of the image. For example, the quantization table shown in FIG. 4 can be used when multilevel error diffusion processing is performed for each color component of cyan, magenta, and yellow (CMY), and for the color component of black (K). Multi-level error diffusion processing can be performed using different quantization tables.

  FIG. 12 is an explanatory diagram showing the structure of the quantization table when the color component is black. The difference from the quantization table of FIG. 4 is the corresponding value associated with the quantized value. That is, in the case of a black color component, the corresponding value 0 is assigned corresponding to the quantized value 0 (quantized value number 0), and the quantized value 36 (quantized value number 1), 73 (quantized value number). 2) and corresponding value 1 corresponding to 109 (quantized value number 3) and corresponding value 2 corresponding to quantized values 146 (quantized value number 4) and 182 (quantized value number 5). The corresponding value 3 is assigned corresponding to the assigned and quantized value 219 (quantized value number 6) and 255 (quantized value number 7). The output characteristics of the color image output device 3 may differ for each color component, and even if an image is output with the same signal, the density unevenness or the roughness appears differently depending on the color component. By making the corresponding value corresponding to the quantized value different for each color component, it is possible to output an image in accordance with the output characteristics and improve the image quality.

  When the peripheral pixel determination unit 289 determines the low gradation level of the peripheral pixel of the target pixel based on the quantized value of each pixel in the peripheral pixel block (or the corresponding value associated with the quantized value) A relationship between a combination of quantized values (or corresponding values) of each pixel of the pixel block and the determination signal can be configured as a lookup table.

  FIG. 13 is an explanatory diagram showing the configuration of the peripheral pixel determination lookup table. As shown in FIG. 13, the peripheral pixel determination lookup table is a table in which determination signals are assigned corresponding to combinations of quantized values of the pixels a, b, c, and d of the peripheral pixel block. When determining the low gradation level of the peripheral pixel of the target pixel, it is not necessary to provide a special arithmetic circuit by using the peripheral pixel determination lookup table, and the circuit scale of the apparatus can be reduced. In addition, the surrounding pixel determination lookup table may be provided with a corresponding value instead of the quantization value. Also, different peripheral pixel determination lookup tables can be used depending on the color components. In addition, when a corresponding value consisting of four integer values is assigned in association with a quantized value consisting of eight integer values, the number of bits can be reduced from 3 to 2, and the peripheral pixel determination look The storage capacity for storing the up table can be further reduced.

  In multilevel error diffusion processing, a required error diffusion matrix can be selected and used as appropriate.

  FIG. 14 is an explanatory diagram showing another example of the error diffusion matrix. The error diffusion matrix includes, for example, two pixels adjacent to the right side, four pixels on the two lines on the lower left side, two pixels on the two lines immediately below the target pixel (* in the figure), right Corresponding to each position of the four pixels on the lower two lines, each pixel is constituted by a diffusion coefficient. The diffusion coefficients have different values as shown in FIGS. 14 (a) to 14 (d). As a result, the quantization error in the pixel of interest includes two adjacent pixels on the right side, four pixels on the lower left two lines, two pixels on the lower two lines, and four pixels on the lower right two lines. It is diffused to a total of 12 pixels. Also in this case, according to the region identification signal (for example, according to the halftone dot region or the photograph region) input from the region separation processing unit 23 and / or the random number generated by the random number generator 287 for each target pixel. Selected.

  In the multi-value error diffusion process, necessary peripheral pixel blocks can be appropriately selected and used.

  FIG. 15 is an explanatory diagram showing another example of the peripheral pixel block. The peripheral pixel block includes, for example, four pixels on the upper left two lines, two pixels on the upper two lines, and four pixels on the upper right two lines with respect to the target pixel (marked * in the figure). It consists of 12 pixels, two pixels adjacent to the left side.

  In this case, for example, a weighting coefficient can be given to all the pixels of the peripheral pixel block or a part of the pixels according to the distance from the target pixel (the number of separated pixels). For example, as shown in FIG. 15, a weighting coefficient α is given to the pixels d and b, a weighting coefficient β is given to the pixels a and c, and a weighting coefficient γ is given to the pixels e and f. . In this case, the weighting coefficients have a relationship of α> β> γ.

  When determining the quantized value of the pixel of interest by assigning a weighting coefficient according to the distance from the pixel of interest, taking into account the influence of the low gradation level of surrounding pixels according to the distance from the pixel of interest Can do. In addition, a situation in a wide range around the target pixel can be obtained without determining the quantization value of the target pixel only by the influence of one pixel adjacent to the target pixel or a peripheral pixel in only one direction with respect to the target pixel. Therefore, the image quality can be further improved.

  In addition, the low gradation level in the surrounding pixel block, that is, the unstable factor of the image due to factors such as density unevenness or roughness, or conversely, the stability level of the density of the output image depends on the quantization value. Can be determined as

  FIG. 16 is an explanatory diagram showing the relationship between the quantization value and the stability coefficient. As shown in FIG. 16, when the quantized value is 0, there is no output and dot printing is not performed, so the image is most stable, and thus a stability coefficient 8 is given. When the quantization value number is 1, the gradation of the pixel is the lowest gradation other than 0, the dot formation state is the most unstable, and the density of the output image is also the most unstable. The most unstable stability coefficient 1 is given. Hereinafter, similarly, as the quantized value increases, a stability coefficient having a large value is given.

  For each pixel of the peripheral pixel block, the peripheral pixel determination unit 289 integrates the stability coefficient corresponding to the quantization value of the pixel and the weighting coefficient assigned to the pixel, and the integrated value is added to all the pixels of the peripheral pixel block. The quantization table is determined on the basis of the magnitude of the evaluation value obtained by adding. For example, when the evaluation value is the largest, the determination signal 0 is output, and when the evaluation value is the smallest, the determination signal 4 is output. Note that the number of determination signals is not limited to 5 (0 to 4).

  As a result, not only the state of the pixel adjacent to the target pixel, or the state of the pixel in only one direction, but also a wide range of quantized values in the periphery can be referred to, and even for an image in which various patterns exist, It is possible to improve the quality of image quality by preventing density unevenness or roughness.

  Next, the operation of the color image processing apparatus 2 will be described. FIG. 17 is a flowchart showing the procedure of multilevel error diffusion processing of the color image processing apparatus 2 (hereinafter referred to as processing unit). The multi-level error diffusion process is not only configured by a dedicated hardware circuit, but a computer program that defines the multi-level error diffusion process procedure is loaded into a personal computer equipped with a CPU, RAM, ROM, etc. This can also be done by causing the CPU to execute the computer program.

  The processing unit scans each pixel of the input image in a predetermined direction, and adds an accumulation error (diffusion error) corresponding to the position of the target pixel to the pixel value (density value) of the target pixel (S11). The processing unit specifies the determination signal of the peripheral pixel according to the low gradation level of the pixel in the peripheral pixel block (S12). The processing unit selects a set of quantization thresholds, that is, a quantization table based on the identified determination signal (S13), and calculates a quantization value of the pixel of interest using the determined quantization threshold ( S14).

  The processing unit calculates a quantization error which is a difference between the pixel value of the target pixel and the quantization value (S15). The processing unit randomly selects an error diffusion matrix according to the region identification signal of the region to which the pixel of interest belongs or a random number, and based on the calculated quantization error and each diffusion coefficient of the selected error diffusion matrix, A diffusion error that diffuses to each pixel that is a peripheral pixel and has not been subjected to quantization processing is calculated (S16).

  The processing unit determines whether or not the processing has been completed for all pixels (S17). If the processing has not been completed (NO in S17), the processing after step S11 is continued and the processing is completed (S17). YES), the process is terminated.

Embodiment 2
In the first embodiment described above, the color image input device 1, the color image processing device (image processing device) 2, the color image output device 3, and the like have been provided. However, the image forming system in which the image processing device is realized by a computer. The present invention can also be applied to.

  FIG. 18 is a block diagram illustrating a configuration of the image forming system according to the second embodiment. The image forming system includes a computer (image processing apparatus) 50 and a printer (image output apparatus, image forming means) 55. The printer 55 may be a digital multifunction machine having a copy function and a facsimile function in addition to the printer function. The printer 55 performs electrophotographic or ink jet image formation.

  For example, image data is input to the computer 50 from an image scanner such as a flatbed scanner or a film scanner or a digital camera, and is stored in a storage device such as a hard disk (not shown). The computer 50 can process and edit the input image data by executing various application programs. The computer 50 includes a region separation processing unit 51 that determines a region of each pixel of output image data to be output to the printer 55, a gradation reproduction processing unit 52 that performs halftone generation processing, and conversion of the output image data into a printer language. It operates as the printer language translation unit 53 to be performed. The region separation processing unit 51 performs the same region separation processing as the region separation processing unit 23 of the first embodiment, and the gradation reproduction processing unit 52 is the same multi-value as the gradation reproduction processing unit 28 of the first embodiment. A halftone generation process using an error diffusion method is performed.

  Although not shown, the computer 50 also performs processing similar to that of the color correction unit 24, the black generation and under color removal unit 25, the spatial filter processing unit 26, and the like of the first embodiment. The data converted into the printer language by the printer language translation unit 53 is output to the printer 55 via the communication port 54 (Centronics port, LAN (Local Area Network) port, etc.).

  FIG. 19 is a block diagram showing the configuration of the computer 50. The computer 50 includes a CPU 61, a RAM 62, a hard disk drive (hereinafter abbreviated as a hard disk) 63, an external storage unit 64 such as a flexible disk drive or a CD (Compact Disk) -ROM drive, an input unit 65 such as a keyboard or a mouse, a CRT (Cathode Ray Tube) includes a display unit 66 such as a display or a liquid crystal display, a communication port 54 for controlling communication with the printer 55, and the like. The communication port 54 includes a network card or a modem, and can be connected to a communication network such as a LAN, the Internet, or a telephone line.

  The CPU 61 controls the above-described units and the communication port 54. Further, the CPU 61 stores the program or data received from the input unit 65 or the communication port 54 or the program or data read from the hard disk 63 or the external storage unit 64 in the RAM 62, and executes the program stored in the RAM 62 or the data Various processes such as computation are performed, and various process results or temporary data used for various processes are stored in the RAM 62. Data such as calculation results stored in the RAM 62 is stored in the hard disk 63 by the CPU 61 or output from the display unit 66 or the communication port 54.

  The CPU 61 operates as the above-described region separation processing unit 51, gradation reproduction processing unit 52, printer language translation unit 53, and the like. The input image data is input to the computer 50 from a scanner or a digital camera, for example, and stored in the hard disk 63.

  The CPU 61 also adds the adder 281, the quantization processing unit 282, the quantization error calculation unit 283, the diffusion error calculation unit 284, the random number generator 287, and the surrounding pixel determination unit 289 of the gradation reproduction processing unit 28 according to the first embodiment. Works as. The RAM 62 or the hard disk 63 operates as a quantization threshold storage unit 288, an accumulation error storage unit 285, and a diffusion coefficient storage unit 286. For example, an error diffusion matrix, a quantization table, a peripheral pixel determination lookup table, and the like are stored in the hard disk (storage unit) 63.

  A program code (execution format program, intermediate code program, source program) of a computer program recorded on a recording medium 69 such as a CD-ROM is read by the external storage unit 64, stored in the hard disk 63 or RAM 62, and executed by the CPU 61. Thus, the computer 50 can be operated as the above-described units or units. The processing realized by the program code of the computer program includes, for example, accumulation error addition, peripheral pixel determination, determination of quantization threshold set (quantization table), calculation of quantization value, calculation of quantization error, area identification Each process such as calculation of diffusion error. It is also possible to receive a program code from another device through the communication port 54 connected to a LAN or the like and store it in the hard disk 63 or the RAM 62. Note that the program code of the computer program for realizing the multilevel error diffusion processing according to the present invention may be included in the printer driver or may be included in the application software for image processing.

  The program code of a computer program that causes a computer to execute halftone generation using the multi-value error diffusion method according to the present invention is stored in the recording medium 69. The recording medium 69 is processed by a microcomputer. Or a program medium such as a ROM (not shown), or a program medium provided with a program reading device such as the external storage unit 64 and readable by inserting a recording medium 69 therein. Good. In any case, the stored program code may be configured to be accessed and executed by the microprocessor, or the program is read out, and the read program is a program storage area (not shown) of the microcomputer. The program code may be downloaded and executed by the program code. In this case, it is assumed that the download program is stored in the main device in advance.

  The program medium is a recording medium configured to be separable from the main body, and includes a tape system such as a magnetic tape and a cassette tape, a magnetic disk such as a flexible disk and a hard disk, and a CD-ROM / MO (Magneto Optical) / MD (Mini disk) / DVD (Digital Versatile Disk) and other optical disk systems, IC (Integrated Circuit) cards (including memory cards) / optical card systems, mask ROM, EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), a medium carrying a fixed program including a semiconductor memory such as a flash ROM may be used.

  Further, in the case of a system configuration that can be connected to a communication network including the Internet, it may be a medium that dynamically carries the program code so as to download the program code from the communication network. When downloading the program code from the communication network in this way, the download program may be stored in the main device in advance or installed from another recording medium. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

1 is a block diagram illustrating a configuration of an image forming apparatus including an image processing apparatus according to the present invention. It is explanatory drawing which shows the example of the filter coefficient used for a weak emphasis process. It is a block diagram which shows the structure of a gradation reproduction process part. It is explanatory drawing which shows the structure of a quantization table. It is explanatory drawing which shows an example of an error diffusion matrix. It is explanatory drawing which shows the example of a surrounding pixel block. It is explanatory drawing which shows the structure of the quantization table corresponding to the determination signal 0. FIG. It is explanatory drawing which shows the structure of the quantization table corresponding to the determination signal 1. FIG. It is explanatory drawing which shows the structure of the quantization table corresponding to the determination signal 2. FIG. It is explanatory drawing which shows the structure of the quantization table corresponding to the determination signal 3. FIG. It is explanatory drawing which shows the structure of the quantization table corresponding to the determination signal 4. FIG. It is explanatory drawing which shows the structure of the quantization table in case a color component is black. It is explanatory drawing which shows the structure of a surrounding pixel determination lookup table. It is explanatory drawing which shows the other example of an error diffusion matrix. It is explanatory drawing which shows the other example of a surrounding pixel block. It is explanatory drawing which shows the relationship between a quantization value and a stability coefficient. It is a flowchart which shows the procedure of the multi-value error diffusion process of a color image processing apparatus. 3 is a block diagram illustrating a configuration of an image forming system according to a second embodiment. FIG. It is a block diagram which shows the structure of a computer.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Color image input device 2 Color image processing device 3 Color image output device 23, 51 Area separation processing unit 28, 52 Tone reproduction processing unit 50 Computer 54 Communication port 61 CPU
62 RAM
63 hard disk 64 external storage unit 281 adder 282 quantization processing unit 283 quantization error calculation unit 284 diffusion error calculation unit 285 accumulation error storage unit 286 diffusion coefficient storage unit 287 random number generator 288 quantization threshold storage unit 289 peripheral pixel determination unit

Claims (16)

In an image processing method for scanning each pixel of an image composed of a plurality of pixels in a predetermined direction and generating a halftone image by multi-quantizing the pixel value of each pixel based on a quantization threshold,
A plurality of quantization tables in which a plurality of quantization threshold values and quantization values are associated are stored in advance,
Stores the quantized value of each pixel subjected to multi-value quantization,
Extract neighboring pixel blocks around the pixel of interest, consisting of multiple multi-valued quantized pixels,
Based on the quantized value of each pixel of the extracted peripheral pixel block, specify the gradation degree around the pixel of interest,
In accordance with the specified gradation level, a quantization table for multilevel quantization of the pixel of interest is determined,
An image processing method, wherein the pixel value of the pixel of interest is subjected to multi-value quantization using the determined quantization table. In an image processing apparatus that scans each pixel of an image composed of a plurality of pixels in a predetermined direction and multi-quantizes the pixel value of each pixel based on a quantization threshold to generate a halftone image.
Means for storing a plurality of quantization tables in which a plurality of quantization thresholds and quantization values are associated;
Means for storing a quantized value of each pixel subjected to multi-value quantization;
Extraction means for extracting a peripheral pixel block around the target pixel composed of a plurality of multi-value quantized pixels;
Means for specifying the degree of gradation around the target pixel based on the quantized value of each pixel of the peripheral pixel block extracted by the extracting means;
Determining means for determining a quantization table for multi-value quantization of the pixel of interest according to the gradation level specified by the means;
An image processing apparatus comprising: quantization means for performing multi-value quantization on a pixel value of the target pixel using the quantization table determined by the determination means. Based on the pixel value of each pixel of the image, comprising at least a region determination means for determining whether the region is a character region, a halftone dot region, or a photo region;
The determining means includes
The quantization table is determined according to the gradation level around the pixel of interest specified based on the quantization value of each pixel of the peripheral pixel block and the determination result determined by the region determination unit. The image processing apparatus according to claim 2, wherein the image processing apparatus is an image processing apparatus. The determining means includes
The image processing apparatus according to claim 2 or 3, wherein the quantization table is determined based on a color component of the image. Means for weighting each pixel according to the distance from the pixel of interest of each pixel of the peripheral pixel block;
Means for providing a stability coefficient indicating the degree of stability of the density of each pixel according to the quantized value of each pixel of the peripheral pixel block, and
5. The image processing according to claim 2, wherein the determination unit is configured to determine a quantization table based on the assigned weighting and stability coefficient. apparatus. Means for storing an identifier for identifying each quantization table in association with a combination of quantization values of each pixel of the peripheral pixel block;
Means for specifying an identifier based on a quantized value of each pixel of the peripheral pixel block extracted by the extracting means,
The determining means includes
6. The image processing apparatus according to claim 2, wherein a quantization table identified by the identifier specified by the means is determined.   7. An erasing unit for erasing a quantized value of a pixel first subjected to multi-level quantization in a neighboring pixel block each time a pixel of interest is scanned is provided. The image processing apparatus described in one.   8. The image processing apparatus according to claim 2, wherein an integer value from 0 to N-1 is associated with each of N different quantized values.   The image according to any one of claims 2 to 7, wherein an integer value from 0 to M-1 (M <N) is associated with each of N different quantized values. Processing equipment.   The integer value from 0 to M-1 (M ≦ 2 to the power of <N) is associated with each of the N different quantized values. An image processing apparatus according to 1.   11. The image processing apparatus according to claim 9, further comprising means for setting an integer value to be associated according to a color component of the image.   12. The image processing apparatus according to claim 2, further comprising a unit that sets a quantization threshold according to a color component of the image.   A common quantization threshold among a plurality of quantization tables is stored in one quantization table having the quantization threshold, and quantization thresholds other than the common quantization threshold are stored in each quantization table. The image processing apparatus according to claim 2, wherein the image processing apparatus is configured as described above.   An image processing apparatus according to any one of claims 2 to 13, and image forming means for forming an output image on a sheet based on image data generated by the image processing apparatus. Image forming apparatus. A computer program for causing a computer to scan each pixel of an image composed of a plurality of pixels in a predetermined direction and to generate a halftone image by multi-quantizing the pixel value of each pixel based on a quantization threshold In
Means for causing a computer to extract a peripheral pixel block around a target pixel composed of a plurality of multi-valued quantized pixels;
Means for causing a computer to specify the degree of gradation around the pixel of interest based on the quantized value of each pixel of the extracted peripheral pixel block;
Means for causing a computer to determine a quantization table for multi-value quantization of the pixel of interest according to the specified gradation level;
A computer program that causes a computer to function as means for performing multi-value quantization on a pixel value of the pixel of interest using a determined quantization table.   A computer-readable recording medium on which the computer program according to claim 15 is recorded.

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