JP2006287474A - Image processor and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processor that enhances a degree of concentration of a dither screen without causing a time lag for error application, and prevents discontinuity of a boarder part by a small scale circuit and suppresses the occurrence of a stripe pattern while establishing the compatibility between the resolution and the gradation. <P>SOLUTION: The image processor includes: an edge level detection section 11 for calculating an edge level representing a degree of a target pixel as an edge; a luminance level detection section 12 for calculating a luminance level representing whether or not the target pixel is close to a medium density; an adaptivity calculation section 13 for calculating to which of dither processing and error diffusion processing the target pixel is more adaptive on the basis of the edge level and the luminance level; a dither threshold value generating section 151 for changing a threshold value matrix depending on the adaptivity; a quantization section 152 for applying quantization to the target pixel; a generated error calculation section 154 for calculating an error between values before and after the dither processing; an accumulated error calculation section 154 for accumulating the error of the error diffusion source pixel for the target pixel; and an accumulated error addition section 155 for adding the accumulated error to the target pixel. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and an image processing program for performing image processing for pseudo gradation on image data.

  2. Description of the Related Art Conventionally, in many image forming apparatuses, image processing such as error diffusion processing or dither processing is performed on image data in order to express more gradations with limited output gradations. . Each of the error diffusion processing and dither processing is inappropriate depending on the characteristics of the image to be processed, that is, whether it is a character region or a photographic region. Therefore, the error diffusion processing and dither processing are switched depending on the image region. A method of performing processing has also been proposed.

  For example, a pixel is quantized using a threshold matrix composed of periodically varying thresholds, and the amount of error is set according to the edge amount detected in advance for the pixel (the amount representing the degree of proximity of the pixel to the edge). The image processing device to be controlled (first prior art) and the degree of suitability, which is the degree to which the image data is suitable for the dither method or the error diffusion method, are obtained based on the luminance value of the image, and are varied or fixed based on the suitability. There is an image processing apparatus (second prior art) that determines the threshold value and controls the error diffusion matrix size by multiplying each coefficient of the error diffusion matrix by a coefficient corresponding to the degree of fitness.

In addition, in Patent Document 1 below, for the purpose of compensating for the weak point of the error diffusion method, a threshold value change is obtained by multiplying a threshold value in a threshold matrix composed of periodically oscillating threshold values by a coefficient corresponding to the detected edge amount. An image processing apparatus is described in which the dither screen angle is variable by controlling the vibration width of the dither screen and relatively shifting the threshold matrixes by a half-phase shift.
JP 2001-292319 A

  However, in the case of the image processing apparatus of the first prior art, since the amount of error used for error diffusion is controlled (dynamically changed), not the edge amount of the pixel of interest but the pixel already processed. Since the error amount applied to the target pixel is determined based on the edge amount, a time lag occurs in applying the error. In the case of the second prior art, the circuit scale becomes large because all the coefficients of the error diffusion matrix are multiplied by the fitness. Further, in the case of the image processing apparatus described in Patent Document 1, since the control for the error is not performed, the concentration degree of the dither screen is lowered.

  The present invention has been made in view of the above problems, and does not cause a time lag in applying errors, increases the concentration of dither screens, and switches between error diffusion processing and dither processing without increasing the circuit size. To provide an image processing apparatus and an image processing program that do not cause a discontinuity in the boundary portion, achieve both the resolution of the character area and the gradation of the photographic area, and suppress the occurrence of a stripe pattern peculiar to error diffusion With the goal.

  The image processing apparatus according to claim 1, an edge level calculation unit that calculates an edge level representing a degree of possibility that a target pixel that is a processing target pixel in image data to be subjected to image processing is a pixel near an edge; A luminance level calculation means for calculating a luminance level indicating whether the pixel value of the target pixel is high density, low density, or intermediate density; and the edge level of the target pixel calculated by the edge level calculation means; By performing a predetermined calculation using the luminance level of the pixel of interest calculated by the luminance level calculation means, a ratio indicating whether the pixel of interest is more suitable for dither processing or error diffusion processing is expressed. In a case where the fitness level calculating means for calculating the fitness level and the fitness level calculated by the fitness level calculating means are values indicating a perfect match with the dither processing, When the threshold value for the target pixel is set to a value of an element corresponding to the target pixel in a predetermined threshold matrix, and the matching level is a value indicating that the matching level is completely compatible with error diffusion processing, When a threshold value for the target pixel is set to a predetermined value, and the fitness is a value that does not completely match the dithering process or the error diffusion process, the threshold value for the target pixel is set to the threshold value matrix. A threshold value generation unit that is set based on a ratio indicated by the fitness between the value of the element corresponding to the target pixel and the predetermined value, and for the target pixel to which an error is added, An error is a difference between a quantization unit that performs quantization using the threshold generated by the threshold generation unit, a value of a pixel of interest after quantization by the quantization unit, and a value of a pixel of interest before quantization calculate The difference calculation means and the error calculated for one or more predetermined pixels for adding an error to the pixel of interest are added together with a predetermined weight for the one or more pixels. An error for adding a cumulative error calculation means for calculating a cumulative error, a result obtained by multiplying the cumulative error calculated by the cumulative error calculation means, and the fitness calculated for the pixel of interest to the value of the pixel of interest The value calculated by the error adding means is a pixel value of a target pixel to which an error is added, which is quantized by the quantizing means.

  According to this configuration, the edge level and the luminance level for the target pixel are obtained by the edge level calculation unit and the luminance level calculation unit, respectively, and the fitness is calculated according to the obtained edge level and luminance level. The threshold matrix value used for dither processing is generated by the threshold generation unit in accordance with the target pixel using the degree of matching, and the dither processing is performed on the target pixel by the quantization unit using the threshold matrix. Thus, pixel data after image processing is generated. On the other hand, when the error between the original value of the target pixel and the image data after the dither processing is obtained by the error calculation unit and another pixel becomes the target pixel, the new target pixel obtained by the error calculation unit is obtained. An error relating to a predetermined pixel other than the pixel that has become is accumulated by the accumulated error calculating means, and this accumulated error is added to a new pixel of interest by the error adding means, and then used for quantization by the quantizing means.

  An image processing apparatus according to a second aspect is the image processing apparatus according to the first aspect, wherein the edge level calculating means calculates an edge level using the following equation (A).

(Max−min) ÷ maximum value of pixel value definition range (A)
However, max is the maximum value of the pixel values of a plurality of pixel positions predetermined with respect to the position of the target pixel, and min is a plurality of pixel positions predetermined with respect to the position of the target pixel. This is the minimum pixel value of the pixel.

  An image processing apparatus according to a third aspect is the image processing apparatus according to the first or second aspect, wherein the luminance level calculation means calculates a luminance level using the following equation (B).

  | Pixel value of target pixel-median value of pixel value definition range | ÷ median value of pixel value definition range (B)

  The image processing device according to claim 4 is the image processing device according to claim 2 or 3, wherein the fitness level calculation unit calculates the edge level calculated by the edge level calculation unit and the luminance level calculation. The higher one of the luminance levels calculated by the means is calculated as the fitness.

  The image processing device according to claim 5 is the image processing device according to claim 2 or 3, wherein the fitness calculation unit calculates the edge level calculated by the edge level calculation unit and the luminance level calculation. A value obtained by multiplying the luminance level calculated by the means is calculated as the fitness.

  An image processing program according to claim 6 is an edge level calculation unit that calculates an edge level representing a degree of possibility that a target pixel that is a processing target pixel in image data to be subjected to image processing is a pixel near an edge; A luminance level calculation means for calculating a luminance level indicating whether the pixel value of the target pixel is high density, low density, or intermediate density; and the edge level of the target pixel calculated by the edge level calculation means; By performing a predetermined calculation using the luminance level of the pixel of interest calculated by the luminance level calculation means, a ratio indicating whether the pixel of interest is more suitable for dither processing or error diffusion processing is expressed. A fitness level calculation means for calculating the fitness level, and the fitness level calculated by the fitness level calculation means is a value indicating that it is perfectly compatible with dither processing. Is set to the value of an element corresponding to the pixel of interest in a predetermined threshold matrix for the threshold of the pixel of interest, and the degree of adaptation is a value indicating that the error diffusion process is completely adapted Sets the threshold for the pixel of interest to a predetermined value, and if the degree of fitness is a value that does not perfectly match either the dither processing or the error diffusion processing, the threshold for the pixel of interest is Threshold generation means that is set based on the ratio indicated by the fitness between the value of the element corresponding to the pixel of interest in the threshold matrix and the predetermined value, and for the pixel of interest to which an error has been added The difference between the quantization means for performing quantization using the threshold generated by the threshold generation means, the value of the target pixel after quantization by the quantization means, and the value of the target pixel before quantization is calculated. Calculate as error And an error calculating means for adding the error calculated for one or more predetermined pixels for adding an error to the pixel of interest with a predetermined weight for the one or more pixels. The cumulative error calculation means for calculating the cumulative error, the result obtained by multiplying the cumulative error calculated by the cumulative error calculation means and the fitness calculated for the target pixel is added to the value of the target pixel. An error adding means, and the value calculated by the error adding means causes the computer to function so as to be a pixel value of a target pixel to which an error is added, which is quantized by the quantizing means. .

  According to the invention described in any one of claims 1 to 6, the error diffusion time lag is generated in order to control the error according to the fitness of the target pixel by multiplying the cumulative error by the fitness. By controlling the accumulated error amount, the concentration of the dither screen is increased, and the total value of the accumulated error is multiplied by the fitness level, thereby suppressing the circuit scale and switching between the error diffusion process and the dither process. It is possible to suppress the occurrence of a stripe pattern peculiar to error diffusion without causing discontinuity in the boundary portion, achieving both the resolution of the character area and the gradation of the photographic area.

  Embodiments according to the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing a functional configuration of an image processing apparatus provided in an image forming apparatus according to an embodiment of the present invention. The image processing apparatus 1 performs pseudo gradation processing on image data in a pseudo manner to express more gradations with limited output gradations. For example, the image processing apparatus 1 outputs an image on a recording paper or a display. Provided in an output device (including an image forming apparatus). The image processing apparatus 1 is implemented as a hardware circuit, for example.

  The multifunction device 2 is a copier having a printer function and the like, and includes an image data acquisition unit 21, an image processing device 1, and a printing unit 22 as functional configurations. The image data acquisition unit 21 reads an image from a document placed on the document placement unit of the multifunction device 2 or receives image data from a PC or the like connected to the multifunction device 2 via a network or the like. Image data is acquired. The image data acquisition unit 21 inputs data for each pixel to the image processing apparatus 1 in a predetermined order (for example, scanning order). The printing unit 22 acquires image data for which image processing has been completed by the image processing apparatus 1 pixel by pixel, and prints this image on, for example, recording paper.

  The image processing apparatus 1 includes an edge level detection unit 11, a luminance level detection unit 12, a gradation processing suitability calculation unit 13, a signal delay unit 14, and an image processing unit 15. The image processing unit 15 includes a dither threshold value generation unit 151, a quantization unit 152, a generated error storage unit 153, and a cumulative error calculation unit 154. The edge level detection unit 11 and the signal delay unit 14 are sequentially input pixel values of pixels of image data to be processed one pixel at a time in a predetermined order (for example, scanning order). The image processing apparatus 1 performs processing using the input pixel as a target pixel. In the present embodiment, the pixel value is 256 gradations from 0 to 255.

  The edge level detection unit 11 calculates an edge level representing the degree of possibility that the target pixel is a pixel near the edge. The edge level detection unit 11 represents the edge level with a value between 0 and 1, and is close to 1 when the pixel of interest is likely to be near the edge, and is 0 when the possibility is low. The edge level is calculated so as to be close. The edge level detection unit 11 calculates the edge level of the target pixel based on, for example, the following expression (A) based on a pixel at a predetermined pixel position with respect to the pixel position of the target pixel (for example, 3 × 3 pixels centered on the target pixel). To do.

(Max value of 3 × 3 pixel region−3 × min value of 3 pixel region) ÷ 255 (A)
Here, the maximum value of the 3 × 3 pixel region is the largest among the pixel values of the 3 × 3 pixels, and the min value of the 3 × 3 pixel region is the pixel value of the 3 × 3 pixels. And 255 is the maximum pixel value in the definition of the pixel value.

  The luminance level detection unit 12 calculates a luminance level that indicates the degree of whether the density of the pixel of interest is near the intermediate density or near the high density and the low density. The luminance level detection unit 12 represents the luminance level with a value between 0 and 1, and is close to 1 when the pixel value of the target pixel is high density and low density, and 0 when the pixel value is intermediate density. The luminance level is calculated so as to be a value close to. The luminance level detection unit 12 calculates the luminance level of the target pixel based on the pixel value, for example, using the following formula (B).

| Pixel value of the pixel of interest −127 | ÷ 128 (B)
Here, 127 is a median value in the definition of the pixel value. In the present embodiment, any of the pixel values (127 and 128) adjacent to the actual median value (127.5) may be used. 128 is the larger pixel value adjacent to the median.

  The gradation processing suitability calculator 13 calculates the degree (fitness) of whether the target pixel is suitable for dither processing or error diffusion processing based on the edge level and the luminance level. The gradation processing suitability calculating unit 13 represents the suitability with a value between 0 and 1, and is close to 1 when suitable for error diffusion processing, and close to 0 when suitable for dither processing. The goodness of fit is calculated. Since the edge portion pixels and the high density and low density pixels are suitable for error diffusion processing, and the pixel portions other than the edges and intermediate density pixels are suitable for dither processing, the gradation processing suitability calculation unit 13 The degree of fitness is calculated to be close to 1 for pixels and high density and low density pixels, and the degree of fitness is close to 0 for pixels other than the edge and pixels of intermediate density. For this purpose, for example, (i) the larger value of the edge level and the luminance level is used as the fitness level, and (b) the value obtained by multiplying the edge level and the luminance level is used as the fitness level. In addition, the above (A) or (B) is performed on the value obtained by converting the edge level or / and the luminance level by using an LUT (Look Up Table) or a calculator, or the above (A) or (B The value obtained by performing conversion using a LUT (lookup table) or an arithmetic unit may be used as the fitness.

  The dither threshold value generation unit 151 generates a threshold value to be applied to the target pixel from a threshold matrix stored in advance. The threshold matrix holds thresholds applied to each pixel in the dither processing as a matrix based on the positional relationship of the pixels, and has different thresholds as matrix elements. The pixel of interest is binarized using a predetermined element (threshold value) (threshold value matrix) based on the pixel position by the dither processing. The dither threshold value generation unit 151 stores a predetermined threshold value matrix (see FIG. 2 (1)), and an element (for example, a thick frame in FIG. 2 (1)) corresponding to the target pixel of the threshold value matrix. The median value (127) of the pixel value (gradation) is subtracted from the value of the enclosed element (see FIG. 2 (2)), and the value obtained by subtracting the fitness from 1 is multiplied by this subtraction result (FIG. 2 (3) Further, the median value (127) is added to the multiplication result (see FIG. 2 (4)) to calculate a threshold value for the target pixel. FIG. 2 is a diagram showing an example of the flow of image processing for one pixel (target pixel) by the image processing apparatus 1 for the target pixel when the fitness is 0.75. The matrixes (1) to (4) in FIG. 2 show the flow of threshold generation by the dither threshold generation unit 151. When the fitness level is close to 1, the threshold value approaches the median value, and when the fitness level is close to 0, the threshold value approaches the value of the corresponding element of the predetermined threshold value matrix.

  The quantization unit 152 quantizes (binarizes) the target pixel using the threshold value. The quantization unit 152 adds a pixel value of a pixel of interest (see FIG. 2 (6)) to which a pixel value of the pixel of interest is added to a value (see FIG. 2 (5)) obtained by multiplying a cumulative error (to be described later) by a fitness. The value is received from the cumulative error adding unit 155, and the threshold value for the target pixel (see FIG. 2 (4)) is received from the dither threshold value generating unit 151, and the pixel value of the target pixel is binarized based on the threshold value. (For example, 0 or 255) (see FIG. 2 (7)) and output from the image processing apparatus 1.

  The generated error storage unit 153 calculates a difference between the data before quantization and the data after quantization as an error, and stores it as an error of the target pixel. The generated error storage unit 153 is a difference between the quantized pixel value generated by the quantization unit 152 (see FIG. 2 (7)) and the pixel value of the target pixel to which an error is added (see FIG. 2 (6)). Is stored as an error (see FIG. 2 (8)).

  The accumulated error calculation unit 154 calculates an error value to be added to the pixel value of the target pixel, using the already determined error of each pixel. The accumulated error calculation unit 154 determines an error diffusion matrix based on an error diffusion matrix stored in advance in the accumulated error calculation unit 154, which is determined in advance with respect to the position of the contribution source of the error to be added to the target pixel and its contribution rate. The accumulated error is calculated by adding the previously obtained error value for the pixel at the pixel position, which is an element of the element, based on the contribution rate, and the value obtained by multiplying the accumulated error by the fitness of the target pixel is accumulated. The error is added to the error adder 155.

  The cumulative error addition unit 155 adds the pixel value of the target pixel received from the signal delay unit 14 to the cumulative error multiplied by the fitness received from the cumulative error calculation unit 154, and adds the pixel value of the target pixel to which the error has been added. Generate pixel values.

  The signal delay unit 14 is configured so that the threshold value input to the quantization unit 152 corresponds to the target pixel input to the quantization unit 152 (with an error) at the same time. The pixel data (pixel value) input to is input to the accumulated error adding unit 155 after being delayed from the timing of input to the edge level detecting unit 11 and the luminance level detecting unit 12.

  As described above, in the present embodiment, the edge level and the luminance level are obtained for the target pixel, the fitness is calculated according to the obtained edge level and the luminance level, and the dither processing is performed using the fitness. In addition to changing the value of the threshold matrix to be used and changing the value of the accumulated error used for error diffusion processing, the dither processing is more strongly controlled or the error diffusion processing is more strongly controlled. There is no time lag, the concentration of the dither screen is increased, the circuit is not enlarged, the boundary between the error diffusion process and the dither process is not generated when switching between the error diffusion process and the dither process, the resolution of the character area and the level of the photo area It is possible to balance the tonality and to suppress the occurrence of stripe patterns peculiar to error diffusion.

  In addition, this invention is not limited to the thing of the said embodiment, The aspect described below can be employ | adopted. In the above embodiment, the image data of 256 gradations is converted to 2 gradations to express the original gradation in a pseudo manner, but the present invention is not limited to the above number of gradations. Any original that reproduces the original gradation with fewer gradations than the original gradation may be used.

  In the above embodiment, the example in which the image processing apparatus 1 is implemented as a hardware circuit has been described. However, the image processing apparatus 1 may be implemented as a computer program.

FIG. 2 is a block diagram illustrating a functional configuration of a multifunction peripheral according to an embodiment of the present invention. It is a figure which shows the process example in the image processing apparatus in one Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 11 Edge level detection part (edge level calculation means)
12 Luminance level detection unit (luminance level calculation means)
13 Gradation processing suitability calculation unit (fitness calculation means)
151 Dither threshold value generator (threshold value generator)
152 Quantization unit (quantization means)
153 Generation error storage unit (error calculation means)
154 Cumulative error calculation unit (cumulative error calculation means)
155 Cumulative error adding unit (error adding means)

Claims (6)

Edge level calculation means for calculating an edge level representing the degree of possibility that the target pixel in the image data for image processing is a pixel near the edge;
A luminance level calculation means for calculating a luminance level indicating whether the pixel value of the pixel of interest is high density or low density, or intermediate density;
The target pixel is dithered by performing a predetermined calculation using the edge level of the target pixel calculated by the edge level calculation unit and the luminance level of the target pixel calculated by the luminance level calculation unit. And a fitness level calculation means for calculating a fitness level that represents a ratio that is more suitable for the error diffusion process,
When the fitness calculated by the fitness calculation means is a value indicating that it is completely compatible with dither processing, the threshold for the pixel of interest corresponds to the pixel of interest in a predetermined threshold matrix. If the value of the matching is a value indicating that the degree of matching is completely compatible with the error diffusion process, a threshold value for the target pixel is set to a predetermined value, and the degree of matching is dithered. When the value is not completely compatible with the processing and the error diffusion processing, the threshold value for the target pixel is set to the value of the element corresponding to the target pixel of the threshold value matrix and the predetermined value. Threshold generation means for setting based on the ratio indicated by the fitness between
Quantization means for performing quantization on the target pixel to which an error has been added, using a threshold value generated by the threshold value generation means;
An error calculating means for calculating a difference between the value of the target pixel after quantization by the quantization means and the value of the target pixel before quantization as an error;
A cumulative error is calculated by adding the error calculated for one or more predetermined pixels for adding an error to the pixel of interest and adding a predetermined weight for the one or more pixels. A cumulative error calculating means;
Error addition means for adding the result of multiplying the cumulative error calculated by the cumulative error calculation means and the fitness calculated for the pixel of interest to the value of the pixel of interest;
The value calculated by the error adding unit is an image processing apparatus that is a pixel value of a target pixel to which an error is added, which is quantized by the quantization unit. The image processing apparatus according to claim 1, wherein the edge level calculation unit calculates an edge level using the following equation (A).
(Max−min) ÷ maximum value of pixel value definition range (A)
However, max is the maximum value of the pixel values of a plurality of pixel positions predetermined with respect to the position of the target pixel, and min is a plurality of pixel positions predetermined with respect to the position of the target pixel. This is the minimum pixel value of the pixel. The image processing apparatus according to claim 1, wherein the luminance level calculation unit calculates a luminance level using the following equation (B).
| Pixel value of target pixel-median value of pixel value definition range | ÷ median value of pixel value definition range (B)   The compatibility level calculating unit calculates the higher one of the edge level calculated by the edge level calculation unit and the luminance level calculated by the luminance level calculation unit as the fitness level. The image processing apparatus according to 3.   4. The fitness level calculation unit calculates a value obtained by multiplying the edge level calculated by the edge level calculation unit and the luminance level calculated by the luminance level calculation unit as the fitness level. An image processing apparatus according to 1. Edge level calculation means for calculating an edge level representing the degree of possibility that the target pixel in the image data for image processing is a pixel near the edge;
A luminance level calculation means for calculating a luminance level indicating whether the pixel value of the pixel of interest is high density or low density, or intermediate density;
The target pixel is dithered by performing a predetermined calculation using the edge level of the target pixel calculated by the edge level calculation unit and the luminance level of the target pixel calculated by the luminance level calculation unit. And a fitness level calculation means for calculating a fitness level that represents a ratio that is more suitable for the error diffusion process,
When the fitness calculated by the fitness calculation means is a value indicating that it is completely compatible with dither processing, the threshold for the pixel of interest corresponds to the pixel of interest in a predetermined threshold matrix. If the value of the matching is a value indicating that the degree of matching is completely compatible with the error diffusion process, a threshold value for the target pixel is set to a predetermined value, and the degree of matching is dithered. When the value is not completely compatible with the processing and the error diffusion processing, the threshold value for the target pixel is set to the value of the element corresponding to the target pixel of the threshold value matrix and the predetermined value. Threshold generation means for setting based on the ratio indicated by the fitness between
Quantization means for performing quantization on the target pixel to which an error has been added, using a threshold value generated by the threshold value generation means;
An error calculating means for calculating a difference between the value of the target pixel after quantization by the quantization means and the value of the target pixel before quantization as an error;
A cumulative error is calculated by adding the error calculated for one or more predetermined pixels for adding an error to the pixel of interest and adding a predetermined weight for the one or more pixels. A cumulative error calculating means;
Error addition means for adding the result of multiplying the cumulative error calculated by the cumulative error calculation means and the fitness calculated for the pixel of interest to the value of the pixel of interest;
An image processing program for causing a computer to function so that a value calculated by the error adding unit is a pixel value of a target pixel to which an error is added, which is quantized by the quantization unit.

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