JP6226717B2 - Image processing apparatus and image processing method - Google Patents

Description

  The present invention relates to an image processing apparatus that performs halftone processing on multivalued image data.

  Digital image processing apparatuses that output digitized image data from a digital printer such as a laser beam printer to reproduce an image are widely used. In this digital image processing apparatus, when reproducing halftones, a method is generally adopted in which gradation reproduction is performed by halftone processing using an AM (Amplitude Modulation: Reproduction of gradation by dot area) screen or the like. ing.

  Such a method is good in a portion with a small high-frequency component such as a flat portion. However, in images and characters / thin lines that are composed of periodic patterns such as halftone dots, the period of the AM screen and the high-frequency components included in the input image (especially the periodic pattern close to the period of the AM screen) Interfere with. As a result, there is a problem that a periodic striped pattern called moire occurs. In addition, when the AM screen is used, the spatial resolution that can be expressed is lowered, so that the edge portion is expressed by dots arranged in a step shape called jaggy.

  On the other hand, in Patent Document 1, a screen process is performed using a plurality of different screens for an image, a composition ratio of the screen process is determined based on an image feature analysis result, and a composite-processed image is output. Is disclosed. Further, Patent Document 2 discloses a method of performing different screen processing between an edge portion and a non-edge portion by an edge determination unit of an input image.

JP 2010-74627 A JP 2010-245591 A

  In the methods disclosed in Patent Literature 1 and Patent Literature 2, it is necessary to include processing means for performing a plurality of different screen processes and analysis means for performing image feature analysis, and there is a problem that the circuit scale increases. In addition, the mixed pixels and the pixels of the switching unit become conspicuous, and there is a possibility that the image quality is visually recognized as degraded.

The image processing apparatus according to the present invention, Oite the input image data, among the pixels that are not white pixels, and detecting means for detecting a pixel adjacent to the white pixel as a boundary pixel, by dither method on the input image data It performs screen processing, and screen processing means for outputting the image data after the screen processing, and gamma conversion means for the input image data to gamma conversion and outputs the gamma-converted image data, the detected boundary pixels in the detection unit based on, have a synthesizing means for synthesizing said screen processed image data and the gamma converted image data, said detecting means, for target pixel in the input image data, adjacent to the pixel of interest and the pixel of interest White pixels are detected in the pixel group, and the target pixel is the boundary pixel based on the result of detecting the white pixels. And judging whether.

  According to the present invention, it is possible to reduce jaggy and moire without increasing the circuit scale and obtain a high-quality halftone processing result without image quality deterioration.

FIG. 3 is a block diagram for explaining the configuration of the first embodiment. FIG. 3 is a diagram for explaining a dither matrix according to the first embodiment. FIG. 6 is a diagram for explaining gamma conversion according to the first embodiment. FIG. 4 is a diagram for explaining a white pixel detection filter according to the first exemplary embodiment and a specific example of image processing. FIG. 6 is a diagram illustrating a specific example of image processing according to the first embodiment. FIG. 6 is a diagram illustrating a specific example of image processing according to the first embodiment. FIG. 6 is a diagram illustrating a specific example of image processing according to the first embodiment. 6 is a flowchart illustrating an example of a flow of image processing according to the first exemplary embodiment. FIG. 6 is a block diagram for explaining a configuration of a second embodiment. FIG. 10 is a diagram illustrating a specific example of image processing according to the second embodiment. FIG. 10 is a diagram illustrating a specific example of image processing according to the second embodiment. FIG. 10 is a block diagram for explaining a configuration of a third embodiment. FIG. 10 is a block diagram for explaining a configuration of a fourth embodiment. FIG. 10 is a diagram illustrating a specific example of image processing according to the fourth embodiment. FIG. 10 is a diagram illustrating a specific example of image processing according to the fourth embodiment. FIG. 10 is a diagram for explaining gamma conversion according to a fourth embodiment. It is a figure for demonstrating the example of the edge detection of Example 4. FIG. FIG. 10 is a block diagram for explaining a configuration of a fifth embodiment. FIG. 10 is a diagram illustrating a specific example of image processing according to the fifth embodiment. FIG. 10 is a block diagram for explaining a configuration of a sixth embodiment. FIG. 10 is a block diagram for explaining a configuration of a seventh embodiment.

  Hereinafter, embodiments according to the present invention will be described in detail with reference to the drawings. However, the components described in this embodiment are merely examples, and are not intended to limit the scope of the present invention thereto.

  A first embodiment of the present invention will be described with reference to FIG. FIG. 1 is a block diagram illustrating a configuration example of the image processing apparatus according to the first embodiment. The image processing apparatus includes a screen processing unit 1, a gamma conversion unit 2, a white pixel boundary detection unit 3, a selector 4, an in-cell total calculation unit 5, an in-cell total calculation unit 6, a subtraction unit 7, The correction value calculation unit 8, the addition unit 9, and the dot stabilization unit 10 are included.

  Multi-value input image data is input to the image processing apparatus. Hereinafter, the multi-value input image data is simply referred to as input image data. A pixel value is stored in each pixel constituting the input image data. In this embodiment, each pixel constituting the input image data is represented by one of pixel values from 0 to 255.

  The screen processing unit 1 performs screen processing on the input image data for each pixel. For example, the screen processing unit 1 performs AM screen processing on the input image data. AM screen processing is also called organized dithering. The screen processing unit 1 performs screen processing by comparing a pixel value of each pixel constituting the input image data with a corresponding threshold value using a dither matrix including threshold values corresponding to each pixel. A pixel group determined by the dither matrix is defined as a cell. In the present embodiment, the screen processing binarizes the input image data. However, because the output value is a process described later, either 0 or 255, which is the quantized representative value, is output instead of 0 or 1. Each pixel value obtained by the screen processing is defined as a screen pixel value, and data constituted by a pixel represented by the screen pixel value is defined as image data after screen processing. That is, the screen processing unit 1 converts the input image data into post-screen processing image data, and outputs the post-screen processing image data.

  The gamma conversion unit 2 gamma-converts input image data using a gamma table. Each pixel constituting the input image data is converted into a pixel value after gamma conversion by gamma conversion. The gamma conversion unit 2 outputs image data after gamma conversion constituted by pixels represented by pixel values after gamma conversion.

  In this way, AM screen processing and gamma conversion are executed on the input image data in parallel. That is, image data after screen processing and image data after gamma conversion are obtained from the input image data.

  The white pixel boundary detection unit 3 detects a white pixel boundary pixel from the pixels included in the input image data. The white pixel boundary pixel is a pixel adjacent to the white pixel among the pixels that are not white pixels. In this embodiment, a pixel whose pixel value is 0 in the input image data is a white pixel. The white pixel boundary detection unit 3 detects whether each pixel in the input image data is a white pixel boundary pixel, and outputs data in which information representing the detection result is stored for each pixel.

  The selector unit 4 combines the screen-processed image data and the gamma-converted image data based on the white pixel boundary detection result by the white pixel boundary detection unit 3 and outputs the combined data. Data output from the white pixel boundary detection unit 3, image data after screen processing, and image data after gamma conversion all have corresponding pixel positions. The selector 4 selects a screen pixel value or a gamma conversion pixel value corresponding to the pixel position of the target pixel for a target pixel in the data output from the white pixel boundary detection unit 3. More specifically, the selector unit 4 performs control to select a pixel value after gamma conversion corresponding to the pixel position of the target pixel for the target pixel detected as the white pixel boundary pixel. For pixels other than the white pixel boundary pixels, control is performed so as to select a screen pixel value corresponding to the pixel position of the target pixel. Here, among the pixels constituting the image data after screen processing, the pixel position detected as the white pixel boundary pixel is replaced with the pixel value after gamma conversion. As a result of processing by the screen processing unit 1, gamma conversion unit 2, white pixel boundary detection unit 3, and selector unit 4, the pixel value of the white pixel boundary pixel becomes a pixel value obtained by gamma conversion, and the white pixel boundary pixel Pixel values other than are pixel values subjected to screen processing.

  The in-cell total calculation unit 5 and the in-cell total calculation unit 6 differ only in the image data to be handled and perform the same operation. The in-cell total calculation unit 5 and the in-cell total calculation unit 6 calculate the sum of the pixel values of the pixels included in the cell for each cell set by the screen processing unit 1. Specifically, the in-cell total calculation unit 5 calculates the total value of the pixel values of the pixels included in the cell for each cell in the data output from the selector unit 4. On the other hand, the in-cell total calculation unit 6 calculates the total value of the pixel values of the pixels included in the cell for each cell in the input image data.

  The subtraction unit 7 obtains a difference between the total values of the corresponding cells in the outputs of the in-cell total calculation unit 5 and the in-cell total calculation unit 6.

  The correction value calculation unit 8 obtains a correction value for each pixel based on the input image data. The correction value is calculated from the difference value for each cell output from the subtraction unit 7. In the present embodiment, in order to prevent edge blurring, white pixels having a pixel value of 0 in the input image data are not corrected. Therefore, the correction value calculation unit 8 outputs a correction value of 0 for white pixels having a pixel value of 0 in the input image data. On the other hand, the correction value calculation unit 8 calculates the difference value for each cell output from the subtraction unit 7 for the pixels having pixel values other than 0 in the input image data, among the pixels included in the cell, the pixel value in the input image data. A value obtained by dividing by the number of pixels other than 0 is output as a correction value.

  The adding unit 9 adds a corresponding correction value to the data output from the selector unit 4 for each pixel. As described above, the data output from the selector unit 4 is data in which pixels other than the white pixel boundary pixels are represented by screen pixel values, and the white pixel boundary pixels are represented by gamma conversion pixel values. The corrected image data output from the adder 9 is assumed to be corrected data.

  The dot stabilization unit 10 converts the corrected data into data having a number of bits such that the image forming apparatus can stably output an image. The output from the dot stabilization unit 10 is output to an image forming apparatus (not shown) and an image is printed.

  In the above description, the dot stabilization unit 10 is configured to match the number of input bits of the image forming apparatus. However, the output of the correction value calculation unit 8 is quantized and added to the number of bits that can be stably output by the image forming apparatus. The structure to do may be sufficient. When the output of the adding unit 9 exceeds the range of the input pixel value of the dot stabilizing unit 10, the output is clipped to be in the range of the input pixel value of the dot stabilizing unit 10 and input to the dot stabilizing unit 10. May be.

  The detailed operation of the first embodiment will be described with reference to FIGS. FIG. 2 is a matrix table showing an example of a dither matrix used when AM screen processing is performed in the screen processing unit 1. One square in FIG. 2 represents one pixel. The numbers in the squares represent the threshold values at the respective pixel positions. In this embodiment, multivalued image data having pixel values of 0 to 255 is input. The output of the screen processing unit 1 is a binary pixel value of 0, 255. The threshold value of the dither matrix in FIG. 2 is a threshold value for determining the output pixel value 0 or 255. That is, when the pixel value of the pixel of the input image data is equal to or smaller than the threshold value, the screen pixel value at the pixel position corresponding to the pixel in the post-screen processing data is 0. When the pixel value of the pixel of the input image data exceeds the threshold value, the screen pixel value of the pixel position corresponding to the pixel in the post-screen processing data is 255. Each cell in the dither matrix of the present embodiment has a shape shown by a thick line in FIG. 2, and is composed of a total of 32 pixels. In the following description, the area indicated by the bold line is called a cell.

  FIG. 3 is a diagram for explaining gamma conversion. FIG. 3A is a diagram illustrating an example of a gamma characteristic representing the relationship between the pixel value of the pixel and the output density in the input image data when a thin line is printed. The horizontal axis is the pixel value of the pixel in the input image data, and the vertical axis is the output pixel value (output density). The output density is normalized so that the maximum density is 255. In this embodiment, when the pixel value of the pixel in the input image data and the output density are in the relationship as shown in FIG. 3A, the following processing is performed. That is, in order to output the output density linearly in accordance with the input image data, the pixel value of the pixel in the input image data is converted using a gamma table as shown in FIG. By using this gamma table, the output pixel value after gamma conversion becomes large in the region where the pixel value of the pixel in the input image data is small. For example, if the pixel value of a pixel in the input image data is 96, it is converted to a pixel value after gamma conversion of 187 using this gamma table. The pixel value after gamma conversion is input to the selector unit 4.

  FIG. 4 is a diagram schematically illustrating an example of a white pixel detection filter and an example of white pixel detection using a filter. FIG. 4A is a diagram schematically showing a filter for white pixel detection in the white pixel boundary detection unit 3. In this filter, when the pixel value of the target pixel d is other than 0 and the pixel values of at least two pixels among the eight pixels d00 to d22 of the adjacent pixels are 0, the target pixel d is defined as a white pixel boundary. judge. A specific example will be described with reference to FIGS. In FIGS. 4B and 4C, the target pixel is surrounded by a circle. FIG. 4B shows an example in which the pixel value of the target pixel is 64, and the pixel values of the upper left, upper, and left pixels of the target pixel are 0. Therefore, it is determined that the target pixel is a white pixel boundary. To do. FIG. 4C illustrates an example in which the pixel value of the target pixel is 64 and all adjacent pixels of the target pixel are pixel values other than 0. Therefore, the target pixel is determined not to be a white pixel boundary. The detection result of the white pixel boundary detection unit 3 is sent to the selector unit 4.

  As described above, the selector unit 4 performs screen processing using the pixel value after gamma conversion from the gamma conversion unit 2 as the pixel value of the detected pixel position of the white pixel boundary, and the pixel value of the pixel position other than the white pixel boundary. The screen pixel value from the unit 1 is selected and output.

  The operation so far will be described with reference to FIGS. 5 to 7 using an example of a process in which input image data is converted. The pixel value of each pixel in a certain area in the input image data is shown in FIG. Note that a range surrounded by a thick line in FIGS. 5 to 7 corresponds to the size of one cell of the AM screen. When screen processing is performed on the pixel value of each pixel in the input image data shown in FIG. 5A, the screen pixel value of each pixel shown in FIG. 5B is obtained.

  Further, the output of the white pixel boundary detection unit 3 for the pixel value of each pixel in the same input image data shown in FIG. 5A is as shown in FIG. In FIG. 6A, 1 represents information indicating a white pixel boundary pixel, and 0 represents information indicating other than the white pixel boundary pixel. This information corresponds to the pixel position of each pixel of the input image data.

  As described above, the pixel value after gamma conversion corrected by the gamma table represented in FIG. Therefore, the output of the selector unit 4 for each pixel in the input image data shown in FIG. 5A is the pixel value of each pixel shown in FIG. The pixel value output from the selector unit 4 shown in FIG. 6B is a pixel value 187 after gamma conversion obtained by gamma-converting the pixel value 96 of the pixel of the input image data for the white pixel boundary pixel. Pixels other than the white pixel boundary pixels have screen pixel values (values of 0 or 255 in this example) shown in FIG.

  The operation of the in-cell total calculation units 5 and 6 will be described using the examples described so far. The in-cell total calculation unit calculates the sum of the pixel values of each pixel in the cell of the AM screen including the target pixel. The pixel value of each pixel after the selection process is input from the selector unit 4 to the in-cell total calculation unit 5. That is, pixel values as shown in FIG. 6B are input to the in-cell total calculation unit 5. Here, description will be made assuming that the pixel of interest is included in the cell indicated by the bold line. The in-cell total calculation unit 5 calculates the total value of the pixel values of the pixels in the cell indicated by the thick line in FIG. In this case, the total value is 0 × 26 + 187 × 4 + 255 × 2 = 1258.

  On the other hand, the pixel value of each pixel in the input image data is input to the in-cell total calculation unit 6. That is, pixel values as shown in FIG. 5A are input to the in-cell total calculation unit 6. The total pixel value shown in FIG. 5A at the pixel position corresponding to the cell indicated by the thick line in FIG. 6B is 0 × 18 + 96 × 14 = 1344. In-cell total calculation is performed in cell units.

The correction value calculation unit 8 subtracts the total value calculated by the in-cell total calculation unit 5 from the total value calculated by the in-cell total calculation unit 6 in the subtraction unit 7 by the number of effective image data in the cell. The value obtained by dividing is calculated as a correction value. The number of effective image data is the number of pixels whose pixel value is other than 0 among the pixels in the cell in the input image data. In the present embodiment, the number of effective image data in the thick line cell shown in FIG. 5A is 14, and the correction value is calculated as follows. (1344-1258) / 14 = 6
In the calculation of the correction value, the fractional part is rounded down, but may be obtained by rounding off.

  By adding the correction value obtained by the correction value calculation unit 8 to the output data of the selector unit 4 in the addition unit 9, the corrected image data after the halftone process can be obtained. Since the output data of the selector unit 4 includes a gamma-transformed white pixel boundary pixel, the area density represented by the pixel value of each pixel in the cell changes from the area density of each corresponding pixel in the input image data. There is a possibility. Therefore, in this embodiment, processing for correcting the output data of the selector unit 4 is performed in order to reduce the density fluctuation. Note that as described above, in order to prevent edge blurring, correction is not performed on pixels whose pixel value is 0 in the input image data. Further, each pixel in the corrected data cannot take a negative value or a value of 255 or more. Therefore, regardless of the correction value, the pixel value of each pixel in the corrected data is clipped at 0 and 255, respectively. In the present embodiment, the result of adding the correction value to each pixel in the output data of the selector unit 4 is shown in FIG. FIG. 7A shows the result of adding the correction value to the pixel value of each pixel in the region including the cell indicated by the thick line in FIG. 6B. As shown in FIG. 7A, the pixel values of the four white pixel boundary pixels are 187 + 6 = 193. In addition, in the post-screen processing image data after the AM screen processing, the pixel value of the pixel having the screen pixel value of 255 is as it is, and the pixel value of the pixel having the screen pixel value of 0 is 0 + 6 = 6.

  In this embodiment, a binary AM screen process is described. However, there are some that can form multi-tone dots in dot formation in the image forming unit. Further, since the white pixel boundary pixel is a pixel obtained by performing gamma conversion on the pixel in the input image data, it is preferable to output the intermediate data when a dot can be formed in a halftone. In this embodiment, the dot formation in the image forming unit (not shown) will be described on the assumption that one dot can be divided into 15 to form 16 gradation dots per dot. In this case, each dot having a pixel value from 0 to 255 is quantized in 16 steps before being input to the dot stabilization unit 10. In order to quantize 255 into 16 steps, multiples of 0 and 17 are used as quantization representative values. That is, among pixel values of 0 to 255, pixel values other than multiples of 0 and 17 are converted into pixel values of 0 and 17. FIG. 7B shows corrected data represented by quantized representative values. Of the pixels shown in FIG. 7A, the pixel value of the pixel of the corrected data corresponding to the pixel having a pixel value of 193 is represented by 187. Further, the correction value of the pixel of the corrected data corresponding to the pixel having the pixel value of 6 is represented by 0.

  In the dot stabilization unit 10, when an image is formed in the image forming unit using the corrected data, the pixel value of a pixel where dot formation is not stably performed is corrected to a pixel value that allows stable dot formation. To do. An example of this method is as follows. When it is determined that dot stabilization is necessary by detecting that the screen pixel value of the image data after screen processing is smaller than a predetermined value, the image is determined using the LUT determined in advance according to the surrounding dot pattern shape. Data conversion such as enlarging data is performed. When the surrounding dot pattern shape is a thin line, or when it is an isolated point, correction may be performed using different LUTs.

  In the present embodiment, it is possible to simplify the circuit of the dot stabilization unit by gamma-converting the pixel value of the white pixel boundary pixel in the input image data in advance. That is, in most cases, the white pixel boundary pixel becomes a contour portion or a fine line in the input image data, and therefore, gamma conversion is performed to connect to adjacent dots in a line shape. In addition, by performing gamma conversion that darkens the pixel value of the white pixel boundary pixel in the input image data, it is possible to correct the image data so as to ensure the latent image contrast with the white pixel portion of the background. . As a result, in the image forming unit, it is possible to stably form dots of white pixel boundary pixels that are connected in a line. Furthermore, by performing the correction to ensure the latent image contrast as described above, the dot stabilization unit can be simplified by omitting the dot stabilization processing for fine lines.

Next, the flow of image processing according to this embodiment will be described with reference to FIG.
In step S801, the image processing apparatus acquires input image data. In step S802, the screen processing unit 2 screen-processes the input image data acquired in step S801, and outputs screen-processed image data. In step S803, the gamma conversion unit 2 performs gamma conversion on the input image data acquired in step S801, and outputs image data after gamma conversion. In step S804, the white pixel boundary detection unit 3 detects white pixel boundary pixels in the input image data acquired in step S801. Note that the processing from step S802 to step S804 is performed in parallel.

  In step S805, the selector unit 4 determines the screen-processed image data obtained in step S802, the gamma-converted image data obtained in step S803, based on the detection result of the white pixel boundary pixel obtained in step S803. Is synthesized. For example, as described above, the selector unit 4 selects the pixel at the pixel position corresponding to the pixel detected as the white pixel boundary pixel among the pixels of the image data after screen processing, and the corresponding pixel in the image data after gamma conversion. Processing to replace the pixel value of the pixel at the position is performed.

  In step S806, the correction value calculator 8 calculates the difference between the total value for each cell in the output data output in step S805 and the total value for each cell at the corresponding position in the input image data obtained in step S801. Determine the correction value. As described above, the correction value calculation unit 8 determines a correction value for the effective pixel.

  In step S807, the adding unit 9 corrects the output data obtained in step S805 by adding the correction value determined in step S806.

  In step S808, the dot stabilization unit 10 stabilizes the dots of the corrected data.

  As described above, according to this embodiment, the pixel value of the pixel at the white pixel boundary portion in the input image data can be replaced with the pixel value after gamma conversion corrected by the gamma conversion table. The portion has a continuous linear shape. Therefore, the white pixel boundary portion maintains the same resolution as the input image. Further, since the background of the white pixel boundary portion is a white pixel without AM screen processing, the contrast of the latent image (the potential on the photosensitive drum) can be easily secured and stabilized. Therefore, there is an effect that the image quality of the white background character / line drawing is greatly improved. In addition, since it is not necessary to provide a plurality of screen processing units and complicated edge determination units, the processing (circuit) can be simplified.

  In the present embodiment, the example in which the white pixel boundary detection unit 3 detects a target pixel as a white pixel boundary pixel when at least two pixel values of adjacent pixels of the target pixel are 0 has been described. However, the target pixel may be detected as a white pixel boundary pixel when at least one pixel value of a pixel adjacent to the target pixel is 0.

  In addition, although the example in which the quantization process is performed when adding correction values, that is, performed in the previous stage of the dot stabilization unit 10, the quantization process may be performed in the dot stabilization unit 10.

  In the example described in the first embodiment, the example in which the quantized representative value after correction is 0, 187, or 255 has been described. However, the corrected quantized representative value may be a small value. In the present embodiment, an example in which dots are not formed when such a corrected quantized representative value is a small value will be described.

  FIG. 9 is a block diagram illustrating a configuration example of the image processing apparatus according to the second embodiment. In FIG. 9, the same reference numerals are given to components that perform the same operations as those in the first embodiment, and description thereof is omitted. In this embodiment, a stabilized pixel detection unit 11 is added, and the operation of the dot stabilization unit 12 is different from that of the dot stabilization unit 10 of FIG.

  10 and 11 are diagrams for explaining image processing in the second embodiment. By performing image processing similar to that of the first embodiment on the input image data in FIG. 10A, the output data of the adder 9 in FIG. 9 becomes as shown in FIG. 11B. More specifically, when each pixel in the input image data shown in FIG. 10A is screen-processed, image data after screen processing shown in FIG. 10B is obtained. When the pixel value at the position corresponding to the white pixel boundary pixel among the pixels of the image data after screen processing shown in FIG. 10B is replaced with a gamma conversion pixel value, output data as shown in FIG. 11A is obtained. . From this, the correction value is calculated in consideration of the number of effective image data, and when the pixel value of each pixel in FIG. 11A is corrected in consideration of the quantized representative value, the corrected data shown in FIG. A pixel value of each pixel is obtained. Among the corrected data in FIG. 11B, the hatched pixels indicate pixels whose pixel value is 17 by adding the correction value 17 to the pixel whose screen pixel value is 0 after the screen processing. ing. This value of 17 is the same as the smallest quantized representative value.

  Data with such a small value may be difficult to stabilize dots during image formation. Therefore, the stabilized pixel detection unit 11 compares the pixel value after addition of the pixel to which the correction amount is added by the addition unit 9 with a set threshold value, and when the pixel value after addition is smaller than the threshold value, The dot stabilization unit 12 is controlled so as not to perform stabilization. The dot stabilization unit 12 basically performs the same dot stabilization as the dot stabilization unit 10 of the first embodiment. The difference is that ON / OFF of dot stabilization is controlled by the control of the stabilization pixel detection unit 11. For example, in this embodiment, a dot having a very small value is generated in the vicinity of the white pixel boundary, but such a small dot hardly contributes to correction of density fluctuation. In particular, since it is difficult to visually detect density fluctuations at white pixel boundary pixels, the image quality is more stable when small dots generated by correction are not reproduced. Therefore, for example, when the threshold value is set to 34, the pixels in the shaded area in FIG. 11B can be prevented from performing dot stabilization. That is, the unstable dots that hardly contribute to the correction of the density fluctuation are not stabilized. As a result, the stabilization process is less performed on the image data of the flat portion other than the white pixel boundary pixels. In addition, since AM screen processing is performed on the flat portion, it is possible to stably form dots without performing dot stabilization processing. In other words, in this embodiment, dot stabilization processing can be simplified by applying dot stabilization only to specific pixels.

  FIG. 12 is a block diagram illustrating a configuration example of the image processing apparatus according to the third embodiment. In FIG. 12, the same reference numerals are given to components that perform the same operations as those in the first embodiment, and the description thereof is omitted. In this embodiment, a dot stabilizing unit 12 having the same function as that shown in FIG. 9 is added. Further, a signal line S1 for outputting the detection result of the white pixel boundary detection unit 3 to the dot stabilization unit 12 is added.

  In this embodiment, the dot stabilization unit 12 is controlled based on the detection result of the white pixel boundary detection unit 3. Specifically, dot stabilization is performed on pixels in output data corresponding to pixel positions detected as white pixel boundary pixels in the input image data. Dot stabilization is not performed on pixels in output data corresponding to pixel positions other than white pixel boundary pixels. As a result, it is possible to reliably stabilize the dots of the white pixel boundary pixels and not to stabilize the unstable dots that hardly contribute to the correction of the density variation. As described above, when dot stabilization is required, it is assumed that the dots are mainly thin lines or isolated points. Gamma conversion of white pixel boundary pixels will connect thin lines and isolated points into a line, but when the density of white pixel boundary pixels is very low, the density of white pixel boundary pixels after gamma conversion stabilizes the dots. In some cases, the concentration cannot be formed automatically. Therefore, dot stabilization is performed on the pixels in the output data corresponding to the pixel positions detected as white pixel boundary pixels. On the other hand, the pixels in the output data corresponding to the pixel positions other than the white pixel boundary pixels are considered to be the pixels of the flat portion, and the AM screen processing is performed. Can be formed. In other words, in this embodiment, dot stabilization processing can be simplified by applying dot stabilization only to specific pixels.

  In the first to third embodiments, the example in which the white pixel boundary pixel is detected and the pixel value after gamma conversion is used as the value of the white pixel boundary pixel has been described. However, the method of detecting the boundary pixel is not limited to the white pixel boundary pixel. In the following embodiments, an example will be described in which an edge portion pixel is detected as a boundary pixel and a gamma conversion pixel value is used as the edge portion pixel value.

  FIG. 13 is a block diagram showing the configuration of the fourth embodiment. The image processing apparatus shown in FIG. 13 converts multi-value input image data into image data with a smaller number of gradations. The image processing apparatus shown in FIG. 13 includes a screen processing unit 1301, a gamma conversion unit 1302, a selector unit 1303, an edge detection unit 1304, and in-cell total calculation units 1305 and 1306. The image processing apparatus shown in FIG. 13 includes a subtracter 1307, a correction amount calculation unit 1308, an adder 1309, and a dot stabilization unit 1310. Hereinafter, the operation of each unit will be described.

  The screen processing unit 1301 performs screen processing on the input image data for each pixel, converts the image data to screen-processed image data having a smaller number of gradations, and outputs the converted image data. Normally, the screen-processed image data is expressed with a smaller number of bits than the input image data, but here, a value corresponding to the quantized representative value is output as the pixel value of each pixel. For example, when the pixel value of each pixel of the input image data is 8 bits (0 to 255) and quantization is performed on a binary screen, the pixel value of each pixel after screen processing is output with a value of 0 or 255 Is done.

  14 and 15 are diagrams illustrating specific examples of image processing in the fourth embodiment. Here, FIG. 14A shows an example of a dither matrix that is used in the screen processing unit 1301 and includes threshold values corresponding to each pixel. In the figure, a cell is constituted by threshold values corresponding to each pixel surrounded by a thick line. The numbers in the cells indicate the threshold values when the pixel value of each pixel of the input image data is 8 bits (0 to 255). The screen processing unit 1301 performs screen processing by using the dither matrix to compare the pixel value of each pixel constituting the input image data with the corresponding threshold value. In this embodiment, one cell has 32 threshold values, and if the result of comparison with the threshold value is output as binary values (0, 255), the 33-level area gradation is obtained in one cell. realizable. As described above, the screen processing unit 1301 according to the present embodiment does not output the screen pixel value in the post-screen processing data as a binary value, but outputs a value corresponding to the quantized representative value. That is, 0 is output when the value is less than the threshold value, and 255 is output when the value is greater than the threshold value. For example, the screen pixel value for each pixel in the input image data shown in FIG. 14B is as shown in FIG.

  The gamma conversion unit 1302 performs gamma conversion optimized for edges in order to stabilize the dots in the edge part continuously.

  FIG. 16 shows an example of the characteristics of the gamma conversion unit 1302. The horizontal axis represents the pixel value (0 to 255) of the pixel in the input image data, and the vertical axis represents the pixel value (0 to 255) output after the gamma conversion. In contrast to the normal linear characteristic 1601, the gamma conversion characteristic 1602 has a characteristic of converting the pixel value of the pixel in the input image data of the low density portion into a pixel value on the high density side and outputting it. Here, in gamma conversion, the pixel values (0 to 255) of the input image data are set to 16 levels (0, 17,...) In accordance with the accuracy (4-bit quantization) of the PWM circuit in the latter stage of the image processing unit (not shown). 34,..., 238, a multiple of 255: 17). For example, in this embodiment, the pixel value “96” of the pixel of the input image data in FIG. 14B is gamma-converted to “187”.

  Based on the detection result of the edge detection unit 1304, the selector unit 1303 uses the gamma converted pixel value of the gamma conversion unit 1302 as a pixel corresponding to the pixel position of the target pixel when the target pixel in the input image data is the pixel of the edge unit. select. When the target pixel is not the edge pixel, the screen pixel value of the screen processing unit 1301 is selected as a pixel corresponding to the pixel position of the target pixel.

The edge detection unit 1304 detects pixels corresponding to the edge portion from the input image data. Here, as an edge detection method, an example in which a target pixel is detected as an edge pixel when a difference amount between the target pixel and an adjacent pixel exceeds a threshold value will be described with reference to FIG. Assuming that the pixel at the center in FIG. 17 is the target pixel *, the edge pixel is detected by comparing the maximum difference amount with the threshold value among the difference amounts of the four neighboring pixels adjacent to the target pixel. The edge pixel detects the high density side. That is, if the maximum difference amount is DIFF and the threshold is TH, edge detection is performed under the following conditions.
DIFF = max ((*-a), (* -b), (* -c), (* -d))
When DIFF = (*-a)
If DIFF ≥ TH, it is judged as an edge, otherwise it is judged as a non-edge.
As well
When DIFF = (*-b)
If DIFF ≥ TH, it is judged as an edge, otherwise it is judged as a non-edge.
When DIFF = (*-c)
If DIFF ≥ TH, it is judged as an edge, otherwise it is judged as a non-edge.
When DIFF = (*-d)
If DIFF ≥ TH, it is judged as an edge, otherwise it is judged as a non-edge.
For example, when TH = 64, the pixel 1401 in FIG. 14B is determined to be a non-edge because DIFF = 0. The pixel 1402 is determined to be an edge because DIFF = (* − a) or (* −b) = 96 and DIFF> TH = 64.

  FIG. 15A shows output data of the selector unit 1303. Of the pixels in the screen-processed image data shown in FIG. 14C, the pixel value of the pixel at the pixel position corresponding to the edge pixel is replaced with a value of '187' which is a pixel value after gamma conversion.

  The in-cell total calculation unit 1305 integrates the output data from the selector unit 1303 for each cell, and the pixel values of the pixels included in the cell. For example, when the output data from the selector unit 1303 is shown in FIG. 15A, the sum in the thick frame cell is 187 × 4 + 255 × 2 = 1258. The in-cell total calculation unit 1306 integrates the input image data for each cell and the pixel values of the pixels included in the cell. For example, when the pixel value of the pixel in the input image data is shown in FIG. 14B, the sum in the thick cell is 96 × 14 = 1344.

  The subtracter 1307 subtracts the output of the in-cell total calculation unit 1305 from the output of the in-cell total calculation unit 1306 to calculate the total value of density fluctuations in the cell. For example, in the example of the cell indicated by the thick line in FIGS. 14 and 15, the output of the in-cell total calculation unit 1306−the output of the in-cell total calculation unit 1305 = 1344-1258 = 86.

  The correction amount calculation unit 1308 normalizes the output of the subtracter 1307 with the number of pixels that can be corrected in the cell, and calculates a correction amount per pixel. Here, the correctable pixel is a pixel whose pixel value is not “0” among the pixels constituting the input image data. In this embodiment, in order to prevent edge blurring, a pixel having a pixel value of “0” among pixels constituting the input image data is set as an uncorrectable pixel. For example, in the example shown in FIGS. 14 and 15, the number of pixels that can be corrected in the thick-line cell in FIG. 14B is ‘14’. Therefore, the correction amount is INT (86/14) = 6 (INT () indicates a truncation operation after the decimal point). However, the correction amount is quantized and converted to 16 levels in accordance with the accuracy of the PWM circuit. Therefore, the final correction value is INT ((6 + 8) / 17) * 17 = 0. FIG. 15B shows the correction amount for each pixel calculated by the correction amount calculation unit 1308. Pixels colored in gray are correctable pixels calculated by the above calculation, and indicate the correction amount for each pixel calculated by the correction amount calculation unit 1308. In this example, the correction amount of pixels that can be corrected is 0 as described above. Since the portions other than those colored in gray are pixels that cannot be corrected, the correction amount is set to “0”.

  An adder 1309 performs correction processing by adding the correction amount of the pixel at the corresponding pixel position output from the correction amount calculation unit 1308 to the pixel value of each pixel in the output data of the selector unit 1303. Here, if the addition result is less than “0”, the value is clipped to “0”. When the addition result is larger than “255”, the value is clipped to “255”.

  Here, when there is a density variation, a density variation that does not exist in the input image data occurs on the image data after the screen processing, which causes moire. By performing correction processing with the adder 1309, density fluctuation is suppressed. Further, in this embodiment, the correction value is calculated by replacing the pixel value of the pixel at the edge portion in the image data after screen processing with a large value obtained by gamma-converting the pixel value of the pixel at the corresponding pixel position in the input image data. Yes. This prevents data with a small value from occurring near the edge, allowing dots with relatively large values to be concentrated on the edge, and improving the image quality of the character line drawing by making the dots continuous in a line. And making it easier to stabilize dots during image formation.

  Next, the operation of the dot stabilization unit 1310 will be described. In this embodiment, the screen-processed image data is corrected so that there is no density variation for each cell. As a result of the correction, the dot formation is not stably performed for the pixel having a small pixel value. Therefore, data conversion is performed to stabilize the dots. For example, an operation for guaranteeing a minimum pulse width in a post-stage PWM circuit (not shown) is performed. In other words, when the data input to the dot stabilization unit 1310 is less than a preset minimum value and there are non-zero values in the surrounding area, if the value is equal to or greater than the set value by adding the value, the larger value Add to the data. Alternatively, the phase of the PWM circuit may be controlled so that the pulses are continuous. On the other hand, if the input data is less than a preset minimum value and there are no non-zero values around it, the value is replaced with the minimum value.

  In this embodiment, the circuit of the dot stabilization unit is simplified by performing gamma conversion on the input image data in advance. For example, the minimum value pulse width guarantee operation can be eliminated by performing gamma conversion so as to guarantee the minimum pulse width for the edge portion. In addition to the edge portion, small values near the edge are added to the edge portion, thereby minimizing the region where the small values continue. For this reason, it is possible to eliminate the minimum value pulse width guaranteeing operation even at portions other than the edge portion.

  According to the present embodiment, it is possible to correct a defect in screen processing by a simple method and obtain a good gradation conversion result. In particular, the correction data is concentrated on the edge pixels by using the image data after screen processing in which the pixel corresponding to the pixel position of the edge pixel in the input image data is replaced with a gamma-converted pixel value obtained by gamma conversion. Is possible. As a result, the dots at the edge portion are continuous in a line shape, and the image quality of characters and line drawings is greatly improved by stabilizing the dots.

  Next, Example 5 will be described below. FIG. 18 is a block diagram illustrating the configuration of the image processing apparatus according to the fifth embodiment. In FIG. 18, components that perform the same operations as those in the fourth embodiment are denoted by the same reference numerals, and description thereof is omitted. In this embodiment, a stabilization pixel detection unit 1801 is added, and the dot stabilization unit 1802 operates differently from the dot stabilization unit 1310 of FIG.

  For example, in the input image data shown in FIG. 19A, when the phase relationship of the cells of the dither matrix is different from that shown in FIG. 14A as shown in FIG. When the processing is performed, the correction amount of each pixel is calculated as shown in FIG. As a result of the addition in the adder 1309, corrected data as shown in FIG. 19C is output. In FIG. 19C, data ‘17’ having a small value is generated in the vicinity of the edge portion, which may make it difficult to stabilize the dots during image formation.

  In order to prevent such a problem, in the stabilized pixel detection unit 1801 of this embodiment, when the pixel value after addition of the pixel to which the correction amount is added by the adder 1309 is smaller than the set threshold value, The dot stabilization unit 1902 is controlled so as not to perform dot stabilization. The dot stabilization unit 1902 performs stabilization equivalent to that of the dot stabilization unit 1310, but performs dot stabilization ON / OFF under the control of the stabilization pixel detection unit 1801. As a result, unnecessary stabilization processing is not performed on dots other than the edge portion. Such a very small dot near the edge hardly contributes to the correction of the density fluctuation. In particular, since it is difficult to visually detect density fluctuation at the edge portion, the image quality is more stable when the small dots generated by the correction are not reproduced. In other words, by avoiding stabilization of unstable dots that hardly contribute to correction of density fluctuation, in other words, by applying dot stabilization processing only to specific pixels, the dot stabilization unit 1310 can be simplified.

  Next, Example 6 will be described below. FIG. 20 is a block diagram illustrating the configuration of the image processing apparatus according to the sixth embodiment. In FIG. 20, the same reference numerals are given to components that perform the same operations as those in the fourth embodiment, and description thereof is omitted. In this embodiment, a dot stabilization unit 1802 having the same function as that shown in FIG. 18 is added.

  In this embodiment, the dot stabilization unit 1802 is controlled based on the detection result of the edge detection unit 1304. Therefore, dot stabilization is performed at the edge portion, and dot stabilization is not performed at portions other than the edge portion. As a result, the dot at the edge is surely stabilized and unstable dots that hardly contribute to the correction of the density variation as shown in FIG. 19C are not stabilized. Therefore, as in the fifth embodiment, the dot stabilization unit 1310 can be simplified by applying the dot stabilization process only to specific pixels.

  Next, Example 7 will be described below. FIG. 21 is a block diagram illustrating the configuration of the image processing apparatus according to the seventh embodiment. In FIG. 21, the same reference numerals are given to components that perform the same operations as those in the fourth embodiment, and the description thereof is omitted. In this embodiment, a gamma conversion unit 2101 is added. The fourth to sixth embodiments have been described on the assumption that the pixel value of each pixel in the input image data is subjected to gamma conversion for screen processing. In this embodiment, input image data before gamma conversion is input, gamma conversion for the screen processing is performed by the gamma conversion unit 2101, and output to the screen processing unit 1301. As a result, the input image can be independently subjected to gamma conversion for the edge portion and gamma conversion for the screen processing. Therefore, it is possible to simultaneously perform edge portion and thin line enhancement processing.

  Similarly, in the processing in the first to third embodiments, a configuration in which input image data before gamma conversion is input, gamma conversion for screen processing is performed in the gamma conversion unit, and output to the screen processing unit 1 is adopted. Also good.

  As described above, in the fourth to seventh embodiments, it is possible to correct a defect of the screen processing by a simple method and obtain a favorable gradation conversion result. In particular, it is possible to concentrate correction data on the edge portion by using screen-processed image data obtained by replacing the pixel corresponding to the pixel position of the edge portion pixel in the input image data with a gamma-converted pixel value obtained by gamma conversion. Become. As a result, the dots at the edge portion are continuous in a line shape, and the image quality of characters / line drawings is greatly improved by stabilizing the dots. Further, in the dot stabilization unit, the dot stabilization of the edge portion is reliably performed by controlling ON / OFF of dot stabilization based on the corrected value and the edge information. At the same time, unstable dots that hardly contribute to correction of density fluctuations are not stabilized, and stable high-quality output is possible.

<Other examples>
In the first to third embodiments, an example in which a white pixel boundary pixel is detected as a boundary pixel has been described, and in the fourth to seventh embodiments, an edge portion is detected as a boundary pixel. In the first to third embodiments and the fourth to seventh embodiments, other processes may be treated as a common process except that a target to be detected as a boundary pixel is different. Therefore, the processing described in the first to third embodiments may be performed in the fourth to seventh embodiments, and the processing described in the fourth to seventh embodiments may be performed in the first to third embodiments. For example, in the fourth embodiment, the gamma conversion unit 1302 converts the data after gamma conversion according to the accuracy of the PWM circuit. However, the gamma conversion unit 2 of the first embodiment also performs the same processing. May be. When a signal for identifying a boundary pixel is input as input pixel attribute data together with input pixel data, the attribute data can be used in place of the outputs of the white pixel boundary detection unit 3 and the edge detection unit 1304. . Accordingly, the white pixel boundary detection unit 3 and the edge detection unit 1304 can be omitted. That is, when position information indicating the position of the boundary pixel in the input image data is input, the position of the boundary pixel can be specified using the position information.

  Further, in the fourth to seventh embodiments, the process of replacing the pixel corresponding to the pixel position of the pixel at the edge portion in the screen-processed image data with the pixel value after gamma conversion has been described as an example, but the present invention is not limited thereto. It is not a thing. For example, it may be a process of replacing pixel values of pixels other than the edge portion of each pixel after gamma conversion with screen pixel values. In addition, a data area having the same number of pixels of the input image data is secured, and the pixel value after gamma conversion is stored for the pixel at the pixel position corresponding to the edge pixel, and the pixel position corresponding to the pixel other than the edge part This pixel may be a process of storing a screen pixel value. The same applies to the processing of the first to third embodiments.

  The present invention can also be realized by executing the following processing. That is, software (program) for realizing the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, etc.) of the system or apparatus reads the program. It is a process to be executed.

Claims (21)

Oite the input image data, among the pixels that are not white pixels, and detecting means for detecting a pixel adjacent to the white pixel as a boundary pixel,
Performs screen processing by ordered dithering the input image data, and the screen processing unit which outputs the image data after screen processing,
Gamma conversion means for gamma-converting the input image data and outputting the image data after gamma conversion;
On the basis of the detected boundary pixels by the detection means, it has a synthesizing means for synthesizing said screen processed image data and the gamma converted image data,
The detection means detects a white pixel in the pixel of interest and a pixel group adjacent to the pixel of interest for the pixel of interest in the input image data, and the pixel of interest is the boundary pixel based on a result of detecting the white pixel. An image processing apparatus characterized by determining whether or not .   The combining means replaces the pixel value of the pixel at the pixel position corresponding to the detected boundary pixel in the post-screen processing image data with the pixel value of the pixel at the corresponding pixel position in the image data after gamma conversion. The image processing apparatus according to claim 1, wherein:   The synthesizing unit outputs a pixel value of a pixel at a corresponding pixel position in the image data after gamma conversion as a pixel value at a pixel position corresponding to the boundary pixel, and a pixel at a pixel position corresponding to a pixel other than the boundary pixel. The image processing apparatus according to claim 1, wherein a pixel value at a corresponding pixel position in the post-screen processing image data is output as a value. A determination means for determining a correction value based on the input image data and the combined data;
The image processing apparatus according to claim 1, wherein the synthesizing unit adds the correction value to a pixel value of a pixel in the synthesized data.   The image processing apparatus according to claim 4, wherein the determination unit determines the correction value for each cell used for the screen processing.   The determining means is based on a difference between a total value of pixel values of each pixel in the cell of the input image data and a total value of pixel values of each pixel in the cell of the combined data corresponding to the cell. The image processing apparatus according to claim 4, wherein the correction value is determined.   The image according to claim 6, wherein the determining unit determines the correction value by dividing the difference by the number of pixels in which pixel values of pixels in the cell in the input image data are not 0. Processing equipment.   8. The determined correction value is added to a pixel value of the combined pixel at a pixel position corresponding to a pixel with a pixel value other than 0 in the input image data. The image processing apparatus according to one item.   The image processing apparatus according to claim 4, further comprising dot stabilization means for performing dot stabilization processing on the data synthesized by the synthesis means.   The image processing apparatus according to claim 9, wherein the data input to the dot stabilization unit is quantized with a value corresponding to the number of gradations at which dots can be formed.   The image processing apparatus according to claim 9, wherein the correction value is a value quantized with a value corresponding to the number of gradations at which dots can be formed.   The image processing apparatus according to claim 9, wherein the gamma conversion unit outputs a value quantized to a value corresponding to the number of gradations at which dots can be formed.   The dot stabilization unit does not perform the dot stabilization process on a pixel to which the correction value is added when the value of the pixel to which the correction value determined by the determination unit is added is equal to or less than a threshold value. The image processing apparatus according to claim 9. The dot stabilization means performs dot stabilization processing on a pixel corresponding to a pixel position detected as the boundary pixel,
The image processing apparatus according to claim 9, wherein a dot stabilization process is not performed on pixels corresponding to pixel positions other than the pixels detected as the boundary pixels.   The image processing apparatus according to claim 1, wherein the gamma conversion unit converts a low density pixel value into a high density pixel value. The image processing apparatus according to claim 1, wherein the detection unit detects a pixel having a pixel value of 0 as a white pixel in an image group adjacent to the target pixel. The detection unit detects the target pixel as the boundary pixel when the pixel value of the target pixel is a non-zero value and at least two pixels of the image group adjacent to the target pixel are white pixels. the image processing apparatus according to any one of claims 1 to 16, characterized in that. Detecting means for detecting a pixel adjacent to the white pixel among the pixels that are not white pixels in the input image data as a boundary pixel;
Performs screen processing by ordered dithering the input image data, and the screen processing unit which outputs the image data after screen processing,
Conversion means for converting the value of the pixel corresponding to the pixel position of the boundary pixel in the screen processed image data to a value higher than the value of the pixel corresponding to the pixel position of the boundary pixel in the input image data,
The controlled so as to perform dot stabilization process on the converted boundary pixel conversion means,
Is controlled so as not to perform the dot stabilization treatment in addition to the boundary pixels, have a control unit,
The detection means detects a white pixel in the pixel of interest and a pixel group adjacent to the pixel of interest for the pixel of interest in the input image data, and the pixel of interest is the boundary pixel based on a result of detecting the white pixel. An image processing apparatus characterized by determining whether or not . And have you to input image data, among the pixels that are not white pixels, a detection step of detecting a pixel adjacent to the white pixel as a boundary pixel,
A screen processing step performs screen processing, and outputs the image data after screen processing by ordered dithering the input image data,
A gamma conversion step of gamma converting the input image data and outputting the image data after gamma conversion;
The detection based on the detected boundary pixels in step, possess a synthesis step of synthesizing said screen processed image data and the gamma converted image data,
In the detection step, for the target pixel in the input image data, a white pixel is detected in the target pixel and a pixel group adjacent to the target pixel, and the target pixel is determined as the boundary pixel based on a result of detecting the white pixel. An image processing method characterized by determining whether or not . In the input image data, a detection step of detecting, as a boundary pixel, a pixel adjacent to the white pixel among pixels that are not white pixels;
A screen processing step performs screen processing, and outputs the image data after screen processing by ordered dithering the input image data,
A conversion step of converting the pixel value corresponding to pixel positions of the boundary pixels in the screen processed image data to a value higher than the value of the pixel corresponding to the pixel position of the boundary pixel in the input image data,
The controlled so as to perform dot stabilization process on the converted boundary pixels in the conversion step,
Is controlled so as not to perform the dot stabilization treatment in addition to the boundary pixels, have a controlling process,
In the detection step, for the target pixel in the input image data, a white pixel is detected in the target pixel and a pixel group adjacent to the target pixel, and the target pixel is determined as the boundary pixel based on a result of detecting the white pixel. An image processing method characterized by determining whether or not . Program for functioning as an image processing apparatus according to any one of the computer claims 1 18.

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