JP3788913B2 - Image processing method, image processing apparatus, and image forming apparatus - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image processing method, an image processing apparatus, and an image forming apparatus that perform noise superimposition processing for superimposing noise on image data.
[0002]
[Prior art]
When an image having continuous gradation and an image with a reduced number of gradations are output by a digital image forming apparatus or the like, a binary dither method, an error in the image processing apparatus is used in advance to improve gradation reproducibility. Halftone processing is performed using a method such as a diffusion method, a multi-value dither method, or a multi-value error diffusion method. However, there is a problem that such halftone processing causes pseudo contours and density unevenness in the output image, and the graininess deteriorates.
[0003]
As a countermeasure, there has been proposed an image processing apparatus that obtains a visually more preferable image by superimposing noise on input image data. In the image signal processing method and apparatus described in Japanese Patent No. 2894117, noise having a spatial frequency characteristic that is difficult to visually perceive is superimposed on the input image signal in advance according to the image signal level. As a result, the image noise and pseudo contours of the document itself can be canceled without impairing the sharpness and color tone of the image, and a visually preferable image can be obtained. Further, the image processing apparatus described in Japanese Patent Laid-Open No. 9-200523 includes means for determining whether an image signal belongs to a gradation group that generates a pseudo contour at the time of output, and belongs to a gradation group determined at the time of image output. Means for superimposing noise on the pixel.
[0004]
[Problems to be solved by the invention]
However, the above conventional technique has the following problems. Since the image processing apparatus described in Japanese Patent No. 2894117 superimposes noise on all pixels, it also degrades the sharpness of a portion of a gradation group that does not generate a pseudo contour. In addition, the image processing apparatus described in Japanese Patent Application Laid-Open No. 9-201053 discloses a boundary between a portion of a gradation group that generates a pseudo contour when an excessive noise is superimposed in order to cancel a pseudo contour that occurs when noise is not superimposed, and a portion that does not. May cause a pseudo contour.
[0005]
An object of the present invention is to provide an image processing method, an image processing apparatus, and an image forming apparatus that are more visually appealing and can perform high-quality recording with excellent resolution and gradation.
[0006]
[Means for Solving the Problems]
The present invention relates to an image processing method for performing noise superimposition processing for superimposing noise on image data and halftone output gradation processing for performing halftone generation processing.
The noise superimposing process superimposes noise on image data in a predetermined input density value range,
In the image processing method, the range of the input density value is larger than twice the amplitude of noise centering on a boundary where image quality deterioration occurs .
[0007]
According to the present invention, the noise superimposing process superimposes noise on image data in a predetermined input density value range, and the input density value range is a noise amplitude centering on a boundary where image quality degradation occurs. Therefore, it is less likely to generate a pseudo contour at the boundary between the input density value range where noise is superimposed and other portions, which is more preferable visually, and provides high-quality recording with excellent resolution and gradation. be able to.
[0008]
Further, the present invention is characterized in that a plurality of input density value ranges are set.
According to the present invention, since a plurality of input density value ranges are set, it is possible to apply noise superimposition processing suitable for each of the plurality of input density value ranges.
[0009]
Further, the present invention is characterized in that the amplitude of noise is set for each range of the input density value.
[0010]
According to the present invention, since the noise amplitude is set for each input density value range, an appropriate amount of noise superimposing processing can be performed for each input density value range.
[0011]
According to the present invention, when the image data is color image data, the range of the input density value is set for each color component.
[0012]
According to the present invention, when the image data is color image data, the input density value range is set for each color component, and therefore noise superimposition processing is performed on the appropriate input density value range for each color component. Can do.
[0013]
According to another aspect of the present invention, there is provided an image processing apparatus including noise superimposing processing means for processing input image data using the above-described image processing method.
[0014]
According to the present invention, since the input image data has noise superimposing processing means for performing processing using the above-described image processing method, a pseudo contour is formed at the boundary between the input density value range where noise is superimposed and other portions. Is less likely to occur, is more visually desirable, and can perform high-quality recording with excellent resolution and gradation.
[0015]
According to another aspect of the present invention, there is provided an image forming apparatus comprising: an image input apparatus that reads a document to obtain image data; the image processing apparatus described above; and an image output apparatus that outputs processed image data. is there.
[0016]
According to the present invention, the image processing apparatus includes an image input device that reads a document to obtain image data, the image processing device, and an image output device that outputs processed image data. A pseudo contour hardly occurs at the boundary between the range of values and other portions, which is more visually desirable, and can form a high-quality image with excellent resolution and gradation.
[0017]
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 is a block diagram showing a configuration of an image forming apparatus 11 including an image processing apparatus 13 according to an embodiment of the present invention. The image forming apparatus 11 is, for example, a digital copying machine using an electrophotographic system or an inkjet system. The image forming apparatus 11 includes an image input device 12, an image processing device 13, and an image output device 14. The image processing device 13 includes an analog / digital (hereinafter abbreviated as "A / D") conversion unit 21, a shading correction unit. 22, an input tone correction unit 23, a color correction unit 24, an image area separation processing unit 25, a black generation under color removal unit 26, a spatial filter processing unit 27, a noise superimposition processing unit 28, a halftone output tone processing unit 29, It comprises a curve storage unit 30, a correction amount storage unit 31, and an output conversion table storage unit 32.
[0018]
The A / D converter 21 converts RGB (R: red, G: green, B: blue) reflectance signals, which are image data supplied from the image input device 12, into digital signals. The shading correction unit 22 performs a shading correction process on the A / D converted reflectance signal. The shading correction process is performed to remove various distortions that occur in the image signal due to the configuration of the illumination system, the imaging system, and the imaging system of the image input device 12. The input tone correction unit 23 performs input tone correction processing on the reflectance signal that has been subjected to the shading correction processing. The input gradation correction process is a process for converting the reflectance signal into a signal that can be easily handled by the image processing apparatus 13 such as a density signal. The input tone correction unit 23 may further perform color balance processing on the reflectance signal. The color correction unit 24 converts the RGB density signal into a CMY (C: cyan, M: magenta, Y: yellow) density signal and realizes faithful color reproduction in the image output device 15. Color correction processing is performed on the density signal. Specifically, the color correction process is a process of removing color turbidity based on the spectral characteristics of CMY toners and inks each including unnecessary absorption components from the CMY density signal. Based on the CMY density signal output from the color correction unit 24, the image region separation processing unit 25 performs region separation processing on the image data into a character region, a photographic region, a halftone dot region, and the like. The separation result in the image area separation processing unit 25 is given to the black generation under color removal unit 26 and the spatial filter processing unit 27 and may also be given to the halftone output gradation processing unit 28. The black generation under color removal unit 26 performs black generation processing for generating a black color signal based on the CMY color signals constituting the density signal output from the color correction unit 24. The black generation under color removal unit 26 performs under color removal processing on the CMY color signal. The under color removal process is a process for obtaining a new CMY color signal by subtracting the black color signal generated by the black generation process from the CMY color signal. As a result of these processes, the CMY density signal is converted into image data composed of CMYK (K: black) color signals. The spatial filter processing unit 27 performs spatial filter processing using a digital filter on the CMYK image data obtained by the black generation and under color removal unit 26. As a result, the spatial frequency characteristics of the image such as edge enhancement are corrected, so that it is possible to prevent the image output from the image output device 15 from being blurred or deteriorated in graininess.
[0019]
The noise superimposing processing unit 28 is noise superimposing processing means for superimposing, as noise, a table value of a noise matrix table prepared in advance or an output value from a random number generation circuit or the like on CMYK image data after spatial filtering. The halftone output gradation processing unit 29 performs gradation correction processing and halftone generation processing on the CMYK image data after the noise superimposition processing. The halftone generation process is a process that makes it possible to reproduce gradation by dividing an image into a plurality of pixels. The halftone output gradation processing unit 29 may perform processing for converting the density value of the image data into a halftone dot area ratio that is a characteristic value of the image output device 14. The density signal processed by the halftone output gradation processing unit 29 is given to the image output device 14.
[0020]
Hereinafter, the noise superimposition processing unit 28 and the halftone output gradation processing unit 29 will be described. Note that the noise superimposition process and halftone generation process for the density values of each color component of CMYK differ only in the actual input density value for superimposing the noise, so the noise superimposition process for the density value of any one color component Only halftone output tone processing is described.
[0021]
First, the tone correction processing in the halftone output tone processing unit 29 will be described. FIG. 2 is a graph showing a reference correction curve 41 and a gradation correction curve 42 used for the gradation correction process. The horizontal axis represents the input density value of the image data, and the vertical axis represents the correction value for the input density value. In FIG. 2, 8-bit correction values 0-255 are output for 8-bit input density values 0-255. The halftone output gradation processing unit 29 has a plurality of reference correction curves 41 stored in the curve storage unit 30 and a plurality of correction amount storage units 31 stored when the CMYK image data is given to the image processing device 14. A gradation correction curve 42 to be actually used is created using the correction amount of. Based on the created gradation correction curve, correction values 0 to 255 corresponding to the input density values 0 to 255 are stored in the output conversion table storage unit 32 as an output conversion table. Even if the image output apparatus is designed in the same manner, the output characteristics differ depending on the tolerance of the design. Even in the same device, the output characteristics differ depending on the use conditions and the use period of the device. Therefore, by setting the gradation correction curve and the output conversion table from the reference correction curve and the correction amount stored in advance, the desired characteristics can be obtained. Output characteristics can be obtained.
[0022]
Next, a halftone generation process performed after the gradation correction process will be described. The halftone generation processing performs dither processing or error diffusion processing. When dither processing is performed to reduce the number of reproduced gradations to 17 by threshold processing using a 4 × 4 threshold matrix, a pseudo contour is generated in the output image. Therefore, among correction values that are actual output values, a range of correction values that generate a pseudo contour in the halftone generation process is determined in advance, and an input density value corresponding to this range is obtained from the gradation correction curve and the output conversion table. By superimposing noise on the image data in the range of the obtained input density value, it is possible to suppress pseudo contours that are easily perceived by human eyes.
[0023]
In the case of error diffusion processing in which a quantization error in a pixel of interest having image data is diffused to surrounding pixels to generate a halftone, the threshold value is set to 128. If the input density value is 128 or more, the output density value is 255, and the input density value is If it is less than 128, the output density value is set to zero. In the output image by this error diffusion processing, there is a portion where the graininess is deteriorated. Therefore, among correction values that are actual output values, a correction value range in which the graininess deteriorates in the halftone generation process is determined in advance, and an input density value corresponding to this range is obtained from the gradation correction curve and the output conversion table. . Graininess can be improved by superimposing noise on the image data in the range of the obtained input density value. The range of the correction value may be an output value that causes density unevenness. Here, the output density value does not indicate the density value of one pixel, but in a dither process using a region composed of a plurality of pixels, for example, a 4 × 4 threshold matrix, than the 4 × 4 pixels. The density value of the area.
[0024]
A method for obtaining a range of input density values corresponding to a predetermined range of correction values will be described. Here, a predetermined correction value range is set to m1 or more and m2 or less, and a corresponding input density value range is set to n1 or more and n2 or less. The range of m1 or more and m2 or less is determined in advance as a range in which pseudo contour and density unevenness occur as described above. FIG. 3 is a diagram illustrating an input density value range corresponding to the correction value range on the gradation correction curve. The gradation correction curve is sequentially compared with m1 from 0, which is the minimum input density value of the gradation correction curve, to high density, and an input density value at which the correction value is m1 or more is first obtained. If there are a plurality of input density values with a correction value of m1, the average density value of the corresponding plurality of input density values is n1. When calculating the average value, the decimal part is rounded down or rounded up. Also, if the correction value that is m1 or more is a value larger than m1, the correction value at that time is compared with the correction value corresponding to the one lower input density value, and the input density value closer to m1 is set to n1. To do. Next, when obtaining n2, the input density value n1 + 1 on the gradation correction curve is compared with m2 in order from the density, and an input density value having a correction value of m2 or more is obtained first. Thereafter, it can be obtained in the same manner as when n1 is obtained. The noise superimposition processing unit 28 performs noise superimposition processing on image data having an input density value in the range of n1 or more and n2 or less.
[0025]
The noise superimposition process in the noise superimposition process part 28 is demonstrated. Here, the pseudo contour is generated at the boundary between a pixel having an input density value of 200 or less and a pixel of 201 or more. In order to cancel the pseudo contour, the image data processed by the spatial filter processing unit 27 may have an input density value range corresponding to the correction value range in which the pseudo contour occurs, for example, an input density value range of 193 to 208. Noise is superimposed. Assuming that the noise amplitude is 10, the input density values 183 to 203 are output to the halftone output gradation processing unit 29 by the noise superimposing process for the input density value 193, and the gradation correction process / halftone generation is performed. The image is output on a recording medium such as paper by the image output device 14 after being processed. In this case, data of a dark density region having an input density value 201 or higher that causes a pseudo contour generated at a boundary between different density values is included. As a result, a pseudo contour may occur at the boundary between a pixel having an input density value of 192 or less and a pixel of 193 or more. Also, for the input density value 208, the input density values 198 to 218 are output to the halftone output tone processing unit 29 by noise superimposition processing, and subjected to tone correction processing and halftone generation processing to be processed. The data is output on a recording medium such as paper by the output device 14. Then, data of a light density area of 200 or less that causes a pseudo contour is included. As a result, a pseudo contour may occur at the boundary between a pixel having an input density value of 208 or lower and a pixel of 209 or higher.
[0026]
In the present invention, if the amplitude of the noise to be superimposed is 10, the range 190 to 211, which is a range larger than twice the amplitude of the noise, centering on the boundary where the pseudo contour is generated, is set as the input density value range for superimposing the noise. These two values are set in RAM (Random Access Memory). In this case, when the input density value is 190, when noise is superimposed, a value of 180 to 200 is output, and data of a density area of 201 or more that causes a pseudo contour as described above is not included. Further, when the input density value is 211, values from 201 to 221 are output by the noise superimposing process, and in this case as well, data of a light density area of 200 or less that causes a pseudo contour is not included. As a result, the generation of pseudo contours can be suppressed. That is, in the noise superimposing process, the range of the input density value is set to be larger than twice the amplitude of the noise, and the noise is superimposed on the image data.
[0027]
When noise is superimposed on a density area where pseudo contours are generated, the problem is that a gap occurs in the gradation in the boundary area between the area where noise is not superimposed and the area where noise is superimposed. In order to solve this problem, as described above, the data of the dark density area is not included in the vicinity of the lowest density of the noise superimposing area, and the data of the light density area is included in the vicinity of the highest density. The gradation is changed as smoothly as possible.
[0028]
Between the noise superimposition areas, data of a dark density area and data of a light density area are included, but there is no gap in gradation by superimposing an appropriate amount of noise.
[0029]
In addition, due to the characteristics of the image output device, pseudo contours and density unevenness may occur when noise is not superimposed, or density value areas with poor graininess may appear in a plurality of locations. A plurality of ranges may be set, and the degree of pseudo contour and density unevenness varies depending on each density value range. Therefore, the amplitude of noise may be set for each input density value range. For example, the noise amplitude can be set to 7 for the input density value range of 100 to 115, and the noise amplitude can be set to 10 for the input density value range of 190 to 211. The amplitude of noise superimposed on each input density value range is obtained as a value that does not cause pseudo contours and density unevenness, and does not output an image with poor graininess by performing noise superimposition processing on many types of images in advance. Just keep it.
[0030]
Further, when the image data is color image data, the tone correction curve (correction curve) is different for each color component, so that the range of the input density value that generates the pseudo contour differs for each color component, and the pseudo color varies depending on each color component. Since there may be no density value range that causes contours or density unevenness, an input density value range in which noise is superimposed and an amplitude of noise may be set for each color component.
[0031]
FIG. 4 is a flowchart showing noise superimposition processing by the image processing apparatus 13 of the present invention. First, in step s1, the noise superimposition processing unit 28 checks the input density value for each pixel of the image data to be input, and determines whether the input density value is n1 or more. If the input density value is n1 or more, the process proceeds to step s2, and if it is smaller than n1, the process proceeds to step s4. In step s2, it is determined whether or not the input density value is n2 or less. If the input density value is less than or equal to n2, the process proceeds to step s3, and if greater than n2, the process proceeds to step s4. In step s3, the noise superimposing processor 28 superimposes noise on the image data. At this time, noise is superimposed on a range of input density values larger than twice the amplitude of noise. In step s4, halftone output gradation processing is performed. In step s5, it is determined whether or not processing has been completed for all pixels. If not, processing returns to step s1 and each processing is repeated. If all the pixels have been completed, the noise superimposing process and the halftone output gradation process are ended.
[0032]
【The invention's effect】
As described above, according to the present invention, a pseudo contour is unlikely to occur at the boundary between the input density value range where noise is superimposed and other portions, which is visually preferable, and has high resolution and gradation. Recording can be performed.
[0033]
Further, according to the present invention, it is possible to apply noise superimposition processing suitable for each of a plurality of input density value ranges.
[0034]
Further, according to the present invention, it is possible to perform an appropriate amount of noise superimposition processing for each input density value range.
[0035]
Further, according to the present invention, it is possible to perform noise superimposition processing within a range of input density values appropriate for each color component.
[0036]
In addition, according to the present invention, a pseudo contour is hardly generated at the boundary between the input density value range where noise is superimposed and the other part, and it is more visually preferable, and a high-quality image with excellent resolution and gradation is formed. can do.
[Brief description of the drawings]
FIG. 1 is a block diagram illustrating a configuration of an image forming apparatus 11 including an image processing apparatus 13 according to an embodiment of the present invention.
FIG. 2 is a graph showing a reference correction curve 41 and a gradation correction curve 42 used for gradation correction processing.
FIG. 3 is a diagram illustrating an input density value range corresponding to a correction value range on a gradation correction curve;
FIG. 4 is a flowchart showing noise superimposition processing by the image processing apparatus 13 of the present invention.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 11 Image forming apparatus 12 Image input apparatus 13 Image processing apparatus 14 Image output apparatus 21 A / D conversion part 22 Shading correction part 23 Input gradation correction part 24 Color correction part 25 Image area separation process part 26 Black ink under color removal part 27 Spatial filter processing unit 28 Noise superimposition processing unit 29 Halftone output tone processing unit 30 Curve storage unit 31 Correction amount storage unit 32 Output conversion table storage unit 41 Reference correction curve 42 Tone correction curve

Claims (6)

In an image processing method for performing noise superimposition processing for superimposing noise on image data and halftone output gradation processing for performing halftone generation processing,
The noise superimposing process superimposes noise on image data in a predetermined input density value range,
The image processing method according to claim 1, wherein the range of the input density value is greater than twice the amplitude of noise centering on a boundary where image quality degradation occurs . The image processing method according to claim 1, wherein a plurality of ranges of the input density value are set. The image processing method according to claim 1 or 2, wherein the noise amplitude is set for each range of the input density value. The image processing method according to claim 1, wherein when the image data is color image data, the range of the input density value is set for each color component. An image processing apparatus comprising noise superimposing processing means for processing input image data using the image processing method according to claim 1. An image input device for reading image data to obtain image data;
An image processing apparatus according to claim 5;
An image forming apparatus comprising: an image output device that outputs processed image data.

Images