JP5162430B2 - Image processing apparatus and image processing method - Google Patents

Image processing apparatus and image processing method Download PDF

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JP5162430B2
JP5162430B2 JP2008314739A JP2008314739A JP5162430B2 JP 5162430 B2 JP5162430 B2 JP 5162430B2 JP 2008314739 A JP2008314739 A JP 2008314739A JP 2008314739 A JP2008314739 A JP 2008314739A JP 5162430 B2 JP5162430 B2 JP 5162430B2
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正裕 川島
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理想科学工業株式会社
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Description

  The present invention relates to an image processing apparatus, and more particularly to an image processing apparatus that converts image data in RGB format into CMYK format, performs multi-value pseudo gradation processing, and outputs the converted data.

  2. Description of the Related Art Conventionally, color printing apparatuses such as an ink jet method perform pseudo-halftone expression using binary values of dot on / off for each ink color. In this case, binary error diffusion processing or Dithering has been widely used. In binary error diffusion processing, in order to express a natural halftone only with binary output, every time one dot is processed, the error between the original value and the value after processing is calculated for the surrounding unprocessed dots. It is reflected in the processing, and the binarization processing of the dots is performed while diffusing the error.

In recent years, it has become possible to express dots in multiple values of three or more by using different sizes of dots or using high and low density inks for the same ink color. The print quality is improved.

When the dots are expressed in multiple values, pseudo halftone expression is performed by performing multi-value pseudo gradation processing such as multi-value error diffusion processing or multi-value dither method. For example, as described in Patent Document 1, there is a problem that a pseudo contour is generated when a density near a quantized value is output in multilevel error diffusion processing. Noise is added to data and quantization threshold.
JP 2000-270210 A

  In order to prevent false contours, when adding noise to image data, for example, it may be possible to add noise to each of CMYK constituting image data for printing, but in order to reduce resources. In addition, a luminance component is extracted from image data and noise is added to the luminance component.

  By the way, when the read original is copied and printed, smoothing processing, edge enhancement processing, background removal processing, and the like are performed on the read image data in order to improve printing quality. Here, the smoothing process is performed to prevent the occurrence of moire in the photo area of the copied document, and the edge enhancement process is performed to facilitate recognition of the character portion of the copied document, and the background removal process. This is a process to make it easier to read the characters of the copied document and reduce the ink consumption when the background density of the document is relatively high, such as newspaper, recycled paper, and colored paper. is there.

  Since these processes are image processing, if the timing of adding noise to prevent false contours is not considered, the effect of adding noise may be reduced or image processing may be adversely affected. The result will not be obtained.

  The present invention has been made in view of such circumstances, and in the case of performing image processing for improving print quality and noise addition for preventing pseudo contour generation by multi-value pseudo gradation processing, The purpose is to obtain a sufficient effect.

In order to solve the above-described problem, an image processing apparatus according to a first aspect of the present invention is an image processing apparatus that inputs RGB format image data and outputs CMYK format image data. A first color conversion unit that converts image data into image data in a color representation format including luminance data, a background removal processing unit that performs background removal processing on the luminance data, and luminance data after background removal processing A noise adding unit for adding a noise component, a second color converting unit for converting image data in a color expression format including luminance data to which the noise component has been added into image data in CMYK format, and the second color converting unit. and a multi-level pseudo gradation processing unit that performs multi-level pseudo gradation processing using the image data of the converted CMYK format by the noise adding unit, false contour generation anti according multilevel pseudo gradation processing It performs noise addition for, characterized in that it does not add noise for maximum and minimum values that can take the luminance data.

In this aspect, since noise components for preventing the occurrence of pseudo contours by multi-value pseudo gradation processing are added to the luminance data after the background processing, the accuracy of the background density in the background processing decreases due to the addition of noise. Can be prevented. For this reason, it is possible to sufficiently obtain the effects of background processing for improving the print quality and noise addition for preventing the occurrence of pseudo contours due to multi-value pseudo gradation .

Also, the noise adding unit does not add noise for maximum and minimum values that can take the luminance data, it is possible to prevent the base by noise adding resulting in recurrence. The multi-value pseudo gradation process can be a multi-value pseudo diffusion process, a multi-value dither process, or the like.

In order to solve the above problems, an image processing apparatus according to a second aspect of the present invention is an image processing apparatus that inputs RGB format image data and outputs CMYK format image data. A first color conversion unit that converts image data into image data of a color representation format including luminance data, a smoothing processing unit that performs a smoothing process on at least a part of the luminance data, and smoothing A noise addition unit for adding a noise component to the processed luminance data, a second color conversion unit for converting image data in a color representation format including the luminance data to which the noise component has been added into image data in CMYK format, A multi-value pseudo gradation processing unit that performs multi-value pseudo gradation processing using the CMYK format image data converted by the second color conversion unit, and the noise addition unit includes the multi-value pseudo gradation processing. By And performing noise addition for the false contour generation prevention.

In this aspect, the noise component is added to the luminance data after the smoothing process to prevent the occurrence of pseudo contours by the multi-value pseudo gradation process, so that the noise addition effect is lost by the smoothing process. Can be prevented. For this reason, it is possible to sufficiently obtain a smoothing process for improving the print quality and a noise addition effect for preventing the generation of pseudo contours by the multi-value pseudo gradation process. The multi-value pseudo gradation process can be a multi-value pseudo diffusion process, a multi-value dither process, or the like.

In order to solve the above-described problem, an image processing method according to a third aspect of the present invention is an image processing method for generating CMYK format image data by inputting RGB format image data. A first color conversion step for converting image data into image data in a color representation format including luminance data, a background removal step for performing background removal processing on the luminance data, and luminance data after the background removal processing A noise adding step for adding a noise component, a second color converting step for converting image data in a color expression format including luminance data to which the noise component has been added into image data in the CMYK format, and the second color converting step. It possesses a multi-level pseudo gradation step of performing multi-level pseudo gradation processing using the image data of the converted CMYK format, in, at the noise adding step Performs noise addition for the false contour generation prevention by multilevel pseudo gradation processing, characterized in that it does not add noise for maximum and minimum values that can take the luminance data.

In this aspect, since noise components for preventing the occurrence of pseudo contours by multi-value pseudo gradation processing are added to the luminance data after the background processing, the accuracy of the background density in the background processing decreases due to the addition of noise. Can be prevented. For this reason, it is possible to sufficiently obtain the effect of adding noise for preventing the generation of pseudo contours by the background processing and the multi-value pseudo gradation processing for improving the print quality .

Further, in the noise addition step, for maximum and minimum values that can take the luminance data does not adding noise, it is possible to prevent the by noise adding base will then reoccur. The multi-value pseudo gradation process can be a multi-value pseudo diffusion process, a multi-value dither process, or the like.

In order to solve the above-described problem, an image processing method according to a fourth aspect of the present invention is an image processing method for generating CMYK format image data by inputting RGB format image data. A first color conversion step of converting image data into image data of a color expression format including luminance data, a smoothing step of performing a smoothing process on at least a part of the luminance data, and the smoothing A noise addition step for adding a noise component to the processed luminance data; a second color conversion step for converting image data in a color representation format including the luminance data to which the noise component has been added into image data in CMYK format; have a, and the multi-level pseudo gradation step of performing multi-level pseudo gradation processing using the image data of the converted CMYK format in the second color conversion step, wherein Neu In adding step, and carrying out noise addition for the false contour generation prevention by multilevel pseudo gradation processing.

In this aspect, the noise component is added to the luminance data after the smoothing process to prevent the occurrence of pseudo contours by the multi-value pseudo gradation process, so that the noise addition effect is lost by the smoothing process. Can be prevented. For this reason, it is possible to sufficiently obtain a smoothing process for improving the print quality and a noise addition effect for preventing the generation of pseudo contours by the multi-value pseudo gradation process. The multi-value pseudo gradation process can be a multi-value pseudo diffusion process, a multi-value dither process, or the like.

In order to solve the above-mentioned problem, an image processing method according to a fifth aspect of the present invention is an image processing method for generating CMYK format image data by inputting RGB format image data. A first color conversion step of converting image data into image data of a color expression format including luminance data, a smoothing step of performing a smoothing process on at least a part of the luminance data, and the smoothing A background removal step for performing background removal processing on the luminance data after processing, a noise addition step for adding a noise component to the luminance data after the background removal processing, and luminance data to which the noise component is added A second color conversion step of converting the image data in the color representation format into image data in the CMYK format, and the CMYK format image converted in the second color conversion step. Possess a multi-level pseudo gradation step of performing multi-level pseudo gradation processing using chromatography data, and in the noise adding step performs noise addition for the false contour generation prevention by multilevel pseudo gradation processing, It is characterized in that no noise is added to the maximum value and the minimum value that the luminance data can take .

In this aspect, since noise components are added to the luminance data after the background processing and the smoothing processing to prevent the generation of pseudo contours by the multi-value pseudo gradation processing , the accuracy of the background density in the background processing by adding noise. Can be prevented from being reduced and the effect of noise addition being lost by the smoothing process. For this reason, it is possible to sufficiently obtain the effect of adding noise for preventing generation of pseudo contours by the background processing and smoothing processing for improving the print quality and the multi-value pseudo gradation processing. In addition, since noise is not added to the maximum value and minimum value that the luminance data can take, it is possible to prevent the background from being regenerated due to the addition of noise. The multi-value pseudo gradation process can be a multi-value pseudo diffusion process, a multi-value dither process, or the like.

  A photographic region determining step for determining a photographic region of the image data may be further provided, and the smoothing process in the smoothing step may be performed on the region determined as the photographic region. In this case, it may further include a character region determining step for determining a character region of the image data, and an edge enhancing step for performing edge enhancement processing on the region determined as the character region.

  According to the present invention, when image processing for improving print quality and noise addition for preventing pseudo contours by multi-value pseudo diffusion processing are performed, the respective effects can be sufficiently obtained.

  Embodiments of the present invention will be described with reference to the drawings. In the present embodiment, a case where multilevel error diffusion processing is used as multilevel pseudo gradation processing will be described as an example. FIG. 1 is a block diagram showing the configuration of a copying system including an image processing apparatus according to the present invention. As shown in the drawing, the copying system reads an image of a document and outputs RGB format image data, and inputs an RGB format image signal and outputs CMYK format image data. A processing apparatus 20 and an inkjet printing apparatus 30 that executes printing based on CMYK format image data are provided. The copying system can copy a document by printing with the ink jet printing apparatus 30 based on the image of the document read by the image reading device 10. The image processing apparatus 20 according to the present invention can be applied particularly effectively when image processing is performed on image data obtained by reading a document as in the present copying system. The present invention can also be applied when image processing is performed on image data generated by the apparatus.

  The image reading apparatus 10 includes a CCD as a light receiving element, a light source, a document table, a document table cover, a drive motor that scans the CCD, an AD converter that converts a CCD output signal into a digital signal, and the like. Image data of the original is obtained by irradiating the placed original with light and reading the reflected light with a CCD. In the present embodiment, it is assumed that image data to be output is in RGB format with 8 bits (256 gradations) for each color. However, the gradation of the image data output from the image reading apparatus 10 is not limited to 8 bits for each color.

  The image processing device 20 communicates with the image reading device 10 according to a predetermined protocol to receive RGB format image data, a controller 22 having a CPU, RAM, ROM, and the like, an ink jet printing device 30, and the like. And an output interface 23 for performing communication using a predetermined protocol and outputting CMYK format image data.

  The inkjet printing apparatus 30 uses, for example, four colors of ink of cyan, magenta, yellow, and black, and performs printing by ejecting ink droplets onto a printing sheet from a print head having a large number of nozzles. It is a printing device. The ink jet printing apparatus 30 can control the size of ink droplets to be ejected, and can express multiple values of three or more per dot for each ink color. In the present embodiment, it is possible to express with four gradations of large dot output, medium dot output, small dot output, and no output. For this reason, the image data output from the image processing apparatus 20 to the ink jet printing apparatus 30 indicates four gradation values for each dot of each ink color.

  FIG. 2 is a block diagram illustrating a functional configuration of the image processing apparatus 20. As shown in this figure, the image processing apparatus 20 includes an RGB data input unit 210, an RGB → YCbCr conversion unit 211, an image correction unit 212, a scaling processing unit 213, a background removal unit 214, a noise addition unit 215, and a YCbCr → RGB conversion. A unit 216, a gamma conversion unit 217, an RGB → CMYK conversion unit 218, a multilevel error diffusion unit 219, and a CMYK data output unit 220. These functional units can be realized in software or hardware by allowing the input interface 21, the controller 22, and the output interface 23 shown in FIG. 1 to process individually or cooperatively. . The YCbCr format is a format in which colors are expressed by Y (luminance) and CbCr (color difference).

  The RGB data input unit 210 performs processing for inputting image data in an 8-bit RGB format for each color output from the image reading apparatus 10. The RGB data input unit 210 may input image data from an information processing device such as a PC (not shown), a digital camera, or the like.

The RGB → YCbCr conversion unit 211 performs processing to convert RGB image data into YCbCr format, and separates the data into luminance (Y) data and color difference (CbCr) data. The conversion from the RGB format to the YCbCr format can be performed in accordance with, for example, “Equation 1”. However, you may convert into YCbCr format using another method. Further, as long as Y (luminance) can be acquired, other color expression formats may be used.

The image correction unit 212 performs image correction processing for improving the printing result when the read image data is copied and printed. The image correction process is performed on the luminance (Y) data. Specifically, a character area and a photographic area are determined from the input image data, smoothing processing is performed on the luminance data included in the photographic area to prevent the occurrence of moire, and the luminance data included in the character area is converted into luminance data. On the other hand, edge emphasis processing is performed to make it easy to recognize characters. Therefore, the image correction unit 212 includes a character area / photo area determination unit 221, a smoothing unit 222, and an edge enhancement unit 223.

  The character area / photo area determination unit 221 determines a character area and a photo area in the image data of the document based on the luminance data. A conventional technique can be used as an algorithm for determining a character area and a photograph area. For example, an area having a large density difference and containing many character components such as vertical bars and horizontal bars can be determined as a character area, and an area having a smooth density change and a large area can be determined as a photographic area. The smoothing unit 222 smoothes the luminance data of the area determined as the photographic area. The smoothing can be performed by using a conventional technique, for example, by calculating a weighted average of the luminance value of each pixel with surrounding pixels. The edge emphasizing unit 223 performs edge emphasis on the luminance data of the area determined as the character area. Edge enhancement can be performed using a conventional technique, for example, using a Laplacian filter. However, smoothing processing, edge enhancement processing, or the like may be performed uniformly without performing region determination according to the type of document.

  The scaling processing unit 213 can receive an instruction for magnification copying from the user, and performs magnification processing at a specified magnification when the magnification copying is instructed. For example, when the scaling process is performed after image correction and before the background removal, the image is once converted into the RGB format, the scaling is performed using the RGB data, and the image data after the scaling is converted into the YCbCr format again. . However, the scaling process may be performed at another timing.

  The background removal unit 214 performs processing for removing the background color of the document based on the luminance data. The background removal process is used to make it easier to read the characters in the copied document and reduce ink consumption when the background density of the document is relatively high, such as newspapers, recycled paper, and colored paper. This is a widely used process. The background removal process can be performed using a conventional technique. For example, a histogram can be created based on the luminance data, the background density can be estimated from the shape, and the luminance data area corresponding to the background density can be removed.

  The noise adding unit 215 performs processing for adding noise to the luminance data. By adding noise to the luminance data, it is possible to prevent the occurrence of a pseudo contour due to the multilevel error diffusion process. The addition of noise can be performed, for example, by adding positive and negative noise values randomly generated within a predetermined value to the luminance data.

  In the present embodiment, by adding noise to the luminance data, it is possible to reduce the resource usage of the image processing apparatus 20 compared to the case of adding noise to each of the CMYK data. Furthermore, in this embodiment, the background removal process is not performed after the noise is added, but the noise is added to the luminance data after the background is removed. This prevents the background estimation in the background removal processing from becoming inaccurate due to the addition of noise. Further, by adding noise to the luminance data after the smoothing process, the effect of adding the noise is prevented from being lost by the smoothing process.

  When noise is added to the luminance data after the background removal processing, noise is added to the data of the luminance value 255 and the luminance value 0 in order to prevent the reproduction of the background color due to the added noise. Do not do it.

The YCbCr → RGB conversion unit 218 performs processing for converting image data in the YCbCr format into the RGB format. At this time, image correction is performed by the image correction unit 212, the background is removed by the background removal unit 214, and the luminance data to which noise is added by the noise addition unit 215 is converted into RGB format. The conversion from the YCbCr format to the RGB format can be performed according to, for example, “Equation 2”. However, you may convert into RGB format using another method.

The gamma conversion unit 217 performs gamma conversion processing that matches the RGB format image data with the output characteristics of the inkjet printing apparatus 30.

  The RGB → CMYK conversion unit 218 performs processing to convert RGB image data into 8-bit CMYK image data for each color. The conversion from the RGB format to the CMYK format can be performed using, for example, a lookup table in which the correspondence between the RGB representative values and the CMYK values is recorded in advance.

  The multi-level error diffusion unit 219 artificially represents halftones of CMYK format image data expressed in 8 bits for each color with 4 gradations of large dot output, medium dot output, small dot output, and no output for each color. In order to achieve this, multilevel error diffusion processing is performed. A conventional technique can be used for the multi-level error diffusion processing. In summary, in the four-level multi-level error diffusion processing, four quantized values that distinguish large dot output, medium dot output, small dot output, and no output are defined as dot outputs (for example, 255 for large dots). , Medium dots are 170, small dots are 85, no output is 0, etc.) Quantization thresholds are defined for each of the three sections (the quantization threshold can be set to an intermediate value of each section, for example). Then, assignment of dot output is determined based on each CMYK value of the first pixel of interest (for example, when the CMYK value of the pixel of interest is in a large dot and medium dot interval, it is compared with the quantization threshold of that interval, Whether it is dot or medium dot). After that, the process of determining the assignment of the dot output of the next pixel of interest by diffusing the error between the CMYK value of the pixel and the determined quantized value by weighting the CMYK value of the surrounding pixels and shifting the pixel is performed. By repeating, multi-value error diffusion processing can be performed.

  The CMYK data output unit 220 performs a process for outputting image data represented by a CMYK multi-value for each dot to the inkjet printing apparatus 30 by performing multi-value error diffusion processing. The CMYK data output unit 220 may store the image data in a file or output the image data to an apparatus other than the inkjet printing apparatus 30.

  Next, the operation of the image processing apparatus 20 in the present embodiment will be described with reference to the flowchart of FIG.

  In the image processing device 20, first, the RGB data input unit 210 inputs RGB image data read by the image reading device 10 (S 101). Then, the RGB → YCbCr conversion unit 211 separates the input RGB format image data into luminance (Y) data and color difference (CbCr) data (S102).

  Next, using the separated luminance data, the character area / photo area determination unit 221 determines a character area and a photo area in the image data (S103). For the area determined to be a photographic area, the smoothing unit 222 performs a smoothing process on the luminance data (S104), and for the area determined to be a character area, the edge enhancement unit 223 converts the luminance data to the luminance data. Then, edge enhancement processing is performed (S105).

The background removal unit 214 performs background removal processing using the luminance data subjected to smoothing and edge enhancement (S106). The background removal process can be performed, for example, according to the procedure shown in the flowchart of FIG. That is, a histogram indicating the distribution of luminance values is created using the luminance data (S1061). Then, the background density is estimated according to a predetermined standard (S1062). A conventional technique can be used for estimating the background density. For example, with a simple method, the maximum value on the side with the highest luminance in the histogram can be estimated as the background density. When the background density is estimated, pixels having a luminance value equal to or less than the estimated background density are converted into the maximum brightness value, thereby removing the background pixels (S1063).

  When the background removal processing (S106) is completed, the noise adding unit 215 adds noise to the luminance data (S107). Thus, in this embodiment, noise is added to the luminance data after the background removal. As described above, in order to prevent the reappearance of the background color due to the added noise, noise is added to the luminance value 255 and the luminance value 0 which are the maximum and minimum values that the luminance data can take. Do not do it.

  Then, the YCbCr → RGB conversion unit 216 performs RGB conversion using the luminance (Y) data to which noise is added and the color difference (CbCr) data separated in the YCbCr conversion process (S102) (S108).

  If the user has instructed scaling, for example, as shown in FIG. 5, the scaling process can be performed between the background removal process (S106) and the noise addition process (S107). That is, RGB conversion is performed using the luminance data after the background removal process (S106) and the color difference (CbCr) data separated in the YCbCr conversion process (S102) (S201), and the RGB format image data is The instructed magnification is changed (S202). Thereafter, the RGB format image data is converted again to the YCbCr format (S203), and noise is added to the luminance data (S107). Then, the YCbCr → RGB conversion unit 216 performs RGB conversion using the luminance (Y) data to which noise is added and the color difference (CbCr) data separated in the YCbCr conversion process (S203) (S108). do it.

  When RGB conversion is performed, the gamma conversion unit 217 performs gamma conversion processing on the image data converted into the RGB format in accordance with the output characteristics of the inkjet printing apparatus 30 (S109). Next, the RGB → CMYK conversion unit 218 converts the 8-bit RGB image data of each color after the gamma conversion processing into an 8-bit CMYK format of each color (S110).

  Then, the multi-level error diffusion unit 219 performs multi-level error diffusion processing in order to display the 8-bit CMYK format image data of each color in halftone with 4 gradations of each CMYK color (S111). In the present embodiment, image data in CMYK format with 8 bits for each color has noise added to the luminance data in step S107, so that it is possible to prevent the occurrence of pseudo contours due to multilevel error diffusion processing.

  The CMYK data output unit 220 outputs the CMYK data in which each dot is expressed by four gradations for each ink color by the multi-value error diffusion processing (S112), and the image reading device 10 reads the CMYK data. The original is copied and printed.

In the above embodiment, the multi-value expression is performed by controlling the dot size to a plurality of sizes. However, the present invention uses a high-density ink and a low-density ink for the same color. The present invention can also be applied to a case where multilevel error diffusion processing is performed in a system that performs expression. In this case, noise may be added to the luminance data after the smoothing process and the background process and before the multilevel error diffusion process.
In the above embodiment, the case where multi-value error diffusion processing is used as multi-value pseudo gradation processing has been described as an example. However, the present invention is similarly applied to the case where multi-value dither processing is used. can do. In multi-value dither processing (for example, FM screen multi-value dither processing), there are a plurality of threshold tables called dither matrices. When multi-value dither processing is applied to a gradation input image, multi-value dither processing is performed. Similar to the error diffusion process, a region having the same value near the threshold value is generated as a pseudo contour. Even in such a case, the present invention can be effectively applied. In this case, a multi-level dither processing unit may be provided instead of the multi-level error diffusion unit 219 in FIG. 2, and the multi-level error diffusion step in the process (S111) in FIG. 3 may be replaced with a multi-level dither processing step.

1 is a block diagram illustrating a configuration of a copying system including an image processing apparatus. It is a block diagram which shows the function structure of an image processing apparatus. It is a flowchart explaining operation | movement of an image processing apparatus. It is a flowchart which shows an example of a background removal process. It is a flowchart which shows an example of the procedure of a scaling process.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... Image reading apparatus 20 ... Image processing apparatus 21 ... Input interface 22 ... Controller 23 ... Output interface 30 ... Inkjet printing apparatus 210 ... RGB data input part 211 ... RGB-> YCbCr conversion part 212 ... Image correction part 213 ... Scaling processing part
2 14 ... Background removal section 215 ... Noise addition section 216 ... YCbCr → RGB conversion section 217 ... Gamma conversion section 218 ... RGB → CMYK conversion section 219 ... Multi-level error diffusion section 220 ... CMYK data output section 221 ... Photo area determination section 222 ... Smoothing unit 223 ... Edge enhancement unit

Claims (7)

  1. An image processing apparatus for inputting image data in RGB format and outputting image data in CMYK format,
    A first color conversion unit for converting the image data in the RGB format into image data in a color expression format including luminance data;
    A background removal processing unit that performs background removal processing on the luminance data;
    A noise adding unit for adding a noise component to the luminance data after the background removal processing;
    A second color conversion unit that converts image data in a color expression format including luminance data to which a noise component has been added into image data in CMYK format;
    A multi-value pseudo gradation processing unit that performs multi-value pseudo gradation processing using image data in the CMYK format converted by the second color conversion unit ,
    The noise adding unit performs noise addition for preventing pseudo contour generation by multi-value pseudo gradation processing, and does not add noise to the maximum value and the minimum value that can be taken by luminance data. apparatus.
  2. An image processing apparatus for inputting image data in RGB format and outputting image data in CMYK format,
    A first color conversion unit for converting the image data in the RGB format into image data in a color expression format including luminance data;
    A smoothing processing unit that performs a smoothing process on at least a part of the luminance data;
    A noise adding unit for adding a noise component to the luminance data after the smoothing process;
    A second color conversion unit that converts image data in a color expression format including luminance data to which a noise component has been added into image data in CMYK format;
    A multi-value pseudo gradation processing unit that performs multi-value pseudo gradation processing using image data in the CMYK format converted by the second color conversion unit ,
    The image processing apparatus according to claim 1, wherein the noise adding unit performs noise addition for preventing generation of a pseudo contour by multi-value pseudo gradation processing .
  3. The image processing apparatus according to claim 1, wherein:
    The multi-value pseudo gradation processing performed by the multi-value pseudo gradation processing unit is either multi-value error diffusion processing or multi-value dither processing.
  4. An image processing method for inputting image data in RGB format and generating image data in CMYK format,
    A first color conversion step of converting the RGB format image data into color representation format image data including luminance data;
    A background removal step for performing background removal processing on the luminance data;
    A noise addition step of adding a noise component to the luminance data after the background removal processing;
    A second color conversion step of converting image data in a color expression format including luminance data to which a noise component has been added into image data in CMYK format;
    Have a, and the multi-level pseudo gradation step of performing multi-level pseudo gradation processing using the image data of the converted CMYK format in the second color conversion step,
    In the noise addition step, image processing is performed in which noise is added to prevent pseudo contour generation by multi-value pseudo gradation processing, and noise is not added to the maximum value and the minimum value that can be taken by the luminance data. Method.
  5. An image processing method for inputting image data in RGB format and generating image data in CMYK format,
    A first color conversion step of converting the RGB format image data into color representation format image data including luminance data;
    A smoothing step of performing a smoothing process on at least a part of the luminance data;
    Adding a noise component to the luminance data after the smoothing process;
    A second color conversion step of converting image data in a color expression format including luminance data to which a noise component has been added into image data in CMYK format;
    Have a, and the multi-level pseudo gradation step of performing multi-level pseudo gradation processing using the image data of the converted CMYK format in the second color conversion step,
    An image processing method characterized in that, in the noise adding step, noise is added to prevent generation of a pseudo contour by multi-value pseudo gradation processing .
  6. An image processing method for inputting image data in RGB format and generating image data in CMYK format,
    A first color conversion step of converting the RGB format image data into color representation format image data including luminance data;
    A smoothing step of performing a smoothing process on at least a part of the luminance data;
    A background removal step for performing background removal processing on the luminance data after the smoothing processing;
    A noise addition step of adding a noise component to the luminance data after the background removal processing;
    A second color conversion step of converting image data in a color expression format including luminance data to which a noise component has been added into image data in CMYK format;
    Have a, and the multi-level pseudo gradation step of performing multi-level pseudo gradation processing using the image data of the converted CMYK format in the second color conversion step,
    In the noise addition step, image processing is performed in which noise is added to prevent pseudo contour generation by multi-value pseudo gradation processing, and noise is not added to the maximum value and the minimum value that can be taken by the luminance data. Method.
  7. An image processing method according to any one of claims 4 to 6 ,
    The image processing method characterized in that the multi-value pseudo gradation processing in the multi-value pseudo gradation step is either multi-value error diffusion processing or multi-value dither processing.
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