JP2007166563A - Image processing apparatus and image processing method, image processing program, and storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus and image processing method in which a certain degree of color conversion accuracy can be kept and further, color space conversion processing can be performed at high speed. <P>SOLUTION: A color image represented in a first color space is divided into blocks for each color component by a block dividing section 1, and an average value of color components is calculated for each block by an average value calculation section 2. Color space conversion is then performed on that average value into a block average value in a second color space by a color conversion section 3. This color space conversion is performed only on the average value of blocks, so that throughput is remarkably decreased, and processing can be accelerated. On the other hand, a feature amount in each pixel is calculated from the average value of color components for each block and pixel values of the blocks by a feature amount calculation section and in accordance with the calculated feature amount for each pixel, the block average value on which color space conversion is performed, is corrected by a correction section 5 and defined as a value for each pixel in the second color space, thereby preventing color conversion accuracy from being reduced in pixels of colors other than the block average value. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing technique for performing color space conversion processing on a color image.

  Conventionally, techniques for performing conversion processing between different color spaces have been used. For example, in a copying machine or a printer, an image expressed in a color space such as RGB or YCbCr is converted into an image expressed in a CMYK color space, and an image is formed using color materials of the respective color components. . As a representative color space conversion processing method, there is a method using an N-dimensional lookup table and interpolation (hereinafter abbreviated as DLUT).

  In the conventional color space conversion process, the color space conversion process is performed for all the pixels in the image. In recent years, various methods for improving color conversion accuracy have been applied, the amount of processing has increased, and the processing time for color space conversion processing has become longer. For example, in the above-described DLUT, for a color space conversion process of one pixel, several table values are read and N-dimensional interpolation calculation is performed. If this process is performed for all the pixels in the image, there is a problem that a considerable amount of processing is required and processing time is required. Therefore, an improvement in processing speed is required by shortening the processing time.

  For example, in Japanese Patent Application Laid-Open No. H11-228707, when performing color conversion with reference to the lookup table, a grid in the lookup table is obtained by performing gradation conversion in the pre-gradation number conversion unit in the previous stage. The value is converted into a point, the converted value is taken out with reference to the lookup table, and is converted into a desired number of gradations by a post-gradation number conversion unit at a later stage. As a result, the lookup table reference is reduced and the interpolation process is not performed. However, with such a configuration, only the number of gradations registered in the lookup table can be obtained, and color conversion cannot be performed with high accuracy. This method also performs pre-gradation conversion, lookup table lookup, and post-gradation conversion for all pixels in the image, so the amount of processing is large and the processing speed is increased. I could not.

  As another technique similar to the present invention, there is a block compression technique for compressing an image. A typical example is GBTC (Generalized Block Truncation Coding) as described in Patent Document 2. This technique blocks an image, calculates an average value for each block, quantizes the difference from the average value, and compresses and encodes the average value together with the average value. This technique is an image compression technique as described above, and is a technique different from the color conversion technique.

JP-A-7-30772 Japanese Patent Laid-Open No. 9-9069

  The present invention has been made in view of the above-described circumstances, and an object thereof is to provide an image processing apparatus and an image processing method capable of performing color space conversion processing at high speed while maintaining a certain degree of color conversion accuracy. Is. It is another object of the present invention to provide an image processing program for causing a computer to execute such a function of the image processing apparatus or an image processing method, and a storage medium storing the image processing program.

  The present invention relates to an image processing apparatus and an image processing method for color-converting a color image expressed in a first color space into an image expressed in a second color space, the image processing method expressing the color image expressed in the first color space. The color image is divided into blocks for each color component, an average value of each color component is calculated for each block, and the average value is converted to a block average value in the second color space. On the other hand, the feature amount in each pixel is calculated from the average value of the color components for each block and each pixel value of the block, and the block average value subjected to color space conversion is corrected based on the calculated feature amount of each pixel. It is characterized by the value of each pixel in the color space.

The feature amount is a difference between the average value of the color components for each block and each pixel value of the block, the difference is multiplied by the weight for each color component of the second color space, and each color component of the block average value is calculated. By adding each, the value of each pixel in the second color space can be obtained. Especially when the first color space is the L ^* a ^* b ^* color space, calculates the difference between the L ^* component as the feature amount, the color component of the differential to a second color space for the L ^* component of each pixel Each weight component is multiplied, and each color component of the block average value is added to obtain the value of each pixel in the second color space. Alternatively, it is configured to obtain the value of each pixel in the second color space by approximately color-converting the difference of each color component into the difference of the second color space and adding it to each color component of the block average value. May be.

  Furthermore, the pixel value in the second color space obtained by the above-described configuration can be configured to perform enhancement processing according to the degree of contrast. The difference between the maximum value and the minimum value of the difference can be determined. Furthermore, the function for performing enhancement processing can be changed according to the degree of contrast at that time.

  According to the present invention, since the color space conversion process is performed on the average value of the block, the processing amount can be significantly reduced as compared with the case where the color space conversion process is performed on all the pixels of the block. Color space conversion processing can be performed at high speed. In addition, as the value of each pixel in the second color space after color space conversion, the block average value in the second color space is not used as it is, but the block average value is determined according to the feature amount of each pixel in the first color space. By correcting the above, there is an effect that a certain degree of color conversion accuracy can be maintained.

FIG. 1 is a block diagram showing a first embodiment of the present invention. In the figure, 1 is a blocking unit, 2 is an average value calculation unit, 3 is a color conversion unit, 4 is a feature amount calculation unit, and 5 is a correction unit. Here, the input image is assumed to be an image expressed in the L ^* a ^* b ^* color space, and the output image is assumed to be an image expressed in the CMYK color space. Of course, the color space is not limited to this example, and color space conversion processing between other color spaces such as RGB color space and YCbCr may be performed.

  The blocking unit 1 blocks the input image for each color component. The size of the block can be arbitrarily determined in advance, but in this example, it is illustrated as 4 × 4 pixels as an example.

  The average value calculation unit 2 calculates the average value of each color component for each block passed from the blocking unit 1.

  The color conversion unit 3 performs color space conversion on the average value of each color component of each block calculated by the average value calculation unit 2 into a block average value in the second color space. As the color conversion unit 3, a known color conversion method can be applied. For example, the above-described DLUT can be used. The color conversion unit 3 performs the color space conversion process only for the average color of the pixels in each block, so that it is markedly different from the conventional case where the color space conversion process is performed for each pixel. The amount of processing is small, and processing can be performed at high speed. In this example, since the block size is 4 × 4 pixels, the processing amount and processing time are 1/16.

The feature amount calculation unit 4 calculates the feature amount in each pixel from the average value of the color components for each block calculated by the average value calculation unit 2 and each pixel value in the block. Here, the difference between the average value of the L ^* component of the block and the value of L ^* of each pixel of the block is calculated as the feature amount. Of course, the feature amount is not limited to the difference between the L ^* components, and a difference for each component may be used as in an embodiment described later, or a feature amount other than the difference may be calculated.

The correction unit 5 corrects the block average value converted by the color conversion unit 3 based on the feature amount of each pixel in the block calculated by the feature amount calculation unit 4, and the value of each pixel in the second color space To do. In this example, the difference (d _ij ) calculated as the feature quantity for each pixel by the feature quantity calculation unit 4 is multiplied by the weight (Wc, Wm, Wy, Wk) for each color component in the second color space, and color conversion is performed. Each color component of the block average values (Cave, Mave, Yave, Kave) obtained in the section 3 is added to obtain the value of each pixel in the second color space. That is, when the value of the pixel of the second color space to be obtained is (C _ij , M _ij , Y _ij , K _ij ) (i = 1 to 4, j = 1 to 4),
C _ij = Cave + Wc · d _ij
M _ij = Mave + Wm · d _ij
Y _ij = Yave + Wy · d _ij
K _ij = Kave + Wk · d _ij
Thus, the block average value is corrected to obtain the pixel value of the second color space.

Here, the difference d _ij is a difference with respect to the L ^* component, and is not a difference with respect to the respective color components of C, M, Y, and K, but by correcting the brightness direction indicated by the L ^* component, The color change between each pixel in the block is approximated to suppress a decrease in color conversion accuracy. The contribution of the brightness (L ^* ) component to each color component in the second color space is the weight (Wc, Wm, Wy, Wk). The weights (Wc, Wm, Wy, Wk) may be constants or functions. If the weight is too large, the difference from the color expressed in the first color space will be large, so that it should be set to an appropriate value so that the difference from the original color does not become large. desirable.

  In this way, by arranging the blocks composed of the pixels of the second color space output from the correction unit 5, it is possible to obtain an output image after the color space conversion processing. As described above, the color space conversion process can be performed at high speed, and the correction unit 5 corrects the block average value for each pixel, thereby suppressing a decrease in color conversion accuracy. In this example, since the block size is small, the color of the block average value is visually recognized as the entire image, and even if the color of each pixel in the block is slightly different, the image as a whole is not affected so much and deterioration of image quality is suppressed. be able to.

  FIG. 2 is a block diagram showing a second embodiment of the present invention. In the figure, the same parts as those in FIG. This 2nd Embodiment shows another example of the feature-value calculation part 4 and the correction part 5 in the above-mentioned 1st Embodiment.

  In this example, the feature amount calculation unit 4 calculates the difference between the color component of each pixel in the block and the average value for each color component in the first color space, and sets it as the feature amount.

  The correction unit 5 performs color conversion on the difference for each color component in the first color space calculated by the feature amount calculation unit into a difference for each color component in the second color space. This color conversion may be performed by a simple function or table and does not require accuracy. Then, the color-converted difference and the block average value output from the color conversion unit 3 are added to obtain the value of each pixel in the second color space.

  In the configuration according to the second embodiment, since the correction unit 5 performs simple color conversion on the difference from the average value, the color reproducibility within the block can be improved. Therefore, the color conversion accuracy of the output image can be improved as compared with the first embodiment described above.

  FIG. 3 is a block diagram showing a third embodiment of the present invention. In the figure, the same parts as those in FIG. Reference numeral 6 denotes an enhancement degree calculation unit, and 7 denotes an enhancement processing unit. In the third embodiment, an example in which enhancement processing is appropriately performed on values in the second color space output from the correction unit 5 is shown.

The enhancement degree calculation unit 6 calculates the degree of contrast. As the degree of contrast, the difference between the maximum value and the minimum value of the L ^* values of the pixels in the block can be obtained.

  The enhancement processing unit 7 performs enhancement processing on the value of each pixel in the second color space output from the correction unit 5 in accordance with the degree of contrast calculated by the enhancement degree calculation unit 6. The enhancement processing can be performed using a function, but the function used at this time is changed depending on the degree of contrast. Thereby, it is possible to perform enhancement processing according to the degree of contrast.

FIG. 4 is an explanatory diagram of an example of switching of functions used for the enhancement processing. 4A, as described above, the pixel having the largest L ^* value in the block is Max, the smallest pixel is Min, and the difference is calculated by the enhancement degree calculation unit 6 as the degree of contrast. When the absolute value of the degree of contrast is equal to or less than the predetermined threshold value TH, for example, a function that outputs the input as it is as shown in FIG. When the absolute value of the degree of contrast is larger than a predetermined threshold value TH, for example, a function as shown in FIG. 4B is used to enhance the contrast. As a result, the portion where the degree of contrast is small is not emphasized, and the portion where the degree of contrast is large is emphasized. The portion with a high degree of contrast is an edge portion in many cases, and the edge can be emphasized by performing a process of enhancing the contrast in a block where the edge portion exists. Such enhancement processing can also be performed using the values of the blocked pixels. Since the color conversion is performed using the average value of the blocks as described above, the blur caused by this can be reduced by the enhancement process.

  In FIG. 3, the configuration in which the enhancement degree calculation unit 6 and the enhancement processing unit 7 are added to the first embodiment is illustrated, but it goes without saying that the configuration can be applied to the second embodiment. .

  FIG. 5 is an explanatory diagram of an example of a computer program and a storage medium storing the computer program when the function of the image processing apparatus or the image processing method of the present invention is realized by the computer program. In the figure, 11 is a program, 12 is a computer, 21 is a magneto-optical disk, 22 is an optical disk, 23 is a magnetic disk, 24 is a memory, 31 is a magneto-optical disk apparatus, 32 is an optical disk apparatus, and 33 is a magnetic disk apparatus.

  A part or all of the configuration described as each of the above-described embodiments and modifications thereof can be realized by a program 11 that can be executed by a computer. When implemented by the program 11, the program 11 and data used by the program can be stored in a computer-readable storage medium. A storage medium is a signal format that causes a state of change in energy such as magnetism, light, electricity, etc. according to the description of a program to a reader provided in the hardware resources of a computer. Thus, the description content of the program can be transmitted to the reading device. For example, there are a magneto-optical disk 21, an optical disk 22 (including a CD and a DVD), a magnetic disk 23, a memory 24 (including an IC card, a memory card, and the like). Of course, these storage media are not limited to portable types.

  By storing the program 11 in these storage media and mounting these storage media in, for example, the magneto-optical disk device 31, the optical disk device 32, the magnetic disk device 33, or a memory slot or interface (not shown) of the computer 12, The program 11 is read from the computer, and the function of the image processing apparatus or the image processing method of the present invention can be executed. Alternatively, a storage medium may be mounted or built in the computer 12 in advance, and the program 11 may be transferred to the computer 12 via a network, for example, and the program 11 may be stored and executed on the storage medium. Of course, some functions may be configured by hardware, or all may be configured by hardware.

It is a block diagram which shows the 1st Embodiment of this invention. It is a block diagram which shows the 2nd Embodiment of this invention. It is a block diagram which shows the 3rd Embodiment of this invention. It is explanatory drawing of an example of the switch of the function used for an emphasis process. FIG. 3 is an explanatory diagram of an example of a computer program and a storage medium storing the computer program when the function of the image processing apparatus or the image processing method of the present invention is realized by the computer program.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Blocking part, 2 ... Average value calculation part, 3 ... Color conversion part, 4 ... Feature-value calculation part, 5 ... Correction part, 6 ... Enhancement degree calculation part, 7 ... Enhancement processing part, 11 ... Program, 12 ... Computer, 21 ... Magneto-optical disk, 22 ... Optical disk, 23 ... Magnetic disk, 24 ... Memory, 31 ... Magneto-optical disk device, 32 ... Optical disk device, 33 ... Magnetic disk device.

Claims (18)

  Blocking means for blocking the color image expressed in the first color space for each color component, average value calculating means for calculating an average value of each color component for each block, and average of each color component for each block Color conversion means for color space converting a value to a block average value in a second color space, and feature quantity calculation means for calculating a feature quantity at each pixel from the average value of the color components for each block and each pixel value of the block And a correction unit that corrects the block average value converted by the color conversion unit based on the feature amount of each pixel calculated by the feature amount calculation unit to obtain a value of each pixel in the second color space. A featured image processing apparatus.   The image processing apparatus according to claim 1, wherein the feature amount calculation unit calculates a difference between an average value of color components for each block and each pixel value of the block as a feature amount of each pixel.   The correction unit multiplies the difference calculated as the feature amount for each pixel by the feature amount calculation unit by a weight for each color component of the second color space, and each color of the block average value obtained by the color conversion unit The image processing apparatus according to claim 2, wherein the components are added to obtain the value of each pixel in the second color space. First color space is an L ^* a ^* b ^* color space, the feature amount calculating means calculates the difference between the average value of the L ^* component and the L ^* component of each pixel in the block for the L ^* component The correction means multiplies the difference for each L ^* component of each pixel by the weight for each color component of the second color space, and sets each color component of the block average value obtained by the color conversion means, respectively. The image processing apparatus according to claim 2, wherein the value of each pixel in the second color space is obtained by addition.   The feature amount calculating unit calculates a difference between each color component in the first color space for each block and an average value of each color component for each pixel as a feature amount, and the correction unit calculates each color in the first color space. The component difference is approximately color-converted to a difference in the second color space, and each color component of the block average value is added to the difference in the second color space, and the value of each pixel in the second color space The image processing apparatus according to claim 1, wherein:   Furthermore, an enhancement degree calculating means for calculating the degree of contrast, and an enhancement process for the value of each pixel in the second color space output from the correction means according to the degree of contrast calculated by the enhancement degree calculation means. 6. The image processing apparatus according to claim 1, further comprising an emphasis unit that performs the enhancement.   The image processing apparatus according to claim 6, wherein the enhancement degree calculation unit sets a difference between a maximum value and a minimum value of differences in the block as a degree of contrast.   The image processing apparatus according to claim 6, wherein the enhancement unit changes a function used when performing the enhancement process according to the degree of contrast.   The color image expressed in the first color space is blocked for each color component by the blocking unit, the average value of each color component is calculated for each block by the average value calculating unit, and the average value of each color component for each block Is converted to a block average value in the second color space by the color conversion means, and a feature amount in each pixel is calculated by the feature amount calculation means from the average value of the color components for each block and each pixel value of the block. An image processing method, wherein the block average value is corrected by a correction means based on the calculated feature amount of each pixel to obtain a value of each pixel in the second color space.   The image processing method according to claim 9, wherein a difference between an average value of color components for each block and each pixel value of the block is calculated as the feature amount.   The correction of the block average value by the feature amount of each pixel is performed by multiplying the difference for each pixel calculated as the feature amount by the weight for each color component of the second color space, and adding each color component of the block average value, respectively. The image processing method according to claim 10, wherein the image processing method is performed. First color space is an L ^* a ^* b ^* color space, as the feature amount, calculates a difference between the average value of the L ^* component and the L ^* component of each pixel in the block for the L ^* component, The difference between the L ^* components of each pixel is multiplied by the weight for each color component in the second color space, and each color component of the block average value is added to obtain the value of each pixel in the second color space. The image processing method according to claim 10.   For each color component in the first color space as the feature amount, a difference from the average value of each color component is calculated for each pixel, and the difference between the calculated color components in the first color space is approximately second. The color conversion to a difference in the color space of the second color space is performed, and each color component of the block average value is added to the difference in the second color space to obtain the value of each pixel in the second color space. 10. The image processing method according to 9.   The contrast level is calculated by an enhancement level calculation unit, and the enhancement process is performed by the enhancement unit for the value of each pixel in the second color space after correction according to the contrast level. The image processing method according to claim 13.   The image processing method according to claim 14, wherein a difference between a maximum value and a minimum value in the block is calculated as the degree of contrast.   The image processing method according to claim 14, wherein a function used when performing the enhancement processing is changed according to the degree of the contrast.   9. An image processing program for performing color conversion processing for converting a color image expressed in a first color space into an image expressed in a second color space on a computer. An image processing program for causing a computer to execute the function of the image processing apparatus according to claim 1 or the image processing method according to any one of claims 9 to 16.   A computer-readable storage medium storing an image processing program for causing a computer to execute a color conversion process for converting a color image expressed in a first color space into an image expressed in a second color space. An image processing program for causing a computer to execute the function of the image processing device according to any one of claims 1 to 8 or the image processing method according to any one of claims 9 to 16 is stored. A computer-readable storage medium.

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