JP2005143008A - Image processor, image processing method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To prevent a high-saturation color from being saturated when a dynamic range of an image is compressed. <P>SOLUTION: An image analysis unit 2 analyzes an image S0 and sets dynamic range compressibility P0, and a compression table generation unit 3 generates a compression table T0. A color saturation calculation unit 4 calculates the color saturation C of each of pixels of the image S0, and a color saturation correction factor calculation unit 5 calculates a color saturation correction factor f(C) for correcting a correction value to reduce the correction value for compressing the dynamic range as the color saturation C is high. A compression processing unit 6 refers to the compression table T0 to calculate the correction value for correcting pixel values of the pixels, corrects the correction value according to the color saturation correction factor f(C) and adds the corrected correction value to the pixel values of the pixels, so that the dynamic range of the image S0 is compressed and processed image data S1 are obtained. An image output unit 7 prints out the processed image data S1. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an image processing apparatus and method for compressing a dynamic range of a color image so that it falls within the dynamic range of a reproduction apparatus such as a printer that outputs the color image, and a program for causing a computer to execute the image processing method. It is.

  Conventionally, an image obtained by photoelectrically reading an image acquired by photographing a subject with an imaging device such as a digital camera, an image recorded on a photographic film such as a negative film or a reversal film, or a printed matter. Is reproduced on a reproducing apparatus such as a printer. In this way, when the image is reproduced on the reproduction device, in order to prevent the bright portion and / or the dark portion on the image from being crushed, the image is set so that the dynamic range of the image is within the dynamic range of the reproduction device. The dynamic range of compression has been done.

In such a dynamic range compression method, a filtering process using a low-pass filter is performed on an image to create a blurred image representing only a structure having a low spatial frequency in the image, and the dynamic range is compressed using the blurred image. Thus, there has been proposed a method for suppressing the collapse of both the bright and dark portions of the image while keeping the fine texture contrast in the bright and dark portions included in the image (see Patent Document 1).
JP-A-9-130609

  However, in the method described in Patent Document 1, since the dynamic range compression rate is set based on information representing the brightness of the image, when the dynamic range of the image is compressed with the set dynamic range compression rate, There is a problem that a high-saturation color included in an image is saturated and crushed.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to compress the dynamic range of an image so that high-saturation colors are not saturated.

The image processing apparatus according to the present invention is arranged so that the density area of a color image falls within the density reproduction area of the reproduction means so as to be reproduced by reproduction means having a predetermined density reproduction area and color reproduction area. A correction value for correcting the pixel value of each pixel of the image is calculated, and the dynamic range is compressed by adding the correction value to the pixel value of each pixel of the color image to compress the dynamic range of the color image. In an image processing apparatus provided with a dynamic range compression means for obtaining a processed image,
Based on the dynamic range of the color image, a compression rate setting unit that sets a dynamic range compression rate for compressing the dynamic range of the color image so as to be within a density reproduction range of the reproduction unit;
Compression table generating means for generating a compression table for calculating a correction value according to a pixel value of each pixel of the color image based on the dynamic range compression rate;
A saturation calculating means for calculating the saturation at each pixel of the color image;
Saturation correction coefficient calculation means for calculating a saturation correction coefficient for correcting the correction value so that the correction amount decreases as the saturation calculated by the saturation calculation means increases,
The dynamic range compression means calculates the correction value by referring to the compression table, calculates the correction correction value by correcting the correction value with the saturation correction coefficient, and calculates the correction correction value for each pixel. It is means for obtaining the processed image by compressing the dynamic range of the color image by adding to the pixel value.

  In the image processing apparatus according to the present invention, the compression rate setting means creates a histogram of image data representing the color image, calculates a dynamic range of the color image based on the histogram, and adds the dynamic range to the dynamic range. Based on a predetermined reference value of the image data, a dynamic range compression ratio corresponding to each of a relatively high data value portion, a relatively low data value portion, and / or the entire image data is set. It may be a means.

The image processing method according to the present invention is arranged so that the density area of a color image falls within the density reproduction area of the reproduction means so that reproduction is performed in the reproduction means having a predetermined density reproduction area and color reproduction area. A correction value for correcting the pixel value of each pixel of the image is calculated, and the dynamic range is compressed by adding the correction value to the pixel value of each pixel of the color image to compress the dynamic range of the color image. In an image processing method for obtaining a processed image,
Based on the dynamic range of the color image, set a dynamic range compression ratio for compressing the dynamic range of the color image so as to be within the density reproduction range of the reproduction means,
Based on the dynamic range compression rate, generate a compression table for calculating a correction value according to the pixel value of each pixel of the color image,
Calculating the saturation at each pixel of the color image;
Calculating a saturation correction coefficient for correcting the correction value so that the correction amount decreases as the calculated saturation increases,
By calculating the correction value with reference to the compression table, correcting the correction value with the saturation correction coefficient to calculate a correction correction value, and adding the correction correction value to the pixel value of each pixel The processed image is obtained by compressing the dynamic range of the color image.

  The image processing method according to the present invention may be provided as a program for causing a computer to execute the image processing method.

  According to the present invention, based on the dynamic range of the color image, the dynamic range compression rate for compressing the dynamic range of the color image is set so as to be within the density reproduction range of the reproducing unit, and based on the dynamic range compression rate A compression table for calculating a correction value corresponding to the pixel value of each pixel of the color image is generated. On the other hand, the saturation at each pixel of the color image is calculated, and the saturation correction coefficient for correcting the correction value for correcting the pixel value of each pixel is calculated so that the dynamic range compression rate decreases as the saturation increases. The Then, the correction value for correcting the pixel value of each pixel of the color image is calculated by referring to the compression table, the calculated correction value is corrected by the saturation correction coefficient, the correction correction value is calculated, and the correction correction By adding the value to the pixel value of each pixel, the dynamic range of the color image is compressed and a processed image is obtained.

  For this reason, in a high saturation pixel, the degree to which the dynamic range is compressed is smaller than in a low saturation pixel such as gray having the same density, and as a result, the degree to which the high saturation pixel included in the color image is saturated is also small. can do. Therefore, according to the present invention, saturation of high saturation pixels can be prevented while compressing the dynamic range for a color image having many high saturation pixels.

  Also, a color image histogram is obtained, and based on this histogram, dynamic range compression is performed according to each of the entire image data, a high data value portion, and / or a low data value portion based on a predetermined reference value. By setting the ratio and performing dynamic range compression processing with the set dynamic range compression ratio, the contrast is weakened only in the bright or dark part of the color image, and the dynamic range is applied to the part where the contrast is weak over a wide range. The compression process is not performed. For this reason, the bright and dark images will not be crushed, and the low-contrast parts of the image will not be further weakened, and this has been achieved by compressing the dynamic range. The image quality can be improved.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a schematic block diagram showing the configuration of an image processing apparatus according to an embodiment of the present invention. As shown in FIG. 1, the image processing apparatus according to the present embodiment has an image input unit 1 that receives input of image data S0 representing a color image composed of RGB color data, and an image represented by image data S0 (hereinafter referred to as an image). Similarly, the reference code S0 is used to analyze the image analysis unit 2 (compression rate setting means) for setting the dynamic range compression rate P0, and based on the dynamic range compression rate P0 set by the image analysis unit 2, A compression table generation unit 3 that generates a compression table T0 for calculating a correction value corresponding to the pixel value of each pixel of S0, a saturation calculation unit 4 that calculates saturation C at each pixel of the image S0, and saturation calculation A saturation correction coefficient calculation unit 5 that calculates a saturation correction coefficient f (C) for correcting the correction value so that the correction amount decreases as the saturation C calculated by the unit 4 increases, and a compression table A correction value for correcting the pixel value of each pixel of the image S0 is calculated with reference to the compression table T0 generated by the generation unit 3, and the correction value is corrected by the saturation correction coefficient f (C). , And the correction correction value is added to the pixel value of each pixel of the image S0, thereby compressing the dynamic range of the image S0 and obtaining the processed image data S1, and the processed image data S1. An image output unit 7 (reproducing means) such as a printer or a monitor for reproduction is provided. In the present embodiment, the image output unit 7 is a printer that obtains the print P of the processed image data S1.

  The image input unit 1 includes a media drive that reads image data S0 recorded on the medium from the medium, and various interfaces that receive input of the image data S0 transmitted via the network. The image data S0 may be acquired by an imaging device such as a digital camera, or may be acquired by photoelectrically reading an image recorded on a film or a document.

The image analysis unit 2 sets the compression rate of the image S0 as follows. First, the image analysis unit 2 calculates the density Y of each pixel of the image S0 by the following equation (1). R0, G0, and B0 are RGB data of each pixel of the image S0.
Y = 0.3125R0 + 0.3750G0 + 0.3125B0 (1)
Next, the image analysis unit 2 obtains a histogram of density Y. FIG. 2 is a diagram showing a histogram H of density Y. In the histogram H, the image analysis unit 2 obtains the density at which the cumulative relative frequency from the shadow side is 3% as the shadow density Ys of the image data S0.

On the other hand, information on the maximum density Dmax that can be reproduced by the image output unit 7 is input to the image analysis unit 2, and the image analysis unit 2 compares the shadow density Ys with the maximum density Dmax to determine the shadow density Ys. If the shadow density Ys is darker than the maximum density Dmax, the dynamic range compression rate for making the shadow density Ys fall within Dmax around the preset reference density Y0 is set. calculate. Specifically, the dynamic range compression rate P0 is calculated as shown in the following equation (2).
P0 = (Ys−Y0) / (Dmax−Y0) (2)
Here, as the value of the reference density Y0, for example, when the subject included in the image S0 is a person, a value between 0.50 and 0.70 that is substantially the same density as the skin color (as a ratio to the number of bits). , Preferably set to 0.6.

  The compression table generation unit 3 generates a compression table T0 for calculating a correction value according to the pixel value of each pixel of the image S0 based on the dynamic range compression rate P0 set by the image analysis unit 2. FIG. 3 is a diagram illustrating an example of a compression table. As shown in FIG. 3, in the compression table T0, Y0 is the reference density described above, and the slope of the straight line portion is 1 / P0-1.

  In the compression table T0, if the portion where the inclination changes (that is, the point of the reference density Y0) is discontinuous, an artifact may occur in the processed image. Therefore, a function that makes the inclination continuous should be set. Thus, the occurrence of artifacts can be prevented.

The saturation calculation unit 4 calculates the saturation C of each pixel of the image S0 by the following equation (3). In Equation (3), W is the average value (R0 + G0 + B0) / 3 of the RGB data R0, G0, B0 in each pixel. Note that the saturation calculation method is not limited to the method shown in Equation (3), and various known methods can be used.
C = √ ((R0−W) ² + (G0−W) ² + (B0−W) ² ) (3)
The saturation correction coefficient calculation unit 5 calculates a saturation correction coefficient f (C) for correcting the compression table T0 according to the value of saturation C. Specifically, the saturation correction coefficient f (C) is calculated by the following equation (4).
f (C) = (Cmax−C) / Cmax (4)
However, Cmax is the maximum value of the saturation C calculated by the above equation (3) for all color data that can be received as image data S0 in advance.

  As can be seen from equation (4), the saturation correction coefficient f (C) is in the range of 0 ≦ f (C) ≦ 1, and the saturation correction coefficient f (C ) Value becomes smaller.

  The compression processing unit 6 compresses the dynamic range of the image data S0 as follows. First, the compression processing unit 6 calculates the density Y of each pixel of the image S0 by the above-described equation (1). Then, a filtering process using a low-pass filter of a predetermined size is performed on the image S0 to obtain a blurred image having a blurred density Y ′. Here, if the size of the low-pass filter is too small, the sharpness is unnaturally emphasized or the overshoot of the edge portion becomes conspicuous. On the other hand, when the main subject such as the face is small, there is a drawback that the effect of the blur mask does not appear so much, or the amount of calculation increases and the scale of the apparatus increases. For this reason, in this embodiment, the size of the low-pass filter is set so that this does not occur.

Next, the compression processing unit 6 performs dynamic range compression processing on the image data S0. Specifically, as shown in the following formulas (5) to (7), a correction value LutDR (Y ′), which is a value obtained by processing the blur density Y ′ of each pixel according to the compression table T0, is calculated and further calculated. The correction value LutDR (Y ′) is corrected by multiplying the correction value LutDR (Y ′) by the saturation correction coefficient f (C), and the RGB color data R0, G0, B0 of each pixel of the image S0 is corrected. By adding the correction value LutDR (Y ′) corrected by the saturation correction coefficient f (C), processed RGB color data R1, G1, and B1 are obtained.
R1 = R0 + f (C) × LutDR (Y ′) (5)
G1 = G0 + f (C) × LutDR (Y ′) (6)
B1 = B0 + f (C) × LutDR (Y ′) (7)
Then, the compression processing unit 6 outputs processed image data S1 including processed RGB color data R1, G1, B1 to the image output unit 7.

  The image output unit 7 prints out the processed image data S1 to obtain a processed image print P.

  Next, processing performed in the present embodiment will be described. FIG. 4 is a flowchart showing processing performed in the present embodiment. First, the image input unit 1 accepts input of image data S0 (step S1). Next, the image analysis unit 2 analyzes the image data S0 and sets the dynamic range compression rate P0 (step S2), and the compression table generation unit 3 performs compression based on the dynamic range compression rate P0 set by the image analysis unit 2 A table T0 is generated (step S3).

  On the other hand, the saturation calculation unit 4 calculates the saturation C of each pixel of the image S0 (step S4), and the saturation correction coefficient calculation unit 5 calculates the saturation correction coefficient f (C) (step S5). Subsequently, the compression processing unit 6 performs calculations shown in the above formulas (5) to (7) to compress the dynamic range of the image S0 to obtain processed image data S1 (step S6), and the image output unit 7 performs processing. The completed image data S1 is printed out (step S7), and the process ends.

  As described above, in this embodiment, the saturation correction coefficient f (C) for correcting the correction value LutDR (Y ′) is calculated so that the correction amount decreases as the saturation increases, and the compression table T0 is referred to. The correction value LutDR (Y ′) calculated in this way is corrected by the saturation correction coefficient f (C), and the corrected correction value f (C) × LutDR (Y ′) is added to the pixel value of each pixel. Thus, the processed image data S1 is calculated. For this reason, in a high saturation pixel having a high saturation C, the degree to which the dynamic range is compressed is smaller than in a low saturation pixel such as gray having the same density, and as a result, the high saturation pixel included in the image S0 is reduced. The degree of saturation can also be reduced. Therefore, according to the present embodiment, it is possible to prevent saturation of high saturation pixels while compressing the dynamic range for the image S0 having many high saturation pixels.

  In the above embodiment, the compression table T0 compresses the dynamic range on the shadow side of the image S0. However, as shown in FIG. 5, the compression table T0 compresses the dynamic range on the highlight side of the image S0. As shown in FIG. 6, a compression table T0 for compressing the dynamic range on both the shadow side and the highlight side may be generated.

In the above embodiment, the compression processing unit 6 obtains a blurred image having the blurred density Y ′ of the image S0 and compresses the dynamic range of the image data S0. However, instead of the blurred density Y ′, a low-pass filter is used. As shown in the following equations (8) to (10), the density Y of each pixel is used for the RGB color data R0, G0, B0 of each pixel of the image S0, using the density Y before the filtering process is performed. The processed RGB color data R1, G1, B1 may be obtained by adding the value LutDR (Y) obtained by processing Y with the compression table T0. Thereby, dynamic range compression processing can be performed at high speed.
R1 = R0 + f (C) × LutDR (Y) (8)
G1 = G0 + f (C) × LutDR (Y) (9)
B1 = B0 + f (C) × LutDR (Y) (10)

1 is a schematic block diagram showing the configuration of an image processing apparatus according to an embodiment of the present invention. Diagram showing density histogram The figure which shows the example of the compression table which compresses the dynamic range of the shadow side A flowchart showing processing performed in the present embodiment The figure which shows the example of the compression table which compresses the dynamic range of highlight side The figure which shows the example of the compression table which compresses the dynamic range of shadow side and highlight

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image input part 2 Image analysis part 3 Compression table production | generation part 4 Saturation calculation part 5 Saturation correction coefficient calculation part 6 Compression processing part 7 Image output part

Claims (4)

In order to reproduce in the reproduction means having a predetermined density reproduction area and color reproduction area, the pixel value of each pixel of the color image is set so that the density area of the color image falls within the density reproduction area of the reproduction means. Dynamic range compression that calculates a correction value to be corrected and adds the correction value to the pixel value of each pixel of the color image to compress the dynamic range of the color image to obtain a processed image in which the dynamic range is compressed In an image processing apparatus comprising means,
Based on the dynamic range of the color image, a compression rate setting unit that sets a dynamic range compression rate for compressing the dynamic range of the color image so as to be within a density reproduction range of the reproduction unit;
Compression table generating means for generating a compression table for calculating a correction value according to a pixel value of each pixel of the color image based on the dynamic range compression rate;
A saturation calculating means for calculating the saturation at each pixel of the color image;
Saturation correction coefficient calculation means for calculating a saturation correction coefficient for correcting the correction value so that the correction amount decreases as the saturation calculated by the saturation calculation means increases,
The dynamic range compression means calculates the correction value by referring to the compression table, calculates the correction correction value by correcting the correction value with the saturation correction coefficient, and calculates the correction correction value for each pixel. An image processing apparatus, characterized in that the processed image is obtained by compressing a dynamic range of the color image by adding to a pixel value.   The compression rate setting means creates a histogram of image data representing the color image, calculates a dynamic range of the color image based on the histogram, and based on the dynamic range, a predetermined reference value of the image data 2. A means for setting a dynamic range compression ratio corresponding to each of a relatively high portion of the data value, a relatively low portion of the data value and / or the whole of the image data with reference to The image processing apparatus described. In order to reproduce in the reproduction means having a predetermined density reproduction area and color reproduction area, the pixel value of each pixel of the color image is set so that the density area of the color image falls within the density reproduction area of the reproduction means. An image processing method for calculating a correction value to be corrected and adding the correction value to a pixel value of each pixel of the color image to compress the dynamic range of the color image to obtain a processed image in which the dynamic range is compressed In
Based on the dynamic range of the color image, set a dynamic range compression ratio for compressing the dynamic range of the color image so as to be within the density reproduction range of the reproduction means,
Based on the dynamic range compression rate, generate a compression table for calculating a correction value according to the pixel value of each pixel of the color image,
Calculating the saturation at each pixel of the color image;
Calculating a saturation correction coefficient for correcting the correction value so that the correction amount decreases as the calculated saturation increases,
By calculating the correction value with reference to the compression table, correcting the correction value with the saturation correction coefficient to calculate a correction correction value, and adding the correction correction value to the pixel value of each pixel An image processing method, wherein the processed image is obtained by compressing a dynamic range of the color image. In order to reproduce in the reproduction means having a predetermined density reproduction area and color reproduction area, the pixel value of each pixel of the color image is set so that the density area of the color image falls within the density reproduction area of the reproduction means. An image processing method for calculating a correction value to be corrected and adding the correction value to a pixel value of each pixel of the color image to compress the dynamic range of the color image to obtain a processed image in which the dynamic range is compressed In a program for causing a computer to execute
Based on the dynamic range of the color image, a procedure for setting a dynamic range compression ratio for compressing the dynamic range of the color image so as to be within the density reproduction range of the reproducing means;
A procedure for generating a compression table for calculating a correction value according to a pixel value of each pixel of the color image based on the dynamic range compression rate;
Calculating the saturation at each pixel of the color image;
A procedure for calculating a saturation correction coefficient for correcting the correction value such that the higher the calculated saturation, the smaller the correction amount;
By calculating the correction value with reference to the compression table, correcting the correction value with the saturation correction coefficient to calculate a correction correction value, and adding the correction correction value to the pixel value of each pixel And a procedure for obtaining the processed image by compressing the dynamic range of the color image.

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