JP4303061B2 - Image processing apparatus and method, and program - Google Patents

Description

  The present invention relates to an image processing apparatus and method for compressing a dynamic range of an image so as to be within the dynamic range of an output device such as a printer that outputs an image, and a program for causing a computer to execute the image processing method. .

  Conventionally, an image obtained by photoelectrically reading an image obtained 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).

Also, when compressing the dynamic range using a blurred image, a method using an IIR filter to save the filter line memory (see Patent Document 2), and suppressing artifacts appearing at the edge of the processed image In order to achieve this, a method has been proposed in which a plurality of blurred images having different frequency bands are generated, and a dynamic range is compressed using an integrated signal of the generated plurality of blurred images (see Patent Document 3).
JP-A-9-130609 Japanese Patent Laid-Open No. 9-182093 JP-A-10-75364

  However, in the methods described in Patent Documents 2 and 3, although the line memory of the filter can be saved and the image quality of the processed image can be improved, the amount of calculation for compressing the dynamic range is large, Processing takes a long time.

  The present invention has been made in view of the above circumstances, and an object thereof is to shorten the processing time when compressing the dynamic range of an image.

An image processing apparatus according to the present invention includes: a correction amount calculation unit that calculates a correction amount for compressing the dynamic range of the image based on image data representing the image; and the image data is corrected by the correction amount to correct the image data. In an image processing apparatus comprising: a processing unit that obtains a processed image with a compressed dynamic range by performing image processing including processing for compressing a dynamic range of an image on the image;
A determination means for determining whether or not an image change amount due to the image processing is larger than a predetermined threshold;
The correction amount calculating means generates a blurred image of the image when the determination is affirmed, calculates the correction amount from the blurred image, and when the determination is negative, calculates the correction amount from the image. It is a means for calculating.

  In the image processing apparatus according to the present invention, the determination means may determine the size of the compression ratio used when compressing the dynamic range, the size of the inclination of the compression table used when calculating the correction amount, and the Means for performing the determination may be set by using the magnitude of the density correction amount when the image processing includes AE processing as the amount of change in the image.

The image processing method according to the present invention calculates a correction amount for compressing the dynamic range of the image based on the image data representing the image, and corrects the image data by the correction amount to reduce the dynamic range of the image. In an image processing method for obtaining a processed image having a compressed dynamic range by performing image processing including compression processing on the image,
Determining whether or not the amount of change in the image by the image processing is greater than a predetermined threshold;
When the determination is affirmative, a blurred image of the image is generated and the correction amount is calculated from the blurred image. When the determination is negative, the correction amount is calculated from the image. Is.

  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, it is determined whether or not an image change amount due to image processing including dynamic range compression processing is greater than a predetermined threshold value. If this determination is affirmed, since the fine texture collapse included in the image is increased by the dynamic range compression processing, a blurred image of the image is generated as described in Patent Document 1, and the blurred image is generated from the blurred image. A dynamic range correction amount is calculated. On the other hand, if the determination is negative, the amount of change in the image due to image processing is small, and the fine textures included in the image are small, so the dynamic range correction amount is calculated from the image instead of the blurred image. For this reason, when the amount of image change due to image processing is small, the amount of calculation can be reduced compared to the case where the correction amount is calculated using a blurred image, thereby enabling image processing including dynamic range compression processing. The processing time when applying to the image can be shortened.

  Also, the compression rate when compressing the dynamic range of the image, the magnitude of the inclination of the compression table used when calculating the correction amount for compressing the dynamic range, and the brightness when the image processing includes AE processing By determining one of the correction amounts as the image change amount, it is possible to easily determine whether or not the image change amount is larger than a predetermined threshold value.

  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 includes an image input unit 1 that receives input of image data S0 representing a color image composed of RGB color data, and includes dynamic range compression processing for the image data S0. An image processing unit 2 that performs image processing to obtain processed image data S3 and an image output unit 3 such as a printer or a monitor that reproduces the processed image data S3 are provided. In the present embodiment, the image output unit 3 is a printer that obtains the print P of the processed image data S3.

  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. In the present embodiment, it is assumed that 8-bit image data S0 is input.

  The image processing unit 2 converts the number of bits of the image data S0 from 8 bits to 10 or 12 bits to obtain bit-converted image data S1, and performs AE processing on the image data S1 to perform AE processing. The AE processing unit 22 that obtains the processed image data S2, the analysis of the image represented by the image data S2 (hereinafter, the reference symbol S2 is also used for the image), and the compression table T0 for compressing the dynamic range An image analysis unit 23 that calculates a coefficient for obtaining an inclination, a compression table generation unit 24 that generates a compression table T0 that compresses the dynamic range of the image S0 based on the coefficient calculated by the image analysis unit 23, and a compression table generation unit Correction amount calculation unit 25 for calculating dynamic range correction amount C0 based on compression table T0 generated by 24, and correction C0 comprises a compression unit 26 for obtaining processed image data S3 by compressing the dynamic range of the image S2 by.

  The bit conversion unit 21 converts the number of bits of the image data S0 to 10 or 12 bits larger than 8 bits to obtain the image data S1 in which the number of bits is converted.

  The AE processing unit 22 detects a skin color area as a face area from an image represented by the image data S1 (hereinafter also using the reference sign S1), so that the face area has a predetermined appropriate brightness. The image data S2 subjected to the AE process is obtained by adding / subtracting a predetermined value to / from all the pixels of the image S1. Thereby, for example, when a predetermined value is subtracted from each pixel of the image S1, the entire density of the image S1 is reduced as shown in FIG. Note that the AE treatment method is not limited to this, and various known methods can be applied.

The image analysis unit 23 sets the compression rate of the image S2 as follows. First, the image analysis unit 23 calculates the density Y of each pixel of the image S2 by the following equation (1). R0, G0, and B0 are RGB data of each pixel of the image S2.
Y = 0.3125R0 + 0.3750G0 + 0.3125B0 (1)
Next, the image analysis unit 23 obtains a histogram of density Y. FIG. 3 is a diagram showing a histogram H of density Y. In the histogram H, the image analysis unit 23 obtains the density at which the cumulative relative frequency from the highlight side and the shadow side is 3% as the highlight density Yh and the shadow density Ys of the image data S2, respectively.

  On the other hand, information on the minimum density Dmin and the maximum density Dmax that can be reproduced by the image output unit 3 is input to the image analysis unit 23, and the image analysis unit 23 compares the highlight density Yh with the minimum density Dmin. When the highlight density Yh is lower than the minimum density Dmin, the compression table T0 for keeping the highlight density Yh within the minimum density Dmin around the preset reference density Y0 is used. A coefficient Ph for obtaining the inclination is calculated. On the other hand, the image analysis unit 23 compares the shadow density Ys and the maximum density Dmax. If the shadow density Ys is higher than the maximum density Dmax, the image analysis unit 23 uses the preset reference density Y0 as the center to perform the shadowing. A coefficient Ps for calculating the slope of the compression table T0 for keeping the density Ys within the maximum density Dmax is calculated. Specifically, the coefficients Ph and Ps are calculated as shown in the following equations (2) and (3).

Ph = (Dmin−Y0) / (Yh−Y0) (2)
Ps = (Dmax−Y0) / (Ys−Y0) (3)
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.

  Note that the coefficient Ph is not calculated when the highlight density Yh falls within the minimum density Dmin, and the coefficient Ps is not calculated when the shadow density Ys falls within the maximum density Dmax.

  The compression table generation unit 24 generates a compression table T0 based on the coefficients Ph and Ps set by the image analysis unit 23. FIG. 4 is a diagram illustrating an example of a compression table. As shown in FIG. 4, in the compression table T0, Y0 is the above-described reference density, and the slope of the straight line portion is Ph-1 on the highlight side (that is, the left side of the reference density Y0), and shadow side (that is, from the reference density Y0). Is also Ps-1.

  If the coefficient Ps is not calculated in the image analysis unit 23, a compression table T0 for compressing only the highlight portion is generated as shown in FIG. If the coefficient Ph is not calculated, a compression table T0 for compressing only the shadow part is generated as shown in FIG. In the present embodiment, it is assumed that a compression table T0 for compressing both the shadow part and the highlight part is generated as shown in FIG.

  Here, 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 is set. As a result, the occurrence of artifacts can be prevented.

The correction amount calculation unit 25 calculates the density Y of each pixel of the image S2 by the above-described equation (1). Whether the magnitude | Ph−1 | of the highlight side of the generated compression table T0 is larger than the threshold Th1 and the magnitude | Ps−1 | of the shadow side is larger than the threshold Th2. Determine. When this determination is positive, by compressing the dynamic range, since the collapse of the fine texture included in images S2 is increased, the filtering process with the low pass filter of a predetermined size for image S2 As a result, a blurred image S2 ′ having the blurred density Y ′ is obtained. 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 the first embodiment, the size of the low-pass filter is set so that this does not occur.

  Then, the value LutDR (Y ′) obtained by referring to the compression table T0 using the blur density Y ′ is calculated as the dynamic range correction amount C0.

  On the other hand, when the determination is negative, the change amount of the image S2 due to the dynamic range compression process is small, and the fine texture included in the image S2 is small, so the density Y is used instead of the blur density Y ′. Then, the value LutDR (Y) obtained by referring to the compression table T0 is calculated as the dynamic range correction amount C0.

The compression processing unit 26 performs dynamic range compression processing on the image data S2 based on the correction amount C0 calculated by the correction amount calculation unit 25. Specifically, as shown in the following formulas (4) to (6), the correction amount C0 is added to the RGB color data R0, G0, B0 of each pixel of the image S2 to complete the processing. RGB color data R1, G1, and B1 are obtained.
R1 = R0 + C0 (4)
G1 = G0 + C0 (5)
B1 = B0 + C0 (6)
Then, the compression processing unit 26 outputs processed image data S3 including processed RGB color data R1, G1, and B1 to the image output unit 3.

  As a result, as shown in FIG. 2, the density on the highlight side of the image S2 is increased around the reference density Y0, and the density on the shadow side is decreased, thereby compressing the dynamic range of the image S2.

  The image output unit 3 converts the number of bits of the processed image data S3 into 8 bits and prints out to obtain a processed image print P.

  Next, the operation of this embodiment will be described. FIG. 7 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 bit conversion unit 21 converts the number of bits of the image data S0 to obtain image data S1 (step S2), and the AE processing unit 22 performs AE processing on the image data S1 to obtain image data S2 (step S3). Then, the image analysis unit 23 calculates the coefficients Ph and Ps (step S4), and the compression table generation unit 24 generates the compression table T0 based on the coefficients Ph and Ps (step S5).

  Next, the correction amount calculation unit 25 calculates the density Y of each pixel of the image S2 (step S6), and the magnitude | Ph-1 | of the highlight side of the compression table T0 is larger than the threshold value Th1 and is a shadow. It is determined whether the magnitude of the side inclination | Ps-1 | is larger than the threshold value Th2 (step S7). If the determination in step S7 is affirmative, a blurred image S2 ′ composed of a blurred density Y ′ of density Y is generated (step S8), and a dynamic range correction amount C0 is calculated from the blurred density Y ′ with reference to the compression table T0 (step S8). Step S9). On the other hand, if step S7 is negative, the dynamic range correction amount C0 is calculated from the density Y (step S10).

  Then, the compression processing unit 26 compresses the dynamic range of the image S2 by the correction amount C0 to obtain processed image data S3 (step S11), and the image output unit 3 prints out the processed image data S3 (step S12). The process ends.

  As described above, in the present embodiment, the magnitude | Ph-1 | of the highlight side of the compression table T0 is larger than the threshold value Th1, and the magnitude of the inclination | Ps-1 | When it is determined whether or not it is greater than the value Th2, if this determination is affirmative, a blurred image S2 ′ of the image S2 is generated, and the dynamic range correction amount C0 is calculated from the blurred density Y ′. In this example, the correction amount C0 of the dynamic range is calculated without generating the blurred image S2 ′ of the image S2. For this reason, when the inclination of the compression table T0 is small and the change amount of the image by the dynamic range compression process is small, the amount of calculation can be reduced compared with the case where the correction amount C0 is calculated from the blur density Y ′. Thus, it is possible to shorten the processing time when performing the dynamic range compression processing.

In the first embodiment, the highlight side inclination magnitude | Ph-1 | of the compression table T0 is larger than the threshold Th1 and the shadow side inclination magnitude | Ps-1 | When the threshold value Th2 is greater than the threshold value Th2, the dynamic range correction amount C0 is calculated from the blur density Y '. However, the magnitude | Ph-1 | of the compression table T0 on the highlight side is greater than the threshold value Th1. Alternatively, when the magnitude of inclination on the shadow side | Ps−1 | is larger than the threshold value Th2, the dynamic range correction amount C0 may be calculated from the blur density Y ′. As shown in FIG. 5, when the compression table T0 for compressing the dynamic range on the highlight side is obtained, is the magnitude of the highlight side inclination | Ph-1 | larger than the threshold value Th1? If the compression table T0 for compressing the dynamic range on the shadow side is determined as shown in FIG. 6, the magnitude of the inclination on the shadow side | P s -1 | is the threshold Th 2. What is necessary is just to determine whether it is larger.

  In the above-described embodiment, the compression table T0 is generated by the image analysis unit 23 and the compression table generation unit 24. However, the dynamic range correction amount C0 is set using a compression table (T1) prepared in advance. It may be calculated. FIG. 8 is a diagram showing an example of the compression table T1 prepared in advance. When the dynamic range of the image S2 is compressed using such a compression table T1, it is possible to obtain a processed image S3 in which the density on the highlight side is increased and the density on the shadow side is decreased as shown in FIG. However, a density range lower than the density Yk on the highlight side cannot be reproduced in the image output unit 3.

  Therefore, when the compression table T1 prepared in advance is used, the lowest density Yk that can be reproduced by the image output unit 3 is obtained, the correction amount LutDR (Yk) of the density Yk is obtained on the compression table T1, and the correction amount LutDR (Yk ) May be a dynamic range compression rate, and it may be determined whether or not the dynamic range compression rate is greater than a predetermined threshold value Th3. In this case, if this determination is affirmed, the dynamic range compression processing increases the amount of fine texture included in the image. Therefore, the dynamic range correction amount C0 is calculated from the blur density Y ′, and the above determination is denied. Then, the amount of change in the image due to the image processing is small, and the fine texture included in the image S2 is also small. Therefore, the dynamic range correction amount C0 may be calculated from the density Y.

Since the compression table T1 is non-linear, a differential value at the density Yk may be obtained, and it may be determined whether or not the magnitude of this differential value is greater than a predetermined threshold value Th4. Further, it may be determined whether or not a predetermined value in the AE processing unit 22 (that is, a value to be added to or subtracted from the image S1 in order to obtain the image S2 from the image S1 ) is larger than a predetermined threshold Th5.

  In these cases, if the determination is affirmed, the fine texture collapse included in the image is increased by the dynamic range compression processing. Therefore, the dynamic range correction amount C0 is calculated from the blur density Y ′, and the determination is negative. Then, the amount of change in the image due to the image processing is small, and the fine texture included in the image S2 is small, so the dynamic range correction amount C0 may be calculated from the density Y.

1 is a schematic block diagram showing the configuration of an image processing apparatus according to an embodiment of the present invention. The figure for demonstrating AE processing and dynamic range compression processing Diagram showing density histogram An example of a compression table that compresses the dynamic range of the shadow side and highlight 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 the shadow side A flowchart showing processing performed in the present embodiment The figure which shows the example of the compression table prepared beforehand The figure for demonstrating the dynamic range compression process using the compression table shown in FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image input part 2 Image processing part 3 Image output part 21 Bit conversion part 22 AE processing part 23 Image analysis part 24 Compression table production | generation part 25 Correction amount calculation part 26 Compression processing part

Claims (9)

A density histogram of the image is calculated, and the highlight density and shadow density of the density histogram are compared with the lowest density and the highest density that can be reproduced by the image output apparatus that outputs the processed image, respectively, and based on the comparison result Te, the density of each pixel of the image to the x-axis, such as when the correction amount for compressing the dynamic range was placed on the y-axis, the correction amount of change with respect to change of the pre-Symbol concentration of linear, Table generating means for generating a compression table representing a relational expression defining the relationship between the density and the correction amount;
Correction amount calculation means for calculating a correction amount to be added to each pixel of the image in order to compress the dynamic range of the image with reference to the compression table;
An image processing apparatus comprising: processing means for obtaining a processed image in which the dynamic range is compressed by performing processing for adding the correction amount to each pixel of the image and compressing the dynamic range of the image to the image In
Determination means for determining whether or not the slope of the relational expression is greater than a predetermined threshold;
When the determination is affirmative, the correction amount calculation unit generates a blurred image of the image, calculates the correction amount by referring to the compression table using the blurred image, and the determination is negative In this case, the image processing apparatus is means for calculating the correction amount by referring to the compression table using the image. Referring to a compression table that defines the relationship between the density of each pixel in the image and the correction amount for compressing the dynamic range, calculate the correction amount to be added to each pixel of the image to compress the dynamic range of the image Correction amount calculating means to perform,
An image processing apparatus comprising: processing means for obtaining a processed image in which the dynamic range is compressed by performing processing for adding the correction amount to each pixel of the image and compressing the dynamic range of the image to the image In
A determination means for determining whether or not a density correction amount by the compression table of the lowest density that can be reproduced by the image output apparatus that outputs the processed image is larger than a predetermined threshold;
When the determination is affirmative, the correction amount calculation unit generates a blurred image of the image, calculates the correction amount by referring to the compression table using the blurred image, and the determination is negative In this case, the image processing apparatus is means for calculating the correction amount by referring to the compression table using the image. When the density of each pixel of the image is on the x-axis and the correction amount for compressing the dynamic range is on the y-axis, the density and the correction are changed so that the change in the correction amount with respect to the change in density becomes non-linear. A correction amount calculation means for calculating a correction amount to be added to each pixel of the image in order to compress the dynamic range of the image with reference to a non-linear compression table representing a relational expression that defines a relationship with the amount;
An image processing apparatus comprising: processing means for obtaining a processed image in which the dynamic range is compressed by performing processing for adding the correction amount to each pixel of the image and compressing the dynamic range of the image to the image In
A determination means for determining whether a differential value of the relational expression at a preset reference concentration is larger than a predetermined threshold;
When the determination is affirmative, the correction amount calculation unit generates a blurred image of the image, calculates the correction amount by referring to the compression table using the blurred image, and the determination is negative In this case, the image processing apparatus is means for calculating the correction amount by referring to the compression table using the image. A density histogram of the image is calculated, and the highlight density and shadow density of the density histogram are compared with the lowest density and the highest density that can be reproduced by the image output apparatus that outputs the processed image, respectively, and based on the comparison result Te, the density of each pixel of the image to the x-axis, such as when the correction amount for compressing the dynamic range was placed on the y-axis, the correction amount of change with respect to change of the pre-Symbol concentration of linear, A compression table representing a relational expression that defines the relationship between the density and the correction amount is generated, and a correction amount to be added to each pixel of the image to compress the dynamic range of the image with reference to the compression table. The dynamic range is compressed by calculating and adding the correction amount to each pixel of the image and compressing the dynamic range of the image. An image processing method for obtaining processed image,
Determining whether the slope of the relational expression is greater than a predetermined threshold;
When the determination is affirmative, a blurred image of the image is generated, the correction amount is calculated by referring to the compression table using the blurred image, and when the determination is negative, the image is used. An image processing method, wherein the correction amount is calculated with reference to the compression table. Referring to a compression table that defines the relationship between the density of each pixel in the image and the correction amount for compressing the dynamic range, calculate the correction amount to be added to each pixel of the image to compress the dynamic range of the image Then, in the image processing method of obtaining a processed image with a compressed dynamic range by adding the correction amount to each pixel of the image and compressing the dynamic range of the image,
Determining whether the density correction amount by the compression table of the lowest density that can be reproduced by the image output apparatus that outputs the processed image is larger than a predetermined threshold value;
When the determination is affirmative, a blurred image of the image is generated, the correction amount is calculated by referring to the compression table using the blurred image, and when the determination is negative, the image is used. An image processing method, wherein the correction amount is calculated with reference to the compression table. When the density of each pixel of the image is on the x-axis and the correction amount for compressing the dynamic range is on the y-axis, the density and the correction are changed so that the change in the correction amount with respect to the change in density becomes non-linear. A correction amount to be added to each pixel of the image in order to compress the dynamic range of the image is calculated with reference to a non-linear compression table that represents a relational expression that defines the relationship with the amount, and the pixel of the image In an image processing method for obtaining a processed image in which the dynamic range is compressed by performing a process of adding a correction amount to compress the dynamic range of the image,
Determining whether a differential value of the relational expression at a preset reference concentration is larger than a predetermined threshold;
When the determination is affirmative, a blurred image of the image is generated, the correction amount is calculated by referring to the compression table using the blurred image, and when the determination is negative, the image is used. An image processing method, wherein the correction amount is calculated with reference to the compression table. A density histogram of the image is calculated, and the highlight density and shadow density of the density histogram are compared with the lowest density and the highest density that can be reproduced by the image output apparatus that outputs the processed image, respectively, and based on the comparison result Te, the density of each pixel of the image to the x-axis, such as when the correction amount for compressing the dynamic range was placed on the y-axis, the correction amount of change with respect to change of the pre-Symbol concentration of linear, A compression table representing a relational expression that defines the relationship between the density and the correction amount is generated, and a correction amount to be added to each pixel of the image to compress the dynamic range of the image with reference to the compression table. The dynamic range is compressed by calculating and adding the correction amount to each pixel of the image and compressing the dynamic range of the image. The program for executing an image processing method for obtaining a processed image in computers,
Determining whether the slope of the relational expression is greater than a predetermined threshold;
When the determination is affirmative, a blurred image of the image is generated, the correction amount is calculated by referring to the compression table using the blurred image, and when the determination is negative, the image is used. A program for calculating the correction amount with reference to the compression table. Referring to a compression table that defines the relationship between the density of each pixel in the image and the correction amount for compressing the dynamic range, calculate the correction amount to be added to each pixel of the image to compress the dynamic range of the image Then, an image processing method for obtaining a processed image with a compressed dynamic range is performed on the computer by adding the correction amount to each pixel of the image and compressing the dynamic range of the image. In the program to let
A procedure for determining whether a density correction amount by the compression table having the lowest density that can be reproduced by the image output apparatus that outputs the processed image is larger than a predetermined threshold;
When the determination is affirmative, a blurred image of the image is generated, the correction amount is calculated by referring to the compression table using the blurred image, and when the determination is negative, the image is used. A program for calculating the correction amount with reference to the compression table. When the density of each pixel of the image is on the x axis and the correction amount for compressing the dynamic range is on the y axis, the density and the correction are made so that the change in the correction amount with respect to the change in density becomes non-linear A correction amount to be added to each pixel of the image in order to compress the dynamic range of the image is calculated with reference to a non-linear compression table that represents a relational expression that defines the relationship with the amount, and the pixel of the image In a program for causing a computer to execute an image processing method for obtaining a processed image with a compressed dynamic range by performing a process of adding a correction amount and compressing the dynamic range of the image on the image,
A procedure for determining whether a differential value of the relational expression at a preset reference concentration is larger than a predetermined threshold;
When the determination is affirmative, a blurred image of the image is generated, the correction amount is calculated by referring to the compression table using the blurred image, and when the determination is negative, the image is used. A program for calculating the correction amount with reference to the compression table.

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