JP6164024B2 - Image processing apparatus and program - Google Patents

Description

  The present invention relates to an image processing apparatus and a program.

  After evaluating the image quality (sharpness) of the subject area of the target image, obtaining the high frequency component of the target image, converting the high frequency component based on the evaluation result of the image quality, and processing the target image based on the converted high frequency component An image processing apparatus that acquires an image is known (see, for example, Patent Document 1).

  Tone correction is performed on the luminance signal of the input image, the luminance signal change rate is calculated from the luminance signal of the input image and the luminance signal after gradation correction, and the color difference signal of the input image is calculated using the luminance signal change rate. At the time of correction, the amount of gradation correction is controlled according to the evaluation result obtained by evaluating the correction result performed on the preceding input image according to a predetermined standard, the luminance signal change rate is corrected, and the color difference signal is corrected. An image processing apparatus used for correction is also known (see, for example, Patent Document 2).

  The combination of the minimum contrast / brightness product and the minimum contrast / brightness constraint as a separate entity defines the range of “visually good” and higher, which is considered “visually ideal” It is also known that a contrast / brightness product contour may exist (see, for example, Non-Patent Document 1).

JP 2002-359780 A JP 2012-10227 A

Daniel J. Jobson, Zia-ur Rahman and Glenn A. Woodell, "The Statistics of Visual Representation", Visual Information Processing XI, Proc.SPIE, vol.4736, pp.25-35, July 2002

  An object of the present invention is to bring an image quality close to a designated image quality when emphasizing a specific component that affects the image quality.

According to the first aspect of the present invention, the original image and the enhancement degree information indicating the enhancement degree of a specific component that affects the image quality of the original image, the enhancement degree information having the first enhancement degree set. A first reproduction image generating unit configured to generate a first reproduction image reproduced so that the specific component of the original image is emphasized at the first enhancement degree; and the first reproduction image. First image quality amount acquisition means for acquiring a first image quality amount representing the image quality of the original image, second image quality amount acquisition means for acquiring a second image quality amount representing the image quality of the original image, and the first image quality Based on the amount, the second image quality amount, and the first enhancement level, the enhancement level set in the enhancement level information and the specific component of the original image are enhanced with the enhancement level. The amount of image quality that represents the image quality of the reproduced image Based on the image quality characteristic acquisition means for acquiring the image quality characteristic of the original image, the image quality characteristic, and the designated image quality amount representing the designated image quality, the image quality amount representing the image quality of the reproduced image becomes the designated image quality amount. Therefore, based on the enhancement degree acquisition means for acquiring the second enhancement degree to be set in the enhancement degree information, the original image, and the enhancement degree information in which the second enhancement degree is set, An image processing apparatus comprising: a second reproduction image generation unit configured to generate a second reproduction image that is reproduced so that the specific component of the image is emphasized at the second enhancement degree. .
The image processing according to claim 2, wherein the image quality characteristic acquisition unit acquires the image quality characteristic in which the enhancement degree and the image quality amount are associated with each other by a linear function. Device.
According to a third aspect of the present invention, the first reproduction image generating means is configured to determine whether the specific component of the original image is the other one based on the enhancement degree information in which another first enhancement degree is set. Further, another first reproduction image reproduced so as to be emphasized at the first enhancement degree is further generated, and the first image quality amount acquisition unit is configured to generate another image representing the image quality of the other first reproduction image. A first image quality amount is further acquired, and the image quality characteristic acquisition unit acquires the image quality characteristic further based on the other first image quality amount and the other first enhancement degree. The image processing apparatus according to claim 1.
According to a fourth aspect of the present invention, in the image processing according to the third aspect, the image quality characteristic acquisition unit acquires the image quality characteristic in which the enhancement degree and the image quality amount are associated by a non-linear function. Device.
According to a fifth aspect of the present invention, the image quality characteristic acquisition unit acquires the image quality characteristic in which the enhancement degree and the image quality amount are associated with each other by a monotonically increasing function or a monotonically decreasing function. An image processing apparatus according to any one of claims 1 to 4.
According to a sixth aspect of the present invention, each of the first reproduction image generation unit and the second reproduction image generation unit relates to at least one of luminance, chromaticity, brightness difference, and frequency of the original image. 5. The image processing apparatus according to claim 1, wherein the first reproduction image and the second reproduction image that have been emphasized are generated. 6.
According to the seventh aspect of the present invention, the degree of emphasis in which the first emphasis degree is set, which is emphasis degree information indicating the emphasis degree of the original image and a specific component that affects the image quality of the original image. Based on the information, the function of generating a first reproduction image that is reproduced so that the specific component of the original image is emphasized at the first enhancement degree, and the image quality of the first reproduction image A function for obtaining a first image quality amount, a function for obtaining a second image quality amount representing the image quality of the original image, the first image quality amount, the second image quality amount, and the first image quality amount. Based on the degree of enhancement, the degree of enhancement set in the degree-of-emphasis information, and an image quality amount representing the image quality of the reproduced image reproduced so that the specific component of the original image is enhanced with the degree of enhancement. A device for acquiring image quality characteristics of the associated original image And the image quality characteristic and the designated image quality amount representing the designated image quality, the image quality amount representing the image quality of the reproduced image becomes the designated image quality amount. The specific component of the original image is emphasized with the second enhancement degree based on the function of acquiring the enhancement degree, the original image, and the enhancement degree information in which the second enhancement degree is set. This is a program for realizing a function of generating a second reproduced image reproduced in such a manner.

According to the invention of claim 1, when emphasizing a specific component that affects the image quality of the image, the image quality of the image can be brought close to the designated image quality.
According to the second aspect of the present invention, it is possible to easily obtain the degree of emphasis for bringing the image quality of the image closer to the designated image quality as compared with the case where the present configuration is not provided.
According to the invention of claim 3, when emphasizing a specific component that affects the image quality of the image, the image quality of the image can be made closer to the designated image quality.
According to the fourth aspect of the present invention, it is possible to accurately obtain the degree of emphasis for bringing the image quality of the image closer to the designated image quality as compared with the case where the present configuration is not provided.
According to the fifth aspect of the present invention, it is possible to easily determine the degree of emphasis used to bring the image quality of the image close to the designated image quality as compared with the case where the present configuration is not provided.
According to the sixth aspect of the present invention, the image quality of the image can be brought close to the designated image quality when performing enhancement related to at least one of the brightness, chromaticity, contrast difference and frequency of the image.
According to the invention of claim 7, when emphasizing a specific component that affects the image quality of the image, the image quality of the image can be brought close to the designated image quality.

It is the block diagram which showed the function structural example of the image processing apparatus in embodiment of this invention. It is the figure which showed the relationship between (alpha) and Q in case the image quality amount Q converges as the reproduction parameter (alpha) approaches the maximum value. It is the figure which showed the relationship between (alpha) and Q in case the image quality amount Q falls as the reproduction parameter (alpha) approaches the maximum value. FIG. 5 is a diagram illustrating an original image quality amount and a predicted image quality amount when one value is used as an image quality prediction parameter value. It is the figure which showed the linear prediction characteristic when one value is used as an image quality prediction parameter value. It is the figure which showed the linear prediction characteristic in case a some value is used as an image quality prediction parameter value. It is the figure which showed the nonlinear prediction characteristic when a some value is used as an image quality prediction parameter value. It is the figure which showed the method of estimating an image quality control parameter value from the designated image quality amount using the prediction characteristic. FIG. 6 is a diagram illustrating a method for predicting an image quality control parameter value from a designated image quality amount using a prediction characteristic when a deviation occurs between a prediction characteristic and a true characteristic as the reproduction parameter α approaches a maximum value. It is the figure which showed the prediction characteristic which absorbed the gap | deviation in case a gap arises between a prediction characteristic and a true characteristic as the reproduction parameter (alpha) approaches the maximum value. 5 is a flowchart illustrating an operation example of the image processing apparatus according to the embodiment of the present invention. It is the block diagram which showed the hardware structural example of the image processing apparatus in embodiment of this invention.

  Embodiments of the present invention will be described below in detail with reference to the accompanying drawings.

[Background of the invention]
Image enhancement is based on correcting or enhancing luminance or chromaticity, and enhances the characteristics of the original image to produce a preferable reproduced image. Image enhancement includes gamma correction, saturation enhancement, band enhancement, contrast enhancement, dynamic range correction, and visibility improvement.

  Such control parameters for reproduction in image enhancement (hereinafter referred to as “reproduction parameters”) may be mechanically determined within the software. In that case, a value serving as a reference for reproduction is necessary, and for example, it is considered that this includes values relating to image quality. However, the value relating to image quality that can be calculated from the image is a physical quantity such as a value based on the contrast of the image. Accordingly, a psychological experiment has been conducted to determine what the image quality should look like, and a preferable range of physical quantities is presented from the correspondence between psychological quantities and physical quantities.

  However, even if a preferable range of physical quantities is presented in this way, it is not considered to determine a reproduction parameter in accordance with various images.

  Therefore, in the present embodiment, a reproduction parameter for reproducing a desired image quality is predicted according to the image.

[Configuration of the embodiment]
FIG. 1 is a block diagram illustrating a functional configuration example of an image processing apparatus 10 according to an embodiment of the present invention. As illustrated, the image processing apparatus 10 according to the present embodiment includes a prediction reproduction unit 11, image quality amount calculation units 12a and 12b, an image quality characteristic prediction unit 13, an image quality control parameter value calculation unit 14, and an image reproduction unit. 15. In the figure, the original image may be any image such as an RGB image, an L * a * b ** image, or an HSV image.

  The prediction reproduction unit 11 generates a reproduction image (hereinafter referred to as “prediction reproduction image”) for predicting the image quality by performing image reproduction for image quality prediction on the original image. Specifically, a parameter value for image quality prediction (hereinafter referred to as “image quality prediction parameter value”) is set to a reproduction parameter described later, and a predicted reproduction image is generated. Note that the prediction reproduction unit 11 is equivalent to an image reproduction unit 15 described later. In the following description, it is assumed that the prediction reproduction unit 11 and the image reproduction unit 15 perform the same processing.

  The processing performed by the prediction reproduction unit 11 is image enhancement. As image enhancement, enhancement such as band enhancement, contrast enhancement, luminance enhancement, and visibility improvement can be considered. Of these, band enhancement is an example of enhancement related to frequency, and contrast enhancement is an example of enhancement related to contrast. Further, the image enhancement can be generally called enhancement of a specific component that affects the image quality of the image. In the present embodiment, such image enhancement is collectively described as being performed by the following reproduction formula.

Here, I (x, y) represents the pixel value of the original image and is a luminance component (V for HSV, Y for YCbCr, L * for L * a * b *). . I _R (x, y) represents a pixel value when image enhancement is performed to the maximum. I ^ (x, y) represents the pixel value of the reproduced image, and corresponds to the pixel value of the predicted reproduced image when the predicted reproduction unit 11 performs image reproduction. Further, α is a reproduction parameter (enhancement degree information) representing the degree of enhancement in reproduction. When the prediction reproduction unit 11 performs image reproduction, the image quality prediction parameter value (first enhancement degree) in FIG. 1 is set. Is done. I ^ (x, y) is a pixel value when maximum image enhancement is performed when α = 1, and is a pixel value of the original image when α = 0. In the present embodiment, α may be any value from 0 to 1. In the present specification, a hat symbol is added immediately above a character in a mathematical expression, but is added after a character in a sentence.

Examples of the processing considered as conversion from I (x, y) to I _R (x, y) and the combination thereof include the following processing. Here, these six processes are shown because prediction of image quality characteristics to be described later is similar, but the present embodiment can be applied to any process as long as it does not impair the essence of these six processes. .
(1) Gamma curve enhancement (2) Band enhancement (3) Visibility improvement by Retinex principle (4) Combination of gamma curve enhancement and band enhancement (5) Combination of gamma curve enhancement and visibility enhancement by Retinex principle (6) Combination of bandwidth enhancement and visibility improvement by Retinex principle

  In the present embodiment, a predicted reproduction image is used as an example of a first reproduction image that is reproduced so that a specific component of the original image is emphasized at the first enhancement degree. The prediction reproduction unit 11 is provided as an example of the first reproduction image generation unit to be generated.

  The image quality amount calculation unit 12a calculates the image quality amount of the predicted reproduction image (hereinafter referred to as “predicted image quality amount”), and the image quality amount calculation unit 12b determines the image quality amount of the original image (hereinafter referred to as “original image image quality amount”). Is calculated. In the present embodiment, as an example, the amount of image quality is defined as follows.

  Here, Q represents an image quality amount that is a physical quantity related to an image. A symbol with a bar on I represents an average value of pixel values of all pixels. Furthermore, a symbol with a bar on σ represents a value obtained by averaging the dispersion of pixel values for each local region of the image over the entire region of the image. For example, a value obtained by dividing an image into a plurality of blocks and averaging the dispersion of pixel values in each block over the entire area of the image may be used. This value is also an index of contrast.

  In the present embodiment, the predicted image quality amount is used as an example of the first image quality amount representing the image quality of the first reproduced image, and an example of the first image quality amount acquisition unit that acquires the first image quality amount is used. The image quality amount calculation unit 12a is provided. Further, the original image quality amount is used as an example of the second image quality amount that represents the image quality of the original image, and the image quality amount calculation unit 12b is an example of a second image quality amount acquisition unit that acquires the second image quality amount. Is provided.

  The image quality characteristic prediction unit 13 includes a predicted image quality amount (Q of the predicted reproduction image) calculated by the image quality amount calculation unit 12a, an original image image quality amount (Q of the original image) calculated by the image quality amount calculation unit 12b, and a prediction reproduction unit. 11 predicts the relationship between α and Q as the image quality characteristic based on the image quality prediction parameter value used by 11.

  For example, when the amount of image quality is calculated experimentally with Formula 2 for many values of the reproduction parameter α, the relationship between α and Q is as shown in FIG. 2 in the above-described examples (1) to (6). There are many cases. That is, the processes (1) to (6) include elements that increase the contrast or the luminance average, and as α approaches the maximum value, the pixel value after conversion approaches the maximum value, so Q converges. I will do it.

  Further, depending on the processing, when α increases, the luminance average increases, but the contrast may decrease, and the relationship between α and Q may be as shown in FIG. That is, Q may decrease as α approaches the maximum value.

  The image quality characteristic prediction unit 13 predicts the image quality characteristic as shown in FIG. 2 or 3 (hereinafter, the image quality characteristic predicted here is also referred to as “prediction characteristic”). When the prediction reproduction unit 11 uses one value as the image quality prediction parameter value, an original image quality amount and a predicted image quality amount as shown in FIG. 4 are obtained. The original image quality amount is Q when α = 0. Further, the predicted image quality amount is Q in the case of α = 0.2 in FIG.

  As the prediction characteristics representing the relationship between α and Q, for example, those represented by the following linear format are conceivable. Such a prediction characteristic is the simplest and is easy to handle even at a later stage.

  Here, m and n are constants. Since Q when α = 0 and Q when α = 0.2 are known, m and n can be easily obtained. By using Equation 3, prediction characteristics as shown in FIG. 5 can be obtained.

  On the other hand, the prediction reproduction unit 11 may use a plurality of values as the image quality prediction parameter value. That is, a plurality of predicted image quality amounts may be used as shown in FIG. In FIG. 6, for example, the predicted image quality amount on the left is an example of the first image quality amount, and the predicted reproduction image that is the basis of this predicted image quality amount is an example of the first reproduction image. Assuming that the image quality prediction parameter value used for this is an example of the first enhancement degree, the right predicted image quality amount is an example of the other first image quality amount, and the predicted reproduced image that is the basis of this predicted image quality amount Is an example of another first reproduction image, and the image quality prediction parameter value used to generate the prediction reproduction image is an example of another first enhancement degree. In this case, Equation 3 is obtained by regression analysis as shown in FIG. Specifically, a straight line that passes through the original image quality amount and is similar to both of the plurality of predicted image quality amounts is set as the prediction characteristic.

  Alternatively, in this case, the relationship between α and Q may be approximated by a nonlinear function F as follows.

  Specific examples of F (α) include the following formulas.

Here, m ₀ , m ₁ , and m ₂ are coefficients of a quadratic expression. Also in this case, the coefficients m ₀ , m ₁ , and m ₂ are calculated by performing regression analysis on a plurality of points. However, when using Equation 5, since there are three coefficients, at least three image quality amounts including the original image image quality amount are required. The shape of the nonlinear function F (α) thus calculated is shown in FIG. Note that it is desirable that F (α) be a monotonically increasing function or a monotonically decreasing function, considering that α is calculated backward from Q at a later stage. In FIG. 7, F (α) is a monotonically increasing function.

  As described above, the image quality characteristic calculated by the image quality characteristic prediction unit 13 is a straight line or a curve representing the correspondence between α and Q.

  In the present embodiment, an image quality characteristic prediction unit 13 is provided as an example of an image quality characteristic acquisition unit that acquires image quality characteristics of an original image.

The image quality control parameter value calculation unit 14 predicts a parameter value (hereinafter referred to as “image quality control parameter value”) set as a reproduction parameter in order to actually control the image quality. Specifically, when the designated image quality amount Q _deg is given, the image quality control parameter value α _opt is predicted from the designated image quality amount Q _deg based on the image quality characteristic calculated by the image quality characteristic prediction unit 13.

In this case, an arbitrary value may be given as the designated image quality amount Q _deg . For example, if there is something desirable from the relationship between Q and psychological quantity, it may be given. In the present embodiment, Q is a physical quantity to the last, and if Q is maximum, the image quality is not good. It is assumed that a desirable Q value exists and the value of α is predicted when that value is given.

For example, when a prediction characteristic represented by a linear form such as Equation 3 is obtained, it is most easy to handle, and α _opt may be calculated as shown in FIG. Here, as shown by a broken line in FIG. 9, a case is considered where the true characteristic has a shape such that Q decreases as α increases from a value that maximizes Q. Even in such a case, it is unlikely that the image quality is favorable when Q is the maximum. Further, since Q means that the contrast is lowered, it is difficult to consider that the image quality is favorable when α is larger than the value that maximizes Q. Therefore, since it is considered that there is a preferable image quality amount in the section until Q becomes the maximum, the designated image quality amount Q _des may be given in this section, and linear prediction can be supported.

In FIG. 9, there is a difference between the prediction characteristic and the true characteristic when α is larger than the value that maximizes Q. However, the prediction characteristic is represented by a nonlinear expression such as Expression 4 and Expression 5. As shown in FIG. 10, the deviation may be absorbed. In this way, when the prediction characteristic is represented by a non-linear expression, the image quality control parameter value α _opt is obtained by searching. For example, the following equation may be solved by giving a suitable initial value to α and using the framework of Newton's method.

As described above, the image quality control parameter value calculation unit 14 calculates the image quality control parameter value α _{opt in} which the image quality amount of the reproduced image becomes the designated image quality amount Q _des .

  In the present embodiment, the image quality control parameter value is used as an example of the second enhancement degree that should be set in the enhancement degree information because the image quality amount representing the image quality of the reproduced image is the designated image quality amount. An image quality control parameter value calculation unit 14 is provided as an example of an enhancement degree acquisition unit that acquires the enhancement degree.

The image reproduction unit 15 uses the image quality control parameter value α _opt to generate a reproduction image using the following reproduction formula.

  Here, I ^ (x, y) represents the pixel value of the reproduced image as in the case of Equation 1, but in Equation 7, it corresponds to the pixel value of the reproduced image generated by the image reproduction unit 15.

  Note that the reproduction formula in the present embodiment is not limited to Formula 1 and Formula 7. Any reproduction formula may be adopted as long as the essence of the reproduction formula for image enhancement (control between the original image and the image with the maximum image enhancement) is not impaired.

  In the present embodiment, a reproduced image is used as an example of a second reproduced image that is reproduced so that a specific component of the original image is emphasized at the second enhancement degree, and the second reproduced image is generated. An image quality control parameter value calculation unit 14 is provided as an example of the second reproduced image generation means.

  In addition, as the image quality amount calculated in the present embodiment, the above-described image quality characteristics can be obtained if a physical amount including at least luminance and contrast is employed. Therefore, any physical quantity may be adopted as the image quality as long as it does not deviate from this essence.

  FIG. 11 is a flowchart showing an operation example of the image processing apparatus 10 according to the embodiment of the present invention.

  When the original image is input, first, the prediction reproduction unit 11 performs image reproduction with image enhancement on the original image using the reproduction parameter in which the image quality prediction parameter value is set, thereby obtaining the prediction reproduction image. Generate (step 101). Then, the image quality calculation unit 12a calculates a predicted image quality that is the image quality of the predicted reproduction image generated in step 101 (step 102). Further, the image quality amount calculation unit 12b calculates an original image quality amount that is the image quality amount of the original image (step 103). Here, the steps 101 to 103 are executed in this order, but may be executed in any order. Alternatively, at least one of step 101 and step 102 and step 103 may be executed in parallel.

  Next, the image quality characteristic prediction unit 13 uses the predicted image quality amount calculated in step 102, the original image image quality amount calculated in step 103, and the image quality prediction parameter value set in the reproduction parameter used in step 101. Based on the above, an image quality characteristic that is a correspondence relationship between the reproduction parameter and the image quality amount is predicted (step 104).

  Next, when the image quality control parameter value calculation unit 14 is given the designated image quality amount, the image quality control parameter to be set as the reproduction parameter in order to set the image quality amount to the designated image quality amount based on the image quality characteristic predicted in step 104. A value is calculated (step 105).

  Finally, the image reproduction unit 15 generates a reproduced image by performing image reproduction with image enhancement on the original image using the reproduction parameter in which the image quality control parameter value generated in step 105 is set. (Step 105).

[Hardware configuration of image processing apparatus]
The image processing apparatus 10 according to the present embodiment can be realized, for example, as image processing software installed in a PC, but is typically realized as an image processing apparatus 10 that performs image reading and image formation.

  FIG. 12 is a diagram illustrating a hardware configuration example of such an image processing apparatus 10. As illustrated, the image processing apparatus 10 includes a central processing unit (CPU) 21, a random access memory (RAM) 22, a read only memory (ROM) 23, a hard disk drive (HDD) 24, and an operation panel 25. An image reading unit 26, an image forming unit 27, and a communication interface (hereinafter referred to as “communication I / F”) 28.

  The CPU 21 implements various functions to be described later by loading various programs stored in the ROM 23 and the like into the RAM 22 and executing them.

  The RAM 22 is a memory used as a working memory for the CPU 21.

  The ROM 23 is a memory that stores various programs executed by the CPU 21.

  The HDD 24 is, for example, a magnetic disk device that stores image data read by the image reading unit 26 and image data used for image formation in the image forming unit 27.

  The operation panel 25 is a touch panel that displays various types of information and receives operation inputs from the user. Here, the operation panel 25 includes a display on which various types of information are displayed, and a position detection sheet that detects a position designated by a finger, a stylus pen, or the like.

  The image reading unit 26 reads an image recorded on a recording medium such as paper. Here, the image reading unit 26 is, for example, a scanner, and a CCD system in which reflected light with respect to light irradiated from a light source to a document is reduced by a lens and received by a CCD (Charge Coupled Devices), or an LED light source is sequentially irradiated onto a document. It is preferable to use a CIS system in which reflected light with respect to the received light is received by a CIS (Contact Image Sensor).

  The image forming unit 27 forms an image on a recording medium. Here, the image forming unit 27 is, for example, a printer, and forms an image by transferring the toner attached to the photosensitive member to a recording medium to form an image, or ejecting ink onto the recording medium. An ink jet type may be used.

  The communication I / F 28 transmits / receives various information to / from other devices via the network.

  The program for realizing the present embodiment can be provided not only by communication means but also by storing it in a recording medium such as a CD-ROM.

DESCRIPTION OF SYMBOLS 10 ... Image processing apparatus, 11 ... Prediction reproduction part, 12a, 12b ... Image quality amount calculation part, 13 ... Image quality characteristic prediction part, 14 ... Image quality control parameter value calculation part, 15 ... Image reproduction part

Claims (7)

The identification of the original image based on the original image and the enhancement degree information indicating the enhancement degree of a specific component that affects the image quality of the original image and having the first enhancement degree set. First reproduced image generating means for generating a first reproduced image that is reproduced so that the component is enhanced at the first enhancement degree;
First image quality amount acquisition means for acquiring a first image quality amount representing the image quality of the first reproduced image;
Second image quality amount acquisition means for acquiring a second image quality amount representing the image quality of the original image;
Based on the first image quality amount, the second image quality amount, and the first enhancement level, the enhancement level set in the enhancement level information and the specific component of the original image An image quality characteristic acquisition means for acquiring an image quality characteristic of the original image in association with an image quality amount representing the image quality of the reproduced image reproduced so as to be emphasized at a degree;
Based on the image quality characteristic and the designated image quality amount representing the designated image quality, the second enhancement degree to be set in the enhancement degree information so that the image quality amount representing the image quality of the reproduced image becomes the designated image quality amount Emphasis degree acquisition means for acquiring
Based on the original image and the enhancement degree information in which the second enhancement degree is set, the second component reproduced so that the specific component of the original image is enhanced with the second enhancement degree. An image processing apparatus comprising: a second reproduction image generation unit that generates a reproduction image of the above.   The image processing apparatus according to claim 1, wherein the image quality characteristic acquisition unit acquires the image quality characteristic in which the enhancement degree and the image quality amount are associated with each other by a linear function. The first reproduction image generating means emphasizes the specific component of the original image with the other first enhancement degree based on the enhancement degree information in which another first enhancement degree is set. And further generating another first reproduced image reproduced as follows:
The first image quality amount acquisition means further acquires another first image quality amount representing the image quality of the other first reproduction image,
The image processing according to claim 1, wherein the image quality characteristic acquisition unit acquires the image quality characteristic further based on the other first image quality amount and the other first enhancement degree. apparatus.   The image processing apparatus according to claim 3, wherein the image quality characteristic acquisition unit acquires the image quality characteristic in which the enhancement degree and the image quality amount are associated with each other by a non-linear function.   5. The image quality characteristic acquisition unit acquires the image quality characteristic in which the degree of enhancement and the image quality amount are associated with each other by a monotone increasing function or a monotone decreasing function. An image processing apparatus according to claim 1.   Each of the first reproduction image generation unit and the second reproduction image generation unit performs the enhancement related to at least one of the luminance, chromaticity, contrast difference, and frequency of the original image. The image processing apparatus according to claim 1, wherein a reproduced image and the second reproduced image are generated. On the computer,
The identification of the original image based on the original image and the enhancement degree information indicating the enhancement degree of a specific component that affects the image quality of the original image and having the first enhancement degree set. A function of generating a first reproduced image that is reproduced so that the component is enhanced at the first enhancement degree;
A function of obtaining a first image quality amount representing an image quality of the first reproduced image;
A function of obtaining a second image quality amount representing the image quality of the original image;
Based on the first image quality amount, the second image quality amount, and the first enhancement level, the enhancement level set in the enhancement level information and the specific component of the original image A function of acquiring image quality characteristics of the original image in association with an image quality amount representing the image quality of the reproduced image reproduced to be emphasized at a degree;
Based on the image quality characteristic and the designated image quality amount representing the designated image quality, the second enhancement degree to be set in the enhancement degree information so that the image quality amount representing the image quality of the reproduced image becomes the designated image quality amount With the ability to get
Based on the original image and the enhancement degree information in which the second enhancement degree is set, the second component reproduced so that the specific component of the original image is enhanced with the second enhancement degree. Program that realizes the function to generate a reproduction image of

Images