JP5810593B2 - Image processing apparatus, imaging apparatus, and program - Google Patents

Description

  The present invention relates to an image processing device, an imaging device, and a program.

  2. Description of the Related Art Conventionally, a technique for performing smoothing on color difference components of an image in order to improve the resolution of the image is known. As an example, Patent Document 1 performs smoothing by extracting a local fluctuation component from color information of image data, and adding a luminance texture component artificially generated from the fluctuation component to the luminance information. However, a technique for improving the resolution of an image is disclosed.

Japanese Patent No. 4595939

  In the conventional image processing, since the texture component is not generated in consideration of human visual characteristics, there is still room for improvement in the texture of the image after smoothing the color difference component.

  In view of the above circumstances, there is provided means for generating an image having a more natural texture while smoothing color difference components.

The image processing apparatus of one embodiment of the present invention includes a flat smoothing unit, an extraction unit, a calculation unit, a correction unit. The smoothing unit smoothes the color difference component of the input image. The extraction unit calculates a difference between the color difference component before smoothing and the color difference component after smoothing, and calculates the amount of change in saturation from the difference . The calculation unit calculates the saturation and the hue angle from the smoothed color difference component, and calculates the ratio of the luminance change amount to the saturation change amount from the saturation and the hue angle . The correction unit calculates a luminance correction value based on the saturation change amount calculated by the extraction unit and the ratio of the luminance change amount to the saturation change amount calculated by the calculation unit, and the input image is calculated using the correction value. The luminance component of is corrected.

The ratio of luminance variation with respect to the change amount of the saturation, the color phase angle may be those values as compared to other ranges is reduced in the range of 135 degrees from 90 degrees.

The ratio of the amount of change in luminance to the amount of change in saturation described above gives a change in luminance in the positive direction with respect to the change in saturation in the positive direction of the color difference coordinate of the color difference component after smoothing, and also in the negative direction of the color difference coordinate. it may be shall give brightness changes in the negative direction with respect to the saturation change.

  Here, an imaging apparatus including the above-described image processing apparatus, a program and a program storage medium that causes a computer to operate as the above-described image processing apparatus, and an operation of the above-described image processing apparatus expressed in a method category are also included in the present invention. This is effective as a specific embodiment.

An image having a more natural texture can be generated while smoothing the color difference component.

The figure which shows the structural example of the image processing apparatus in one Embodiment. Illustration of noise appearance considering the Helmholtz-Kohlrausch effect The figure which shows the experimental result of the 1st experiment The figure which shows the experimental result of 2nd experiment (C ^* _ab = 10) The figure which shows the experimental result of 2nd experiment (C ^* _ab = 20) The figure which shows the experimental result of 2nd experiment (C ^* _ab = 30) Flow chart showing an example of noise reduction processing in the first embodiment Overview of an example of noise reduction processing in the first embodiment The figure which shows an example of the data table of a brightness | luminance gradient coefficient typically Diagram showing the correlation between saturation and luminance in the luminance gradient Diagram showing the correlation between saturation and luminance in the luminance gradient Overview of noise reduction processing example in the second embodiment The figure which shows the structural example of the imaging device in 3rd Embodiment.

<Description of First Embodiment>
FIG. 1 is a diagram illustrating a configuration example of an image processing apparatus according to the first embodiment. The image processing apparatus according to the first embodiment is a personal computer in which an image processing program for performing noise reduction processing on an input image is installed.

  A computer 11 illustrated in FIG. 1 includes a data reading unit 12, a storage device 13, a CPU 14, a memory 15, an input / output I / F 16, and a bus 17. The data reading unit 12, the storage device 13, the CPU 14, the memory 15, and the input / output I / F 16 are connected to each other via a bus 17. Further, an input device 18 (keyboard, pointing device, etc.) and a monitor 19 are connected to the computer 11 via an input / output I / F 16. The input / output I / F 16 receives various inputs from the input device 18 and outputs display data to the monitor 19.

  The data reading unit 12 is used when reading image data or a program from the outside. The data reading unit 12 communicates with, for example, a reading device (such as a reading device for an optical disk, a magnetic disk, or a magneto-optical disk) that acquires data from a removable storage medium, or an external device in accordance with a known communication standard. A communication device (USB interface, wired / wireless LAN module, etc.) to be performed.

  The storage device 13 is, for example, a storage medium such as a hard disk or a nonvolatile semiconductor memory. The storage device 13 stores the above-described image processing program and various data (such as a data table of luminance gradient coefficients described later) necessary for executing the program. The storage device 13 may store image data read from the data reading unit 12 and image data that has been subjected to noise reduction processing by an image processing program.

  The CPU 14 is a processor that comprehensively controls each unit of the computer 11. The CPU 14 operates as a smoothing unit 21, an extraction unit 22, a calculation unit 23, and a correction unit 24 by executing the image processing program (the operations of the smoothing unit 21, the extraction unit 22, the calculation unit 23, and the correction unit 24). Will be described later).

  The memory 15 temporarily stores various calculation results in the image processing program. The memory 15 is, for example, a volatile SDRAM.

  Next, an operation example of the image processing apparatus in the first embodiment will be described.

  The image processing apparatus according to the first embodiment reduces color noise of an image by smoothing the color difference component of the input image. On the other hand, the image processing apparatus according to the first embodiment generates a texture component in a pseudo manner in consideration of human visual characteristics and performs correction for adding the texture component to the luminance component of the input image.

  Here, the reason why the above processing is performed will be described. In general, it is known that noise in the luminance component of an image produces a favorable effect such as improving the resolution of the image and contributing to a texture such as film shooting. On the other hand, noise (color noise) of the color difference component of the image is preferably suppressed by image processing because it greatly reduces the resolution of the image.

  However, in terms of human visual characteristics, brightness is perceived differently depending on color, and even with the same luminance value, the higher the saturation, the brighter the perception (Helmholtz-Kohlrausch effect). Therefore, if only the color difference component of the image is simply smoothed, the image after correction is perceived by the viewer so as to reduce the texture due to the luminance component.

FIG. 2 is an explanatory view of the appearance of noise in consideration of the Helmholtz-Kohlrausch effect. As shown in FIG. 2A, consider a case where there is fluctuation (noise) on the color difference plane (a ^* b ^* ) when the luminance (L ^* ) is constant. At this time, if there is a fluctuation on the color difference plane, the viewer's sense of brightness also changes. Therefore, although the brightness of the image is constant, the viewer can also perceive brightness fluctuation (noise) (see FIG. 2B).

  The inventor conducted the following two experiments in order to confirm the above matters.

  In the first experiment, two color patches having the same magnitude of color noise and different colors were displayed on the display. And the psychophysical experiment of the one-pair comparison method which makes a test subject choose the direction which feels that noise is large.

FIG. 3 is a diagram showing an experimental result of the first experiment. FIG. 3 shows how noise appears at each position on the color difference plane (a ^* b ^* ) of the CIE L ^* a ^* b ^* color system. In FIG. 3, the center of the cross indicates the coordinates on the color difference plane of the color patch, and the cross corresponding to the color patch is shown larger as the subject who feels that the noise is large.

It can be seen from FIG. 3 that the visibility of noise varies depending on the background color (color patch). Also, from FIG. 3, noise is relatively less perceivable in achromatic colors (a ^* = b ^* = 0), and chromatic colors (for example, blue (third quadrant of the color difference plane) or red purple (fourth quadrant of the color difference plane)). ) Also shows that noise is easily perceived.

In the second experiment, an achromatic reference patch (L ^* = 51.56) and a chromatic patch were displayed on the display. Then, a psychophysical experiment was performed in which the subject adjusted the luminance (L ^* ) of the chromatic color patch so as to have the same brightness as the reference patch.

4-6 is a figure which shows the experimental result of 2nd experiment. 4 shows the experimental results when the saturation C ^* _ab = 10 of the chromatic color patch, FIG. 5 shows the experimental results when the saturation C ^* _ab = 20 of the chromatic color patch, and FIG. 6 shows the chromatic color patch. It is an experimental result when the saturation C ^* _ab = 30. 4 to 6, the vertical axis represents luminance (L ^* ), and the horizontal axis represents hue angle. 4 to 6, the luminance of the reference patch is indicated by a solid line, and the luminance change of the chromatic color patch adjusted by the subject is indicated by a broken line.

4 to 6, it can be seen that the luminance L ^{* of the} chromatic color patch perceived to have the same brightness as the reference patch differs depending on the hue angle. In the hue angle range of 90 to 135 degrees, the influence of the Helmholtz-Kohlrausch effect is relatively small in any saturation. However, in other hue angle ranges, it can be seen that unless the luminance L ^{* of the} chromatic color patch is made smaller than that of the reference patch, they cannot be perceived as the same brightness. 4 to 6, it can be seen that, generally, when the saturation is increased even at the same hue angle, the brightness of the chromatic color patch cannot be perceived as the same brightness as the reference patch unless the luminance L ^* is reduced.

  As described above, since the degree of the Helmholtz-Kohlrausch effect varies depending on the saturation and hue, when the saturation and hue change due to noise, the brightness perceived by the viewer also changes. It is considered that this difference in brightness affects the difference in noise perception in the first experiment. This is because, in human visual characteristics, the perception sensitivity of high frequency components of brightness is higher than that of color differences. For example, the Helmholtz-Kohlrausch effect is hardly seen in any saturation in the range of hue 90 ° to 135 °. Therefore, it is suggested that the colors included in this range are less likely to perceive noise than other regions even if the saturation and hue change due to noise. This is consistent with the experimental results of the first experiment.

  From the above, it can be seen that the image quality can be further improved by correcting the luminance in consideration of the Helmholtz-Kohlrausch effect when smoothing the color difference component of the input image.

  Next, an example of noise reduction processing according to the first embodiment will be described with reference to the drawings. FIG. 7 is a flowchart illustrating an example of noise reduction processing in the first embodiment. FIG. 8 is a schematic diagram of an example of noise reduction processing in the first embodiment. 7 and 8 are started when the CPU 14 executes a program in response to a program execution instruction from the user.

  Step # 101: The CPU 14 acquires data of an input image to be subjected to noise reduction processing from the data reading unit 12. The input image data acquired in # 101 is recorded in the storage device 13 or the memory 15 under the control of the CPU. If input image data is stored in the storage device 13 in advance, the CPU 14 may omit the process of # 101.

Here, the input image of the first embodiment is a color image that has been subjected to color interpolation processing, and is expressed in a color space (YCbCr, CIE L ^* a ^* b ^*, etc.) that includes a luminance component and a color difference component. Is done. In the first embodiment, an example of input image data whose color space is CIE L ^* a ^* b ^* will be described. In the following description, the luminance channel of the input image is referred to as luminance information (L ^* ), and the color difference channel of the input image is referred to as color difference information (a ^* , b ^* ). When the image acquired in # 101 is another color space (for example, RGB), the CPU 14 performs a color space conversion process.

  Step # 102: The smoothing unit 21 performs a smoothing process on the color difference information (# 101) of the input image using a smoothing filter (for example, a bilateral filter or an epsilon filter).

The color difference fluctuation components (da ^* , db ^* ) are color difference noises (fluctuations) removed from an image by smoothing.

Step # 104: The computing unit 23 converts the color difference variation component (da ^* , db ^* ) acquired in # 103 from a Cartesian coordinate system (Cartesian coordinates) to a polar coordinate system. In the process of # 104, the color difference variation components (da ^* , db ^* ) indicated by the coordinates of the color difference plane are converted into the saturation and hue angle (dC ^* , dh ^* ) formats.

The luminance gradient of the above-mentioned texture component is a parameter indicating the saturation dependency of luminance when the lightness is equal in accordance with the Helmholtz-Kohlrausch effect. As an example, the luminance gradient of the texture component can be expressed as a change in luminance (ΔL ^* ) with respect to a change in saturation (ΔC ^* _ab ) (ΔL ^* / ΔC ^* _ab ).

  Here, the calculation unit 23 in the first embodiment obtains the luminance gradient using the data table of the luminance gradient coefficient stored in advance in the storage device 13. FIG. 9 is a diagram schematically illustrating an example of a data table of luminance gradient coefficients.

The luminance gradient coefficient data table stores the correspondence between the luminance coefficient and the hue angle for equal brightness. In the above data table, luminance coefficients are stored in increments of 45 degrees of hue angle. In the above data table, the correspondence relationship between the luminance coefficient and the hue angle changes in the range of saturation 0-10, the range of saturation 10-20, and the range of saturation 20-30, respectively. . The data table of FIG. 9 is generated based on L ^* = 51.56 based on the experimental results (FIGS. 4 to 6) of the second experiment described above.

In the range where the hue angle in FIG. 9 is 90 to 135 degrees, the luminance gradient (ΔL ^* / ΔC ^* _ab ) is smaller than any other range, and is almost zero. Further, the values when the luminance gradient (ΔL ^* / ΔC ^* _ab ) takes a negative value are both small. Therefore, it can be considered that almost (ΔL ^* / ΔC ^* _ab ) ≧ 0. That is, in the luminance gradient, the luminance increases as the saturation increases.

Further, the calculation unit 23 in # 106 may obtain the luminance gradient (ΔL ^* / ΔC ^* _ab ) in the following manner.

  Note that the luminance gradient gives a luminance change in the positive direction with respect to a saturation change in the positive direction of the color difference coordinates, and also gives a luminance change in the negative direction with respect to a saturation change in the negative direction of the color difference coordinates. 10 and 11 are diagrams showing the correlation between saturation and luminance in the luminance gradient. 10 and 11, the vertical axis represents luminance, and the horizontal axis represents saturation.

  FIG. 10 shows a state in which fluctuation is applied in the increasing direction (positive direction) of saturation. In this case, the line of equal lightness decreases with increasing saturation, so that the viewer perceives the object darkly. Therefore, the luminance gradient is balanced by giving a luminance change in the positive direction.

  On the other hand, FIG. 11 shows a state in which fluctuation is applied in the decreasing direction of the saturation (negative direction). In this case, the line of equal lightness rises as the saturation decreases, so that the viewer perceives the subject brightly. Therefore, the luminance gradient is balanced by giving a luminance change in the negative direction.

Step # 107: The computing unit 23 obtains the texture component (dL ^* ) by multiplying the saturation fluctuation dC ^* (# 104) by the luminance gradient (# 106).

Step # 108: The computing unit 23 multiplies the texture component (dL ^* ) obtained in # 107 by a calibration correction coefficient k (where 0 <k <1). The correction coefficient k is for preventing over-correction of the texture component, and is corrected so as to reduce the value of dL ^* of # 107. For example, as the correction coefficient k, a value determined by subjective evaluation according to the model of the camera that captured the input image, the image processing mode, or the like is employed.

Step # 109: The correction unit 24 corrects the luminance information (L ^* ) of the input image of # 101 by adding the texture component (dL ^* ) after adjustment of # 108. Note that the luminance information after the correction of # 109 is expressed as L ^* ′.

  Thereafter, the CPU 14 may store the output image data in the storage device 13 or may display the output image on the monitor 19. Above, description by FIG. 7, FIG. 8 is complete | finished.

  Hereinafter, the operational effects of the first embodiment will be described. The image processing apparatus according to the first embodiment performs smoothing on the color difference information (# 102), and at the same time, the texture component (# 107) corresponding to the influence of the color difference variation component (# 103) on the luminance in the color reproduction of the input image. ) Then, the image processing apparatus corrects the luminance component of the input image using the texture component (# 109).

  As a result, in the output image (# 110) after the noise reduction processing, the color noise is suppressed by smoothing the color difference component, and the luminance component is corrected in consideration of the Helmholtz-Kohlrausch effect. It becomes the image which has.

<Description of Second Embodiment>
FIG. 12 is a schematic diagram of an example of noise reduction processing in the second embodiment. The second embodiment is a modification of the first embodiment, and FIG. 12 corresponds to FIG. 8 described above. In the following description, elements common to the first embodiment are denoted by the same reference numerals, and redundant description is omitted.

In the image processing apparatus according to the second embodiment, a data table of a plurality of brightness gradient coefficients generated under different brightness conditions is stored in the storage device 13 in advance. The calculation unit 23 in the second embodiment uses a data table of luminance gradient coefficients to be referred to in accordance with the value of luminance information (L ^* ) in the process corresponding to # 106 (# 106 ′ in FIG. 12). To change. In the second embodiment, in addition to the same effects as in the first embodiment, the texture component is finely adjusted according to the value of L ^* , so that the resolution of the output image is further improved. Can do.

<Description of Third Embodiment>
FIG. 13 is a diagram illustrating a configuration example of the imaging apparatus according to the third embodiment. The third embodiment is an example in which the image processing apparatus of the first embodiment or the second embodiment is mounted on the electronic camera 31, and the image processing apparatus acquires an input image from the imaging unit 33 of the electronic camera 31.

  The electronic camera 31 includes a photographic lens 32, an imaging unit 33, an image processing engine 34, a first memory 35 and a second memory 36, a recording I / F 37, and an operation unit 38. Here, the imaging unit 33, the first memory 35, the second memory 36, the recording I / F 37, and the operation unit 38 are each connected to the image processing engine 34.

  The imaging unit 33 is a module that captures (captures) an image of a subject formed by the photographing lens 32. For example, the imaging unit 33 includes an imaging device that performs photoelectric conversion, an analog front-end circuit that performs analog signal processing, and a digital front-end circuit that performs A / D conversion and digital signal processing.

  The image processing engine 34 is a processor that comprehensively controls the operation of the electronic camera 31. For example, the image processing engine 34 causes the imaging unit 33 to capture an image in response to a user's shooting instruction input in the shooting mode. Further, the image processing engine 34 operates in the same manner as the CPU 14 (smoothing unit 21, extraction unit 22, calculation unit 23, correction unit 24) according to one embodiment by executing a program.

  The first memory 35 is a memory that temporarily stores image data, and is, for example, an SDRAM that is a volatile storage medium. The second memory 36 is a memory that stores a program executed by the image processing engine 34, and is a non-volatile memory such as a flash memory.

  The recording I / F 37 has a connector for connecting a nonvolatile storage medium 39. The recording I / F 37 writes / reads image data to / from the storage medium 39 connected to the connector. The storage medium 39 is, for example, a hard disk or a memory card incorporating a semiconductor memory. In FIG. 13, a memory card is illustrated as an example of the storage medium 39.

  The operation unit 38 has a plurality of switches that accept user operations. The operation unit 38 includes, for example, a release button for receiving a recording still image shooting instruction.

  Hereinafter, an operation example of the electronic camera 31 in the third embodiment will be briefly described. In the electronic camera 31 of the third embodiment, the imaging unit 33 captures an image in response to a user's shooting instruction input. Thereby, an input image corresponding to the process of # 101 in FIG. 7 is acquired.

  Then, the image processing engine 34 performs noise reduction processing on the image data by the same method as # 103 to # 110 in FIG. Thereafter, the output image data is recorded in the storage medium 39 via the recording I / F 37. The image processing engine 34 may display the output image on a display unit (not shown). In the third embodiment, substantially the same effect as that of the first embodiment or the second embodiment can be obtained.

<Supplementary items of the embodiment>
(Supplementary item 1): In the above embodiment, the example in which the texture component is obtained from the coefficient of the luminance gradient and the saturation of the fluctuation component (saturation fluctuation) has been described, but the hue of the fluctuation component (hue fluctuation) is further described. May be considered.

Here, the saturation fluctuation is dC ^* , and the hue fluctuation is dh. Further, the coefficient of the luminance gradient due to saturation is ΔL ^* _C, and the coefficient of the luminance gradient in the hue direction is ΔL ^* _H. The coefficient of the luminance gradient in the hue direction indicates a change in luminance with respect to the distance in the hue direction on the color difference plane, and is not a change in brightness with respect to the hue angle.

At this time, the texture component dL ^* _C due to saturation fluctuation and the texture component dL ^* _H due to hue fluctuation can be obtained by the following equations (2) and (3). Then, the final texture component dL ^* can be obtained by integrating both as shown in the following equation (4).

  (Supplementary item 2): In the above embodiment, the data table of the luminance gradient coefficient may store the correspondence between the coordinate value of the color difference plane in the Cartesian coordinate system and the luminance gradient. In this case, the calculation unit 23 can omit conversion of the color difference variation component and the smoothed color difference component into polar coordinates.

(Supplementary Item 3): In the above embodiment, in order to finely adjust the luminance noise of the output image, the luminance information L ^* or the luminance information L ^* ′ may be smoothed.

  (Supplementary Item 4): In the first and second embodiments described above, the example in which the image processing apparatus is a personal computer has been described. However, the image processing apparatus of the present invention may be an electronic device such as a printer or a photo viewer.

  (Supplementary item 5): In the third embodiment, the case of an electronic camera has been described as an example of an imaging apparatus. However, the imaging apparatus of the present invention may be a scanner. The imaging apparatus of the present invention may include a microscope or a telescope optical system.

  (Supplementary Item 6): In the above-described embodiment, the example in which each function of the image processing apparatus is realized by software by a program has been described. However, in the present invention, the functions of the reduced / smoothing unit 21, the extraction unit 22, the calculation unit 23, and the correction unit 24 may be realized in hardware using an ASIC.

  (Supplementary Item 7): In the above embodiment, the texture of the image before and after the image processing is corrected by taking into consideration the effect of the color difference variation component (high pass component) on the brightness. However, the present invention is not limited to the above-described embodiment, and a color difference variation component is extracted, and an image after color correction or tone correction is performed in consideration of the influence on brightness by the extracted color difference variation component. The resolution may be corrected.

  That is, an extraction unit that extracts a color difference variation component included in an input image, a calculation unit that obtains a texture component corresponding to the effect of the color difference variation component on luminance in color reproduction of the input image, and the above-described texture component are used. In addition, an image processing apparatus and an imaging apparatus (or an image processing program) including a correction unit that emphasizes the edge of the input image are also included in the technical scope of the present invention. According to Supplementary Item 7, since the edge of the input image is emphasized in consideration of human visual characteristics, it is possible to make the color reproduction and the sense of resolution of the image after edge enhancement more natural.

As an example, the feature of supplementary matter 7 will be described by applying it to the configuration of the above embodiment. The extraction unit 22 and the calculation unit 23 operate in the same manner as in the above embodiment. Thereby, the texture component dL ^* is obtained by the calculation unit 23. Then, the correction unit 24 performs a known edge enhancement process. At this time, the correction unit 24 may adjust the degree of edge enhancement at each position of the image so that the influence of the texture component dL ^* is leveled. Such edge enhancement processing may be performed on some or all channels of the input image. Further, edge enhancement processing may be performed on an input image converted into another color space. In Supplementary Item 7, if the color difference variation component is extracted by a high-pass filter or the like, the color difference component of the input image need not be smoothed.

  (Supplementary Item 8): The experimental results of the first experiment and the second experiment disclosed in this specification are obtained when a 22-type LCD is adjusted according to the sRGB standard and observed from a distance of 50 cm. . In the case of carrying out the present invention, values obtained through experiments according to the environment may be used in different observation environments. Further, when implementing the present invention, an appropriate value (data table) may be used according to the resolution of the image, the number of pixels, and the output condition setting.

  From the above detailed description, features and advantages of the embodiments will become apparent. It is intended that the scope of the claims extend to the features and advantages of the embodiments as described above without departing from the spirit and scope of the right. Further, any person having ordinary knowledge in the technical field should be able to easily come up with any improvements and modifications, and there is no intention to limit the scope of the embodiments having the invention to those described above. It is also possible to use appropriate improvements and equivalents within the scope disclosed in.

DESCRIPTION OF SYMBOLS 11 ... Computer, 12 ... Data reading part, 13 ... Memory | storage device, 14 ... CPU, 21 ... Smoothing part, 22 ... Extraction part, 23 ... Calculation part, 24 ... Correction part, 31 ... Electronic camera, 33 ... Imaging part, 34. Image processing engine

Claims (7)

A smoothing unit that smoothes the color difference component of the input image;
An extraction unit that calculates a difference between the color difference component before smoothing and the color difference component after smoothing, and calculates a change in saturation from the difference ;
Calculating a saturation and a hue angle from the smoothed color difference component, and calculating a ratio of a luminance change amount to a saturation change amount from the saturation and the hue angle ; and
A brightness correction value is calculated from the change amount of saturation calculated by the extraction unit and the ratio of the change amount of brightness to the change amount of saturation calculated by the calculation unit, and the correction value calculates the brightness correction value. A correction unit for correcting the luminance component of the input image;
An image processing apparatus comprising: The image processing apparatus according to claim 1 .
Wherein the luminance variation with respect to the amount of change in saturation ratio, the color phase angle image processing apparatus value compared with other ranges is reduced in the range of 135 degrees from 90 degrees. The image processing apparatus according to any one of claims 1 or claim 2,
The ratio of the change amount of luminance to the change amount of saturation gives a luminance change in the positive direction with respect to the saturation change in the positive direction of the color difference coordinate of the color difference component after the smoothing, and the negative direction of the color difference coordinate Image processing apparatus that gives a luminance change in the negative direction with respect to the saturation change of. A smoothing unit that smoothes the color difference component of the input image;
An extraction unit that calculates a difference between the color difference component before smoothing and the color difference component after smoothing, and calculates a change in saturation from the difference ;
Calculating a saturation and a hue angle from the smoothed color difference component, and calculating a ratio of a luminance change amount to a saturation change amount from the saturation and the hue angle ; and
A brightness correction value is calculated from the change amount of saturation calculated by the extraction unit and the ratio of the change amount of brightness to the change amount of saturation calculated by the calculation unit, and the correction value calculates the brightness correction value. A correction unit for edge enhancement of the input image;
An image processing apparatus comprising: An imaging unit that captures an input image;
An image processing apparatus according to any one of claims 1 to 4 ,
An imaging apparatus comprising: On the computer,
A smoothing step for smoothing the color difference component of the input image;
An extraction step of calculating a difference between the color difference component before smoothing and the color difference component after smoothing, and calculating a change in saturation from the difference ;
Calculating a saturation and a hue angle from the smoothed color difference component, and calculating a ratio of a luminance change amount to a saturation change amount from the saturation and the hue angle ; and
A luminance correction value is calculated from the amount of change in saturation calculated in the extraction step and the ratio of the amount of change in luminance to the amount of change in saturation calculated in the calculation step, and the correction value calculates the luminance correction value. A correction process for correcting the luminance component of the input image;
A program that executes On the computer,
A smoothing step for smoothing the color difference component of the input image;
An extraction step of calculating a difference between the color difference component before smoothing and the color difference component after smoothing, and calculating a change in saturation from the difference ;
Calculating a saturation and a hue angle from the smoothed color difference component, and calculating a ratio of a luminance change amount to a saturation change amount from the saturation and the hue angle ; and
A luminance correction value is calculated from the amount of change in saturation calculated in the extraction step and the ratio of the amount of change in luminance to the amount of change in saturation calculated in the calculation step, and the correction value calculates the luminance correction value. A correction process for edge enhancement of the input image;
A program that executes

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