JP2013127804A - Image processing program, image processing device and image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve gradation of a bright part and a dark part, while keeping contrast of appearance and suppressing change in a color tone and color saturation.SOLUTION: The image processing program includes: an image data acquisition step; a gradation conversion processing step for performing gradation conversion processing on image data, according to input/output characteristics defined by a gradation curve having characteristics to which a characteristic of weakening contrast is added, at an intermediate part of the gradation; and a correction step for performing correction for emphasizing local contrast of the image, using a gain curve in which a degree of emphasis changes according to luminance information of a pixel to be processed, on the image data on which the gradation conversion processing is performed. At the correction step, the brighter an attention pixel is than pixels around the attention pixel, the higher gain of the attention pixel is made to emphasize brightness, and the darker the attention pixel is than the pixels around the attention pixel, the lower the gain of the attention pixel is made to emphasize darkness, and when the attention pixel is darker than the pixels around, the correction is performed using the gain curve which raises the degree of emphasis.

Description

  The present invention relates to an image processing program for performing image processing on image data to be processed, an image processing apparatus, and an image processing method.

  To output image data generated by an imaging device such as an electronic camera to an output device such as a CRT monitor or a printer, a gradation conversion process using a gradation curve corresponding to the output device in order to improve the appearance. Has been done. If such gradation conversion processing is not performed, it will be difficult to see due to flare of the output device, black float, external light reflection and the like. In the gradation conversion process, a so-called S-shaped gradation curve is used in addition to the gradation curve corresponding to the output device. By adjusting the contrast with this S-shaped gradation curve, a sharp output image can be obtained in the output device (see, for example, Patent Document 1).

  In addition, in order to improve the appearance, contour enhancement processing that enhances sharpness is also performed. The contour enhancement processing includes a method of enhancing a contour by adding a high-frequency component to original image data, a method of enhancing a contour using a so-called contour enhancement filter, and the like (for example, see Patent Document 2).

JP 2004-222076 A Japanese Patent No. 3512581

  In the above-described tone conversion process of Patent Document 1, while it is possible to enhance the contrast, there is a case where the contrast of the bright portion gradation is lowered or the dark portion gradation is crushed darkly. In addition, when gradation conversion processing using an S-shaped curve is performed on each of the R, G, and B values, the hue and saturation of each of the light portion gradation, the intermediate portion gradation, and the dark portion gradation are obtained. There was a problem of changing.

  Furthermore, in the above-described contour emphasis processing of Patent Document 2, when the contour emphasis processing is performed with a large radius, there is a problem that a change in saturation is conspicuous and a bright portion gradation is easily overexposed.

  The present invention has been made in view of the above problems, and is capable of improving bright part gradation and dark part gradation while maintaining the apparent contrast and suppressing changes in hue and saturation. The purpose is to do.

  An image processing program according to the present invention is an image processing program for realizing image processing on image data to be processed by a computer, wherein the contrast is obtained in an acquisition step of acquiring the image data and an intermediate portion of gradation. A gradation conversion processing step for performing gradation conversion processing on the image data in accordance with input / output characteristics defined by a gradation curve having characteristics that take into account weakening characteristics; and the image data subjected to the gradation conversion processing A correction step for performing correction for enhancing local contrast indicating local contrast of an image using a gain curve whose degree of enhancement changes according to luminance information of a pixel to be processed, and In the step, as the target pixel is brighter than the surrounding pixels, the gain of the target pixel is increased to increase the brightness. In addition, as the pixel of interest is darker than the surrounding pixels, the gain of the pixel of interest is lowered to enhance the darkness, and when the pixel of interest is darker than the surrounding pixels, the pixel of interest is The correction is performed using the gain curve that increases the degree of enhancement as compared with a case where the pixel is brighter than a pixel.

  In the correction step, image data of a blurred image is created based on the image data, and based on a value indicating a difference between a luminance value in the image data and a luminance value in the image data of the blurred image, The correction may be performed.

  Further, in the correction step, image data of a blurred image is created based on the image data, and as a value indicating a difference between a luminance value in the image data and a luminance value in the image data of the blurred image increases, The correction may be performed using the gain curve that reduces the degree of enhancement.

  In the correction step, image data of a blurred image is created based on the image data, and the smaller the value indicating the difference between the luminance value in the image data and the luminance value in the image data of the blurred image is, The correction may be performed using the gain curve that increases the degree of enhancement.

  Further, in the gradation conversion processing step, a plurality of gradation curves having characteristics that take into account the characteristic of weakening the contrast in an intermediate portion of gradation, and the contrast added to each gradation curve is weakened The image data is subjected to gradation conversion processing according to input / output characteristics defined by a gradation curve selected from a plurality of gradation curves having different characteristics, and the correction step is selected in the gradation conversion processing step. The correction may be performed using a gain curve whose degree of enhancement changes according to the input / output characteristics of the gradation curve.

  The gradation curve may include an S-shaped characteristic.

  The gradation curve may include characteristics corresponding to an external output device.

  In addition, a configuration obtained by converting the configuration related to the above invention into an image processing apparatus and an image processing method for performing image processing on image data to be processed is also effective as a specific aspect of the present invention.

  According to the present invention, it has been made in view of the above problems, and it is possible to improve the bright gradation and the dark gradation while maintaining the apparent contrast and suppressing the change in hue and saturation. Image processing can be performed.

It is a figure which shows the structure of the electronic camera 1 of 1st Embodiment. It is a functional block diagram of electronic camera 1 of a 1st embodiment. It is a flowchart which shows the operation | movement at the time of imaging | photography of the electronic camera 1 of 1st Embodiment. It is a figure explaining a gradation curve. It is another figure explaining a gradation curve. It is a figure explaining a low pass filter. Diagram explaining the gamma curve Diagram explaining gamma curve determination It is another figure explaining a gradation curve. It is a flowchart which shows the operation | movement at the time of imaging | photography of the electronic camera 1 of 2nd Embodiment. It is another figure explaining a gradation curve.

<First Embodiment>
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings. In the first embodiment, a single-lens reflex type electronic camera to which the image processing program of the present invention is applied will be described as an example.

  FIG. 1 is a diagram illustrating a configuration of an electronic camera 1 according to the first embodiment. As shown in FIG. 1, an electronic camera 1 includes a photographing lens 2, an aperture 3, a quick return mirror 4, a sub mirror 5, a diffusion screen 6, a condenser lens 7, a pentaprism 8, a beam splitter 9, an eyepiece lens 10, and an imaging lens. 11, a photometric sensor 12, a shutter 13, an image sensor 14, and a focus detection unit 15.

  The photometric sensor 12 is, for example, a five-part photometric sensor. The imaging element 14 is a semiconductor device such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor). For example, the focus detection unit 15 detects a focus state of the photographic lens 2 by performing phase difference type focus detection. The electronic camera 1 detects the focus state of the photographic lens 2 by performing contrast-type focus detection based on the luminance detected by the photometric sensor 12.

  The electronic camera 1 further includes a monitor 16 such as a liquid crystal monitor that displays an image generated by imaging, and a control unit 17 that controls each unit. The control unit 17 includes a memory (not shown) therein, and records a program for controlling each unit in advance.

  When not photographing, that is, when photographing is not performed, the quick return mirror 4 is disposed at an angle of 45 ° as shown in FIG. The light beam that has passed through the photographing lens 2 and the diaphragm 3 is reflected by the quick return mirror 4 and guided to the eyepiece lens 10 through the diffusion screen 6, the condenser lens 7, the pentaprism 8, and the beam splitter 9. The user confirms the composition by viewing the subject image through the eyepiece 10. On the other hand, the light beam split upward by the beam splitter 9 is re-imaged on the imaging surface of the photometric sensor 12 via the imaging lens 11. Further, the light beam transmitted through the quick return mirror 4 is guided to the focus detection unit 15 via the sub mirror 5.

  On the other hand, at the time of photographing, the quick return mirror 4 is retracted to the position indicated by the broken line, the shutter 13 is opened, and the light flux from the photographing lens 2 is guided to the image sensor 14.

  FIG. 2 is a functional block diagram of the electronic camera 1 according to the first embodiment. 2, the electronic camera 1 includes a timing generator 20, a signal processing unit 21, an A / D conversion unit 22, a buffer memory 23, a bus 24, a card interface 25, and a compression / decompression unit in addition to the configuration of FIG. 26, each part of the image display unit 27 is provided. The timing generator 20 supplies output pulses to the image sensor 14. The image data generated by the image sensor 14 is temporarily stored in the buffer memory 23 via the signal processing unit 21 (including a gain adjustment unit corresponding to the imaging sensitivity) and the A / D conversion unit 22. The buffer memory 23 is connected to the bus 24. The bus 24 is connected to the card interface 25, the control unit 17, the compression / decompression unit 26, and the image display unit 27 described in FIG. The card interface 25 is connected to a removable memory card 28 and records image data on the memory card 28. The control unit 17 is connected to a switch group 29 (including a release button (not shown)) of the electronic camera 1, a timing generator 20, and a photometric sensor 12. Further, the image display unit 27 displays an image or the like on the monitor 16 provided on the back surface of the electronic camera 1.

  The operation at the time of photographing of the electronic camera 1 having the above-described configuration will be described using the flowchart shown in FIG.

  In step S <b> 1, the control unit 17 determines whether or not the user has instructed to start shooting via the switch group 29. If the control unit 17 determines that an instruction to start photographing is given, the process proceeds to step S2.

  In step S <b> 2, the control unit 17 controls each unit and captures a subject image with the image sensor 14 to generate image data. Image data generated by the imaging device 14 is temporarily stored in the buffer memory 23 via the signal processing unit 21 and the A / D conversion unit 22.

  In step S3, the control unit 17 reads the image data from the buffer memory 23 and performs normal image processing. Normal image processing includes white balance adjustment, interpolation processing, color tone correction processing, and the like. Since the specific method of each process is the same as that of a well-known technique, description is abbreviate | omitted.

  In step S4, the control unit 17 selects the gradation curve G1. The gradation curve G1 is used for gradation conversion processing performed in step S5 described later, and is a gradation curve having a known S-shaped characteristic in a gradation curve corresponding to an output device such as a CRT. is there. The control unit 17 records in advance two types of gradation curves (G1, G2) shown in FIGS. 4 and 5 in an internal memory (not shown).

  In step S5, the control unit 17 performs gradation conversion processing on the image data subjected to image processing in step S3 according to the gradation curve G1 selected in step S4. The details of the gradation conversion process are the same as those of the known technique, and thus description thereof is omitted.

  In step S6, the control unit 17 selects the gradation curve G2. As shown in FIG. 5, the gradation curve G2 has a characteristic of weakening the contrast in the middle portion of the gradation as compared with the 1: 1 input / output (see the dotted line in FIG. 5).

  In step S7, the control unit 17 performs the second gradation conversion process on the image data that has been subjected to the first gradation conversion process in step S5, according to the gradation curve G2 selected in step S6. The details of the gradation conversion process are the same as those of the known technique, and thus description thereof is omitted. Note that the gradation is softened in the middle portion of the gradation by performing the gradation conversion processing according to the gradation curve G2 described above.

  In step S8, the control unit 17 performs local contrast enhancement processing on the image data that has been subjected to the second gradation conversion processing in step S7. The local contrast is a contrast in a local region of an image.

  The local contrast enhancement calculation in each pixel R [x, y], G [x, y], B [x, y] is performed by the following equations 1 to 6.

  Y in Equation 1 indicates the luminance value of the target pixel. Further, kr, kg, and kb in Equation 1 are predetermined coefficients. Lpw in Equation 2 is a low-pass filter around the pixel of interest, and this low-pass filter has the characteristics shown in FIG. This low-pass filter is a wide-width low-pass filter whose half-value width (d in FIG. 6) is 1/100 or more of the short side of the image. Therefore, Ylp in Equation 2 corresponds to a low-pass value obtained by performing a low-pass process on the luminance value Y, and thus a set of Ylp indicates a blurred image of the luminance image. Further, the gain in Expression 3 is a gain at the time of enhancement calculation, and GLUT in Expression 3 is a gain curve used at the time of enhancement calculation.

  As shown in FIG. 7, the gain curve GLUT is a gain curve having a different degree of emphasis during the emphasis calculation according to the value of (Y [x, y] −Ylp [x, y]). When the value of (Y [x, y] −Ylp [x, y]) is a positive value (when the target pixel is brighter than the surrounding pixels), the gain is increased to enhance the brightness. . On the other hand, when the value of (Y [x, y] −Ylp [x, y]) is a negative value (when the target pixel is darker than the surrounding pixels), the gain is lowered to enhance the darkness. . That is, the gain curve GLUT emphasizes the brightness by Expression 3 when the target pixel is brighter than the surrounding pixels, and emphasizes the darkness by Expression 3 when the target pixel is darker than the surrounding pixels. It has special characteristics.

  Note that the gain curve GLUT shown in FIG. 7 is an example, and the present invention is not limited to this example. Any shape may be used as long as the degree of enhancement is small when the target pixel is brighter than the surrounding pixels as compared with G0 in FIG. 7 which is a linear gain. For example, a straight line may be used instead of a curved line. Further, when the target pixel is darker than the surrounding pixels, it may have any shape. For example, contrary to the example of FIG. 7, the degree of enhancement when the pixel of interest is darker than the surrounding pixels may be smaller than G0 in FIG. 7, which is a linear gain.

  Further, the gain curve GLUT has a value of (Y [x, y] −Ylp [x, y]) when the value of (Y [x, y] −Ylp [x, y]) is a positive value. The degree of emphasis is determined to be smaller than when the value is a negative value. In general, when the gradation in the bright part is saturated, whiteout occurs. Therefore, in the bright portion, as described above, it is possible to prevent whiteout from being noticeable by reducing the degree of enhancement.

  As described in step S7, the gradation is softened by performing the gradation conversion processing according to the gradation curve G2, so that the local contrast is adjusted by appropriately setting the gain curve GLUT. The visual contrast can be maintained. The gain curve GLUT may be a fixed gain curve or a variable gain curve.

  For example, the control unit 17 may be configured to determine the gain curve GLUT according to the shooting mode (for example, “portrait mode”, “landscape mode”, etc.). For example, in the portrait mode, it is often unfavorable that the bright part gradations are over-exposed or the dark part gradations are black-out. Therefore, in the portrait mode, the control unit 17 determines a gain curve GLUT having a small enhancement degree in both the bright part and the dark part. In the landscape mode, a sharp image is often preferred. Therefore, in the landscape mode, the control unit 17 determines a gain curve GLUT having a high enhancement degree in both the bright part and the dark part.

  Furthermore, the control unit 17 may be configured to determine the gain curve GLUT according to the contrast level of the image or may be determined according to the image adjustment mode. Further, the gain curve GLUT may be determined according to the image determination result by scene analysis or face recognition. Thus, by appropriately determining the gain curve GLUT, it is possible to perform gradation conversion processing and local contrast enhancement processing optimized for an image.

  The control unit 17 may determine the gain curve GLUT based on a user operation via the switch group 29. For example, the control unit 17 displays a designation screen for designating characteristics at the time of image processing as shown in FIG. 8 on the image display unit 27. The user moves the slide bar via the switch group 29 and designates characteristics at the time of image processing. In the example of FIG. 8, the words “hard” or “natural” are used, but this is only an example, and what is the word that indicates the characteristics at the time of image processing according to the above-described gain curve GLUT? It may be anything. And the control part 17 determines the gain curve GLUT according to the characteristic at the time of the image process designated by the user. For example, in the example of FIG. 8, the gain curve GLUT having a lower overall enhancement degree is determined as the characteristic designated by the user is closer to “natural”, and the characteristic designated by the user is closer to “hard”. The gain curve GLUT having a large overall enhancement degree is determined. In the case where the user designates characteristics at the time of image processing, a preview screen may be provided as shown in FIG. 8 so that the user can confirm the result of image processing according to the designated characteristics.

  Further, the control unit 17 may determine the gradation curve G2 described in step S6 in association with the gain curve GLUT. For example, as shown in FIG. 9, a plurality of gradation curves G2a to G2c having different S-shaped characteristics are prepared, and one of the gradation curves can be selected in step S6. The gain curve GLUT may be determined according to the characteristics of the selected gradation curve. That is, the degree of local contrast enhancement processing in step S8 may be determined according to the degree of softening by the gradation conversion processing in step S7.

  The control unit 17 may select and use one of a plurality of pre-recorded curves for each of the gradation curve G2 described in step S6 and the gain curve GLUT described in step S8. The gradation curve and the gain curve may be appropriately adjusted and used.

In step S9, the control unit 17 records the image data subjected to the local contrast enhancement process in step S8 on the memory card 28 via the card interface 25, and ends the series of processes. Note that before the image data is recorded on the memory card 28, an image compression process (such as a JPEG compression process) may be performed as necessary via the compression / decompression unit 26.
As described above, according to the first embodiment, gradation conversion processing is performed on image data according to input / output characteristics having characteristics that reduce contrast in the middle of gradation, and gradation conversion is performed. For the processed image data, correction for enhancing the local contrast indicating the local contrast of the image is performed using a gain curve whose degree of enhancement changes according to the luminance information of the pixel to be processed. Therefore, it is possible to improve the bright part gradation and the dark part gradation while maintaining contrast and suppressing changes in hue and saturation.

  In addition, the local contrast enhancement processing described in the first embodiment can be easily realized by improving an algorithm of contour enhancement processing that has been widely used conventionally.

  Further, according to the first embodiment, the correction for emphasizing the local contrast using the low-pass filter having the wide width at half maximum (d in FIG. 6) of 1/100 or more of the short side of the image illustrated in FIG. Thus, correction can be performed based on the medium frequency component. This correction is different from the correction based on the super-high frequency component such as edge enhancement usually performed for each pixel, and corrects the local contrast to improve the bright part gradation and the dark part gradation while maintaining the contrast. This effect can be obtained because in human vision it is local to perceive contrast.

Second Embodiment
The second embodiment of the present invention will be described below with reference to the drawings. Since the second embodiment is a modification of the first embodiment, only portions different from the first embodiment will be described.

  The configuration of the electronic camera of the second embodiment is the same as that of the electronic camera 1 of the first embodiment. Therefore, the following description will be made using the same reference numerals as in the first embodiment.

  The flowchart of FIG. 10 shows the operation at the time of photographing of the electronic camera 1 of the second embodiment.

  In step S21 to step S23, the control unit 17 performs the same processing as step S1 to step S3 in the flowchart of FIG.

  In step S24, the control unit 17 selects the gradation curve G3. As shown in FIG. 11, the gradation curve G3 is a gradation curve having both the characteristics of the gradation curve G1 and the characteristics of the gradation curve G2 described using the flowchart of FIG.

  In step S25, the control unit 17 performs gradation conversion processing on the image data subjected to image processing in step S23 according to the gradation curve G3 selected in step S24. That is, the control unit 17 performs the gradation conversion process only once using one gradation curve in which a characteristic (corresponding to G2) that weakens contrast is added to a normal characteristic (corresponding to G1).

  In step S26 to step S27, the control unit 17 performs the same processing as in step S8 to step S9 in the flowchart of FIG. By adopting such a configuration, the same effect as that of the first embodiment can be obtained.

  In each of the above-described embodiments, the example in which the technique of the present invention is realized in the electronic camera 1 has been described. However, the present invention is not limited to this. For example, the present invention can be similarly applied to a compact type electronic camera, a movie camera for taking a moving image, and the like.

  Further, the image processing apparatus described in each of the above-described embodiments may be realized by software using a computer and an image processing program. In this case, what is necessary is just to make it the structure which implement | achieves part or all of the process after step S4 demonstrated with the flowchart of FIG. 3 with a computer. Or what is necessary is just to set it as the structure which implement | achieves a part or all of the process after step S24 demonstrated with the flowchart of FIG. 10 with a computer. Note that such an image processing program may be recorded on a medium, or may be downloaded from a server or the like via the Internet or the like.

  In addition, the present invention can be similarly applied when the image to be processed is an image after the gradation conversion process using the gradation curve G1 described in each of the above-described embodiments. In this case, what is necessary is just to make it the structure which implement | achieves part or all of the process after step S6 demonstrated with the flowchart of FIG. 3 with a computer. Or what is necessary is just to set it as the structure which implement | achieves a part or all of the process after step S24 demonstrated with the flowchart of FIG. 10 with a computer.

  The present invention can be implemented in various other forms without departing from the spirit or main features thereof. For this reason, the above-described embodiments are merely examples in all respects and should not be interpreted in a limited manner. The scope of the present invention is indicated by the scope of claims, and is not restricted by the text of the specification. Further, all modifications and changes belonging to the equivalent scope of the claims are within the scope of the present invention.

  DESCRIPTION OF SYMBOLS 1 ... Electronic camera, 2 ... Shooting lens, 14 ... Image sensor, 17 ... Control part

Claims (10)

An image processing program for realizing image processing on image data to be processed by a computer,
An acquisition step of acquiring the image data;
A gradation conversion processing step for performing gradation conversion processing on the image data in accordance with an input / output characteristic defined by a gradation curve having a characteristic that takes into account the characteristic of weakening the contrast in an intermediate part of the gradation;
For the image data that has been subjected to the gradation conversion processing, a correction that enhances local contrast indicating the local contrast of the image is performed, and a gain curve whose emphasis degree changes according to luminance information of the pixel to be processed And a correction step performed using
In the correction step, the brightness of the target pixel is increased by increasing the gain of the target pixel as the target pixel is brighter than the surrounding pixels, and the gain of the target pixel is decreased as the target pixel is darker than the surrounding pixels. While correcting darkness, when the target pixel is darker than the surrounding pixels, the correction is performed using the gain curve that increases the degree of enhancement compared to the case where the target pixel is brighter than the surrounding pixels. An image processing program characterized by In the image processing program according to claim 1,
In the correction step, image data of a blurred image is created based on the image data, and the correction is performed based on a value indicating a difference between a luminance value in the image data and a luminance value in the image data of the blurred image. An image processing program characterized by The image processing program according to claim 1 or 2,
In the correction step, image data of a blurred image is created based on the image data, and the emphasis is increased as a value indicating a difference between a luminance value in the image data and a luminance value in the image data of the blurred image is increased. An image processing program that performs the correction using the gain curve that reduces the degree. In the image processing program according to any one of claims 1 to 3,
In the correction step, image data of a blurred image is created based on the image data, and the emphasis is increased as a value indicating a difference between a luminance value in the image data and a luminance value in the image data of the blurred image is decreased. An image processing program that performs the correction using the gain curve that increases the degree. In the image processing program according to any one of claims 1 to 4,
In the gradation conversion processing step, there are a plurality of gradation curves having a characteristic that takes into account the characteristic of weakening the contrast in an intermediate part of the gradation, and a characteristic that weakens the contrast added to each gradation curve. In accordance with input / output characteristics defined by a gradation curve selected from a plurality of different gradation curves, gradation conversion processing is performed on the image data,
In the correction step, the correction is performed using a gain curve whose degree of enhancement changes according to the input / output characteristics of the gradation curve selected in the gradation conversion processing step. In the image processing program according to any one of claims 1 to 5,
The gradation curve includes an S-shaped characteristic. The image processing program according to any one of claims 1 to 6,
The gradation processing curve includes characteristics corresponding to an external output device. An acquisition unit for acquiring image data to be processed;
A gradation conversion processing unit that performs gradation conversion processing on the image data in accordance with an input / output characteristic having characteristics that take into account the characteristic of weakening the contrast in an intermediate part of gradation;
For the image data that has been subjected to the gradation conversion processing, a correction that enhances local contrast indicating the local contrast of the image is performed, and a gain curve whose emphasis degree changes according to luminance information of the pixel to be processed And a correction unit to be used,
The correction unit enhances the brightness by increasing the gain of the target pixel as the target pixel is brighter than the surrounding pixels, and decreases the gain of the target pixel as the target pixel is darker than the surrounding pixels. The correction is performed using the gain curve that enhances darkness and increases the degree of enhancement when the pixel of interest is darker than the surrounding pixels than when the pixel of interest is brighter than the surrounding pixels. An image processing apparatus characterized by The image processing apparatus according to claim 8.
The gradation conversion processing unit is a plurality of gradation curves having characteristics that take into account the characteristic of weakening the contrast in an intermediate part of gradations, and has a characteristic of weakening the contrast added to each gradation curve. Having a plurality of different gradation curves, and performing gradation conversion processing on the image data in accordance with input / output characteristics defined by the gradation curves selected from the plurality of gradation curves;
The image processing apparatus according to claim 1, wherein the correction unit performs the correction using a gain curve whose degree of enhancement changes according to input / output characteristics of the gradation curve selected by the gradation conversion processing unit. An acquisition step of acquiring image data to be processed;
A gradation conversion processing step for performing gradation conversion processing on the image data in accordance with input / output characteristics having characteristics that take into account the characteristics of weakening the contrast in an intermediate portion of gradation;
For the image data that has been subjected to the gradation conversion processing, a correction that enhances local contrast indicating the local contrast of the image is performed, and a gain curve whose emphasis degree changes according to luminance information of the pixel to be processed And a correction process performed using
In the correction step, as the target pixel is brighter than surrounding pixels, the gain of the target pixel is increased to enhance the brightness, and as the target pixel is darker than the surrounding pixels, the gain of the target pixel is decreased. The correction is performed using the gain curve that enhances darkness and increases the degree of enhancement when the pixel of interest is darker than the surrounding pixels than when the pixel of interest is brighter than the surrounding pixels. An image processing method characterized by:

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