JP2012093904A - Image processing device, image processing method, imaging device, and image processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To generate an image in which a main subject present in an area of interest is more conspicuous.SOLUTION: An image processing device 100 includes an image data acquisition part 102 which acquires source image data as image data to be processed; an area setting part 104 which sets a main part as a partial area including the main subject in the source image data and a peripheral part as a partial area other than the main subject in the source image data; an image processing execution determination part 106 which determines whether the source image data needs to be corrected based upon information on the color saturation of the main part or/and information on the spatial frequency; and a corrected image data generation part 108 which performs reduction processing on an image of the peripheral part so that the image of the main part is relatively conspicuous when the image processing execution determination part 106 determines that the source image data needs to be corrected. Through the reduction processing, the image of the peripheral part is reduced in at least one of lightness, contrast, and color saturation.

Description

  The present invention relates to an image processing technique, and more particularly to an image processing technique that can improve the appearance of an image generated by an image input device such as a photographing apparatus.

  As a method of improving the appearance of an image obtained by photographing, there is a method of correcting a saturation and contrast to obtain a sharp image. Patent Document 1 discloses a technique for dividing an image into several regions and performing saturation correction based on the saturation level of the region having the highest saturation level.

JP 2000-224607 A

  In general, when observing an image obtained by photographing, it is preferable that a region of interest including a main subject stands out. That is, it is desirable to obtain an image in which the image feature of the attention region gives a stronger impression than the image feature of the non-attention region when the attention region is compared with the non-attention region other than the attention region.

  The technique disclosed in Patent Document 1 is intended to prevent the saturation of an area in which a subject whose saturation is not so high, such as a building wall, from being excessively increased. For this reason, the image feature of the attention area is not necessarily corrected so as to give a stronger impression than the image feature of the non- attention area. As a result, an area other than the attention area may stand out.

  The present invention has been made in view of the above-described problems, and an object of the present invention is to provide a technique capable of generating an image in which a main subject appearing in a region of interest in an image can be seen more conspicuously.

According to the first aspect of the present invention, there is provided an image processing apparatus that acquires original image data that is image data to be processed and performs correction processing on the original image data.
An image data acquisition unit for acquiring the original image data;
An area setting unit that analyzes the original image data and sets a main part that is a partial area including a main subject in the original image data and a peripheral part that is a partial area other than the main part in the original image data. When,
An image processing execution determination unit that determines whether or not correction of the original image data is necessary based on either or both of saturation information and spatial frequency information in the main part,
When the image processing execution determination unit determines that the correction of the original image data is necessary, a corrected image that performs reduction processing on the peripheral image so that the image of the main part stands out relatively A data generation unit, comprising: a corrected image data generation unit that performs the reduction process so that at least one of brightness, contrast, and saturation of the peripheral image is decreased.

According to the second aspect of the present invention, there is provided an image processing method for performing correction processing on original image data that is image data to be processed.
An image data acquisition procedure for acquiring the original image data;
An area setting procedure for analyzing the original image data and setting a main part that is a partial area including a main subject in the original image data and a peripheral part that is a partial area other than the main part in the original image data When,
An image processing execution determination procedure for determining whether or not correction of the original image data is necessary based on either or both of saturation information and spatial frequency information in the main part,
When it is determined that the correction of the original image data is necessary by the image processing execution determination procedure, a corrected image that performs a reduction process on the peripheral image so that the image of the main part stands out relatively A data generation procedure, comprising: a corrected image data generation procedure for performing the reduction process so that at least one of brightness, contrast, and saturation of the peripheral image is reduced.

According to the third aspect of the present invention, an imaging device including an imaging device capable of photoelectrically converting a subject image formed by a photographing lens and outputting an image signal,
An image data acquisition unit that acquires image data generated from the image signal output from the image sensor as original image data;
An area setting unit that analyzes the original image data and sets a main part that is a partial area including a main subject in the original image data and a peripheral part that is a partial area other than the main part in the original image data. When,
An image processing execution determination unit that determines whether or not correction of the original image data is necessary based on either or both of saturation information and spatial frequency information in the main part,
When the image processing execution determination unit determines that the correction of the original image data is necessary, a corrected image that performs reduction processing on the peripheral image so that the image of the main part stands out relatively A data generation unit, comprising: a corrected image data generation unit that performs the reduction process so that at least one of brightness, contrast, and saturation of the peripheral image is decreased.

According to the fourth aspect of the present invention, there is provided an image processing program for causing a computer to execute processing for correcting original image data that is image data to be processed.
An image data acquisition step of acquiring the original image data;
A region setting step of analyzing the original image data and setting a main portion that is a partial region including a main subject in the original image data and a peripheral portion that is a partial region other than the main portion in the original image data. When,
An image processing execution determination step for determining whether or not correction of the original image data is necessary based on either or both of the saturation information and the spatial frequency information in the main part,
When it is determined in the image processing execution determination step that the correction of the original image data is necessary, a corrected image that performs reduction processing on the peripheral image so that the image of the main part stands out relatively A data generation step, comprising: a corrected image data generation step that performs the reduction process so that at least one of brightness, contrast, and saturation of the image in the peripheral portion decreases.

  According to the present invention, a main part in an image can be seen more conspicuously than a peripheral part, whereby an image that looks good as a whole can be obtained.

2 is a block diagram schematically illustrating an internal configuration of the image processing apparatus. FIG. FIG. 25 is a block diagram illustrating an example in which an image processing device is incorporated in an imaging device. And FIG. 20 is a block diagram illustrating an example in which an image processing apparatus is realized by a computer that executes an image processing program. It is a figure which shows an example of the image of a process target, and is a figure which shows notionally the mode that the main part including the part in which a main subject is reflected, and the peripheral part which is parts other than a main part are set. 4 is a flowchart for describing a procedure of image processing executed by the image processing apparatus according to the first embodiment. 6 is a flowchart for explaining in more detail a processing procedure of image processing execution determination performed during the processing shown in the flowchart of FIG. 5. It is a figure which illustrates notionally the method of producing | generating the histogram of a spatial frequency and analyzing an image. It is a figure explaining the example which sets the process parameter at the time of performing a reduction process with respect to the image of a peripheral part based on the saturation of a peripheral part, the brightness of a peripheral part, and the contrast of a peripheral part. It is a figure which illustrates notionally the example which sets a principal degree according to the distance from a principal part. It is a figure explaining the example which increases importance based on the result of having analyzed the image of the peripheral part. It is a figure explaining the example which changes the image mixture ratio at the time of synthesize | combining original image data and post-processing temporary image data based on a principal degree. FIG. 3 is a diagram conceptually illustrating a procedure when corrected image data is generated from original image data by the image processing apparatus according to the first embodiment. It is a flowchart explaining the procedure of the image processing performed by the image processing apparatus of 2nd Embodiment. It is a figure which illustrates notionally the procedure at the time of correction | amendment image data being produced | generated from the original image data by the image processing apparatus of 2nd Embodiment. 14 is a flowchart for describing a procedure of image processing executed by the image processing apparatus according to the third embodiment. It is a figure which illustrates notionally the procedure at the time of the correction | amendment image data being produced | generated from the original image data by the image processing apparatus of 3rd Embodiment. 15 is a flowchart for describing a procedure of image processing executed by the image processing apparatus according to the fourth embodiment. It is a figure which illustrates notionally the procedure at the time of the correction | amendment image data being produced | generated from the original image data by the image processing apparatus of 4th Embodiment. It is a figure explaining the example from which the histogram after performing an emphasis process changes before emphasis processing is performed to an image which has various histograms. It is a figure explaining the example which sets the process parameter at the time of performing an emphasis process with respect to the image data of a principal part based on the result of having analyzed the image data of a principal part. It is a figure which illustrates notionally the processing procedure at the time of performing an emphasis process in addition to the reduction process demonstrated in 1st Embodiment, and producing | generating correction | amendment image data. It is a figure which illustrates not only the reduction process demonstrated in 2nd Embodiment but also the emphasis process, and conceptually shows the process sequence at the time of producing | generating correction | amendment image data. It is a figure which illustrates not only the reduction process demonstrated in 3rd Embodiment but a process procedure at the time of also performing an emphasis process and producing | generating correction | amendment image data. It is a figure which illustrates not only the reduction process demonstrated in 4th Embodiment but also the enhancement process, and the process sequence at the time of producing | generating correction | amendment image data notionally.

  FIG. 1 is a block diagram illustrating a schematic configuration of an image processing apparatus 100 according to an embodiment of the present invention. The image processing apparatus 100 includes an image data acquisition unit 102, an area setting unit 104, an image processing execution determination unit 106, and a corrected image data generation unit 108.

  The image data acquisition unit 102 acquires target image data to be processed by the image processing apparatus 100. This image data may be still image data or moving image data. When the acquired image data is still image data, the image processing apparatus 100 performs processing on the acquired image data of one frame. When the image data to be acquired is moving image data including a series of a plurality of frames, the image processing apparatus 100 performs processing on each of the acquired series of images of the plurality of frames.

  The area setting unit 104 analyzes the image data to be processed (hereinafter, this image data is referred to as original image data) acquired by the image data acquisition unit 102, and a portion in which the main subject is captured in the original image data And a peripheral part that is an area other than the main part in the original image data.

  The image processing execution determination unit 106 analyzes the image data of the part corresponding to the main part in the original image data, and either the saturation information or the spatial frequency information of the image data of the part corresponding to the main part, Alternatively, it is determined whether or not correction of the original image data is necessary based on both pieces of information.

  When the image processing execution determination unit 106 determines that correction of the original image data is necessary, the corrected image data generation unit 108 processes the original image data to generate corrected image data. At this time, the corrected image data generation unit 108 performs a reduction process on the peripheral image. The reduction processing is processing in which at least one of the brightness, contrast, and saturation of the peripheral image is decreased, and as a result, the main image is relatively prominent.

  The processing in the corrected image data generation unit 108 can be various depending on what color system data the original image data is. For example, when the original image data is defined in the RGB color space, it is possible to perform processing for correcting the R, G, and B color coordinate values. Further, when the original image data is defined in the YCbCr color space, even if only the color coordinate value of luminance Y is corrected, only the color coordinate values of Cb and Cr that define the hue and saturation are corrected. May be. The same applies when the original image data is defined in the Lab color space. Even if only the color coordinate value of lightness L is corrected, only the color coordinate values of a and b that define hue and saturation are corrected. May be.

  Note that brightness and brightness are defined as the brightness of each pixel in the image data. Luminance is determined by taking into account the human's specific visual sensitivity (measured by the brightness perceived by the human eye), while brightness is taken from the physical intensity as a scale without taking into account the relative visual sensitivity. Is generally defined. In the present specification, the expression “brightness” or “brightness or brightness” is used when it is not necessary to distinguish between these brightness and brightness. Information defining the brightness (luminance or brightness) of each pixel in the image data is referred to as “lightness information” in this specification.

  An image recording unit 160, an image display unit 150, and the like may be connected to the image processing apparatus 100. In that case, the corrected image data generated by the corrected image data generation unit 108 can be recorded in the image recording unit 160 as necessary. Alternatively, an image based on the corrected image data can be displayed on the image display unit 150.

  The image processing apparatus 100 can be provided in an image input apparatus such as a digital still camera or a digital movie camera. Alternatively, the functions of the image processing apparatus 100 can be implemented by an image processing program recorded on a recording medium and a computer that executes the image processing program.

  FIG. 2 is a block diagram illustrating an example in which the image processing apparatus 100 is mounted on a digital camera 200 such as a digital still camera or a digital movie camera. The digital camera 200 includes a photographing optical system 210, a lens driving unit 212, an imaging unit 220, an analog front end (indicated as “AFE” in FIG. 2) 222, an image recording medium 230, an operation unit. 240, a display unit 250, a storage unit 260, a CPU 270, a digital signal processing device (hereinafter referred to as a DSP) 290, and a system bus 280. The storage unit 260 includes a ROM 262 and a RAM 264. In the present embodiment, the image processing apparatus 100 will be described as being implemented as one function provided in the DSP 290.

  The lens driving unit 212, the imaging unit 220, the analog front end 222, the image recording medium 230, the operation unit 240, the display unit 250, the storage unit 260, the CPU 270, and the image processing apparatus 100 are electrically connected via the system bus 280. Is done. The RAM 264 is configured to be accessible from both the CPU 270 and the DSP 290.

  The imaging optical system 210 forms a subject image on the light receiving area of the imaging unit 220. The lens driving unit 212 drives a focus adjustment lens in the photographing optical system 210. Further, when the photographing optical system 210 is a variable focal length optical system, the lens (lens group) in the photographing optical system 210 is driven by the lens driving unit 212 so that the focal length can be changed. May be.

  The imaging unit 220 photoelectrically converts a subject image formed on the light receiving area to generate an analog image signal. This analog image signal is input to the analog front end 222. The analog front end 222 performs processing such as noise reduction, amplification, and A / D conversion on the image signal input from the imaging unit 220 to generate a digital image signal. This digital image signal is temporarily stored in the RAM 264.

  The DSP 290 performs various digital signal processing such as demosaicing, gradation conversion, color balance correction, shading correction, and noise reduction on the digital image signal temporarily stored in the RAM 264 to generate image data. This image data is recorded on the image recording medium 230 as necessary. An image based on the image data is displayed on the display unit 250. The image processing apparatus 100 performs processing for generating the corrected image data schematically described above using the image data generated as described above as original image data.

  The image recording medium 230 includes a flash memory, a magnetic recording device, and the like, and is detachably attached to the digital camera 200. The image recording medium 230 may be built in the digital camera 200. In that case, an area for recording image data can be secured in the ROM 262.

  The operation unit 240 includes any one type or a plurality of types of push switches, slide switches, dial switches, touch panels, and the like, and is configured to be able to accept user operations. The display unit 250 includes a TFT liquid crystal display panel and a backlight device, or a self-luminous display element such as an organic EL display element, and is configured to display information such as images and characters. Note that the display unit 250 includes a display interface, and the display interface reads image data written in a VRAM area provided on the RAM 264 and displays information such as images and characters on the display unit 250.

  The ROM 262 is configured by a flash memory or the like, and stores a control program (firmware) executed by the CPU 270, adjustment parameters, information that needs to be held even when power is not supplied to the digital camera 200, and the like. The RAM 264 is configured by SDRAM or the like and has a relatively high access speed. The CPU 270 comprehensively controls the operation of the digital camera 200 by interpreting and executing the firmware transferred from the ROM 262 to the RAM 264.

  The digital camera 200 may operate in the still image shooting mode or in the moving image shooting mode. When the digital camera 200 operates in the still image capturing mode, the image processing apparatus 100 performs processing for generating corrected image data corresponding to one still image data generated according to one shooting operation. On the other hand, when the digital camera 200 operates in the moving image shooting mode, the image processing apparatus 100 generates a series of corrected image data of a plurality of frames corresponding to each of a plurality of frames of moving image data generated during the shooting operation. Perform the process.

  FIG. 3 is a block diagram illustrating an example in which an image processing program recorded on a recording medium is read and executed by a CPU of a computer, and functions as an image processing apparatus are implemented. The computer 300 includes a CPU 310, a memory 320, an auxiliary storage device 330, an interface 340, a memory card interface 350, an optical disk drive 360, a network interface 370, and a display device 380. The CPU 310, the memory card interface 350, the optical disk drive 360, the network interface 370, and the display device 380 are electrically connected via the interface 340.

  The memory 320 is a memory having a relatively high access speed, such as a DDR SDRAM. The auxiliary storage device 330 is configured by a hard disk drive, a solid state drive (SSD), or the like, and has a relatively large storage capacity.

  The memory card interface 350 is configured so that the memory card MC can be detachably attached. Image data generated by performing a shooting operation with a digital camera or the like and stored in the memory card MC can be read into the computer 300 via the memory card interface 350. Also, the image data in the computer 300 can be written into the memory card MC.

  The optical disk drive 360 is configured to be able to read data from the optical disk OD. The optical disk drive 360 may also be configured to write data to the optical disk OD as necessary.

  The network interface 370 is configured to exchange information between the computer 300 and an external information processing apparatus such as a server connected via the network NW.

  The image processing apparatus 100 is realized by the CPU 310 interpreting and executing an image processing program loaded on the memory 320. This image processing program is recorded on a recording medium such as a memory card MC or an optical disc OD and distributed to users of the computer 300. Alternatively, an image processing program can be downloaded from an external information processing apparatus such as a server via the network NW. This image processing program may be realized as one function called in so-called photo retouching software.

  On the computer 300, a program for processing still image data may be executed, or a program for processing moving image data may be executed. Regardless of which of the above programs is executed, it corresponds to still image data read from any of the memory card MC, the optical disc OD, or the auxiliary storage device 330 or a series of moving image data of a plurality of frames. Thus, the image processing apparatus 100 can perform a process of generating a single corrected image data or a series of corrected image data of a plurality of frames.

  Hereinafter, examples in which the image processing apparatus 100 illustrated in FIG. 1 generates corrected image data corresponding to the acquired original image data will be described in some embodiments.

− First embodiment −
FIG. 4 is a diagram illustrating an example of an image based on the original image data acquired by the image data acquisition unit 102. The area setting unit 104 analyzes the original image data, and a main part that is a part including a part in which the main subject is reflected in the original image data, and a peripheral part that is also an area other than the main part in the original image data. And set. In the example shown in FIG. 4, it is assumed that the tree shown in the lower left part of the screen is determined as the main subject, and the area including the part in which this tree is shown is set as the main part. At this time, a part other than the main part is set as the peripheral part. The region setting unit 104 also sets a neighborhood region. The neighborhood area is an area located in the vicinity (within a predetermined distance range) of the main part, and is an area around the main part.

  FIG. 5 is a flowchart for explaining a procedure of image processing executed by the image processing apparatus 100. The image processing apparatus 100 acquires image data in S500. This process corresponds to the process in the image data acquisition unit 102. The acquired image data is original image data.

  In step S502, the image processing apparatus 100 performs processing for analyzing the original image data and setting the main part and the peripheral part. This process corresponds to the process in the area setting unit 104. The processing by the area setting unit 104 can be performed using various well-known methods. For example, the color and position of each pixel in the original image data are analyzed, and based on their similarity, several determination target regions, that is, target regions for determining whether or not they are main parts are extracted. From these determination target areas, it is possible to select a main part based on the size of the determination target area, the saturation level, or the like.

  In step S <b> 504, the image processing apparatus 100 performs processing to analyze the main part image and determine whether to perform processing for generating corrected image data. This process corresponds to the process in the image processing execution determination unit 106. The processing by the image processing execution determination unit 106 is performed as follows, for example. That is, an image of the main part is analyzed to derive an image feature amount, and it is determined based on the image feature amount whether the image of the main part can obtain a sufficient effect of the correction process. . For example, the image processing apparatus 100 extracts main part color information, spatial frequency information, and edge information as image feature amounts.

  The color information is information that is referred to when an image of a main part is evaluated. For example, RGB image data is converted into image data in a color space such as YCbCr, Lab, or HSL, and saturation information extracted from Cb, Cr values, a, b values, or S values is used as color information. It can be. By the way, as color information, the information which can evaluate the brightness of a principal part other than saturation may be included. In that case, it is also possible to extract the Y value and the L value from the image data in the color space such as YCbCr, Lab or HSL. As described above, the color information may be information capable of evaluating saturation and brightness. However, in the following description, it is assumed that the color information is information for evaluating the main image by saturation.

  The spatial frequency information is information related to the spatial frequency component included in the main image. That is, it is information for evaluating how fine the texture of the main part image is.

  FIG. 6 is a flowchart for explaining in more detail the processing of S504 executed by the image processing apparatus 100. In S600, the image processing apparatus 100 extracts the main part image set in S502. In step S <b> 602, the image processing apparatus 100 converts the image extracted in step S <b> 600 into, for example, image data in a color space of YCbCr, and extracts Cb and Cr data, that is, saturation data. Then, it is determined whether or not the saturation of the main part is less than the first threshold value. If the determination in S602 is affirmed, the process proceeds to S604. If the determination is negative, the process proceeds to S606. The first threshold value may be set in advance as a default value, or may be configured to be appropriately changed by the user.

  In S606, which is a branch destination when the determination in S602 is negative, the image processing apparatus 100 analyzes the image extracted in S600 and derives a spatial frequency evaluation value. This spatial frequency evaluation value is for evaluating how fine the texture of the image of the main part as a whole has. FIG. 7 is a graph conceptually showing a state in which an image of a main part is analyzed and a spatial frequency component included in the image is histogrammed. The horizontal axis represents the spatial frequency, and the vertical axis represents the frequency. For example, if the image of the main part is mesh-divided with a polygon such as a relatively small rectangle, and the two-dimensional Fourier transform is performed for each divided area (divided area), the spatial frequency component corresponding to each divided area is obtained. Can be sought. Based on the obtained spatial frequency components, a histogram as illustrated in FIG. 7 can be generated.

  From the above-described histogram of the spatial frequency, the area of the region R high having a spatial frequency higher than the predetermined spatial frequency U and the area of the region R low having a low spatial frequency are obtained. Based on these R high and R low values, it is possible to derive a spatial frequency evaluation value using an equation such as (R high / (R high + R low)) or (R high / R low). As more finer texture regions are distributed in the main image, the spatial frequency evaluation value becomes larger. The image processing apparatus 100 determines whether or not the spatial frequency evaluation value derived in this way is greater than or equal to the second threshold value in S606, and proceeds to S604 if affirmed or proceeds to S608 if denied. Similar to the first threshold value, the second threshold value may be set in advance as a default value, or may be configured to be appropriately changed by the user.

  In S604, which is a branch destination when the determination in S602 or S606 is affirmed, the image processing apparatus 100 determines to perform image processing and returns. On the other hand, in S608, which is a branch destination when the determinations in S602 and S606 are both denied, the image processing apparatus 100 determines not to perform image processing and returns.

  Referring to FIG. 5 again, in response to the determination processing result in S504, the image processing apparatus 100 determines whether or not to perform image processing in S506. If the determination in S506 is affirmative, the process proceeds to S508. If the determination is negative, the image processing is not performed and the process of FIG.

  If the determination in S506 is affirmed, the image processing apparatus 100 performs the processing from S508 to S516. In the first embodiment, a series of processing from S508 to S516 corresponds to processing by the corrected image data generation unit 108.

  In step S508, the image processing apparatus 100 sets image processing parameters. This image processing parameter setting method will be described with reference to FIG. FIG. 8 is a diagram illustrating an example in which a saturation reduction coefficient, a brightness reduction coefficient, and a contrast reduction coefficient are used as the image processing parameters when performing the reduction process described above. The image processing apparatus 100 performs saturation reduction, brightness reduction, and contrast reduction processing when performing reduction processing on the peripheral image. At this time, the amount of reduction when reducing the saturation, brightness, and contrast is not constant and changes according to the conditions shown in FIG.

  When the average value of saturation in the peripheral portion is equal to or greater than the third threshold value, the saturation reduction coefficient is set to 1.2. When the average value of the saturation at the peripheral portion is higher than the fourth threshold and lower than the third threshold, the saturation reduction coefficient is set to 1.0. Further, when the average saturation value in the peripheral portion is equal to or smaller than the fourth threshold value, the saturation reduction coefficient is set to 0.8.

  Here, the magnitude relationship between the third threshold value and the fourth threshold value will be described. It is assumed that the third threshold value is larger than the fourth threshold value. In other words, the fact that the average value of the saturation in the peripheral portion is equal to or greater than the third threshold value assumes that the saturation in the peripheral portion is relatively high, and in that case, the saturation reduction coefficient is set to the default value. On the other hand, the saturation is increased by 20%, and the saturation of the peripheral portion is further reduced. The fact that the average value of the saturation in the peripheral portion is higher than the fourth threshold value and lower than the third threshold value assumes that the saturation in the peripheral portion is moderate. In that case, the saturation reduction coefficient is The default value (1.0) is set. The average value of the saturation in the peripheral portion is equal to or lower than the fourth threshold value assumes that the saturation in the peripheral portion is relatively low, and in that case, the saturation reduction coefficient is set to the default value. On the other hand, a reduction of 20% is set. As a result, the amount of reduction in reducing the saturation of the peripheral portion is smaller.

  When the average value of the brightness of the peripheral portion is the fifth threshold value or more, the brightness reduction coefficient is set to 1.2. When the average value of the brightness of the peripheral part is higher than the sixth threshold value and lower than the fifth threshold value, the brightness reduction coefficient is set to 1.0. Further, when the average brightness value of the peripheral portion is equal to or less than the sixth threshold value, the brightness reduction coefficient is set to 0.8.

  Here, the magnitude relationship between the fifth threshold value and the sixth threshold value will be described. It is assumed that the fifth threshold value is larger than the sixth threshold value. In other words, the fact that the average value of the brightness of the peripheral portion is equal to or greater than the fifth threshold assumes that the peripheral portion is relatively bright, and in that case, the brightness reduction coefficient is 20 with respect to the default value. % Increase, and the brightness of the peripheral portion is further reduced. That the average value of the brightness of the peripheral part is higher than the sixth threshold value and lower than the fifth threshold value assumes that the peripheral brightness is moderate, in which case the brightness reduction coefficient is The default value (1.0) is set. The average value of the brightness of the peripheral portion is equal to or smaller than the sixth threshold value assumes that the peripheral portion is relatively dark, and in that case, the brightness reduction coefficient is 20 with respect to the default value. Set to% decrease. As a result, the amount of reduction when reducing the brightness of the peripheral portion becomes smaller.

  When the average value of the peripheral contrast is equal to or greater than the seventh threshold value, the contrast reduction coefficient is set to 1.2. When the average value of the contrast at the peripheral portion is higher than the eighth threshold value and lower than the seventh threshold value, the contrast reduction coefficient is set to 1.0. Further, when the average value of the contrast at the peripheral portion is equal to or less than the eighth threshold value, the contrast reduction coefficient is set to 0.8.

  Here, the magnitude relationship between the seventh threshold value and the eighth threshold value will be described. It is assumed that the seventh threshold value is larger than the eighth threshold value. That is, the fact that the average value of the peripheral contrast is equal to or higher than the seventh threshold value assumes that the peripheral contrast is relatively high, and in this case, the contrast reduction coefficient is 20 with respect to the default value. % Increase, and the contrast in the peripheral portion is further reduced. That the average value of the contrast in the peripheral portion is higher than the eighth threshold value and lower than the seventh threshold value assumes that the peripheral contrast is moderate, and in that case, the contrast reduction coefficient is the default value. (1.0). The average value of the peripheral contrast is equal to or less than the eighth threshold value assumes that the peripheral contrast is relatively low. In this case, the contrast reduction coefficient is 20 with respect to the default value. Set to% decrease. As a result, the amount of reduction when reducing the contrast of the peripheral portion is smaller.

  The conditions shown in FIG. 8 and the processing parameters for the reduction processing corresponding to the conditions are merely examples, and the processing parameters may be determined according to more detailed conditions. Further, instead of using the coefficients such as the saturation reduction coefficient, the brightness reduction coefficient, and the contrast coefficient in FIG. 8, the saturation reduction amount, the brightness reduction amount, and the contrast reduction amount itself are determined and used. It may be.

  In S510, the image processing apparatus 100 generates temporary image data from the original image data. The temporary image data may be a simple copy of the original image data, or image data in a color space different from the original image data may be generated.

  In S512, the image processing apparatus 100 uniformly applies the image processing parameters set in S508 to the temporary image data, performs image processing (reduction processing), and generates post-processing temporary image data. With this image processing, the saturation, brightness, and contrast of the entire image, that is, the portion corresponding to the main portion and the portion corresponding to the peripheral portion are reduced. Note that the reduction process is not limited to the above-described process, and at least one of the reduction process of saturation, brightness, and contrast may be performed. Furthermore, in addition to or instead of the above reduction process, a process for adjusting the hue or the like may be performed.

  In step S <b> 514, the image processing apparatus 100 performs a degree of importance setting process. In the process of setting the degree of importance, the degree of importance is derived according to the method described below for each pixel of the original image data or for each of a plurality of pixels, and a degree-of-importance map is generated. As shown in the conceptual diagram of FIG. 12, the importance map is a data table in which the distribution of the importance in the image formed from the original image data is recorded. The data size of the importance map (the number of data defining the importance) may be the same as or smaller than the number of pixels of the original image data. That is, when the data size of the importance map is the same as the number of pixels of the original image data, the importance information is assigned to each pixel in the original image data. When the data size of the importance map is smaller than the number of pixels of the original image data, a plurality of pixels in the original image data, for example, a small size such as 2 pixels × 2 pixels, 2 pixels × 3 pixels, 5 pixels × 5 pixels vertically and horizontally A degree of importance is assigned to each area.

  Moreover, various representation forms are possible regarding the level of importance. In the following description, the derived value of the degree of importance takes a value of 0 or more and 1 or less, and is described as being set to 1 when the degree of importance is the highest, and set to 0 when the degree of importance is the lowest. It can be a range value. For example, it can be expressed by an integer such as 0 to 255, and positive and negative values may be mixed. Alternatively, the degrees of importance may be ranked by codes such as a, b, and c.

  First, the highest degree of importance of each pixel or each of a plurality of pixels in the region corresponding to the main part is set to 1, that is, 1. For each pixel or each of the plurality of pixels in the region corresponding to the peripheral part, the degree of importance is reduced as the distance from the principal part increases (set to a value smaller than 1). This is shown in FIG. Even if the characteristics illustrated in FIG. 9 are preset as the default characteristics, for example, the characteristics of the tone curve of the photo retouching software can be changed. It may be configured so that the setting can be changed.

  In addition to setting the importance according to the distance from the main part as described above, the setting described below is also performed. FIG. 10 is a diagram illustrating an example of a relationship between a condition and a correction amount when correcting the degree of importance derived based on the characteristics illustrated in FIG. In the example shown in FIG. 10, if there is a region surrounded by an edge component having a thickness greater than or equal to the ninth threshold in the peripheral portion, the importance of each pixel or a plurality of pixels in the region is shown in FIG. Processing for adding a value of 0.75 to the degree of importance set under the conditions shown is performed. However, clipping is performed so that the degree of importance does not become greater than 1 (when the result of derivation of degree of importance exceeds 1, it is set to 1).

  Further, if there is a region having a spatial frequency equal to or higher than the tenth threshold in the peripheral portion, the degree of importance of each pixel or each of the plurality of pixels in the region is set higher. For example, a process of adding a value of 0.75 to the degree of importance set under the conditions shown in FIG. Also in this case, a clipping process is performed so that the degree of importance does not exceed 1.

  In this way, by subjecting each pixel in the peripheral part or each of the plurality of pixels to increase the importance as necessary, even if the subject is reflected in a part that is relatively far away from the main part, It becomes possible to increase the degree of importance for a portion where a more favorable result can be expected if the strength of the reduction process is weakened. The ninth threshold value, the tenth threshold value, and the amount of increase in the degree of importance illustrated in FIG. 10 may be set in advance as default values, or may be configured to be appropriately changed by the user. The importance map is generated by the process of S514 described above.

  In S516, the image processing apparatus 100 performs a process of generating corrected image data by combining the original image data and the post-processing temporary image data generated in S512. If the post-processing temporary image data and the original image data are image data defined in different color spaces, the original image data is added to the image data in the same color space as the post-processing temporary image data. Convert. When performing the process of generating corrected image data by synthesizing the post-processing temporary image and the original image, the following algorithm is followed.

With reference to the importance map generated in S514, the mixing ratio of the post-processing temporary image data is reduced corresponding to the pixel or the plurality of pixels having a high importance. That is, the mixing ratio of the post-processing temporary image data and the original image data that are mixed corresponding to the pixels with the priority set to 1 or a plurality of pixels is:
[Temporary image data after processing]: [Original image data] = 0: 1.

In addition, the mixing ratio of the post-processing temporary image data and the original image data that are mixed corresponding to the pixels whose priority is set to 0 or a plurality of pixels is
[Post-processing temporary image data]: [original image data] = 1: 0.

The mixing ratio of the post-processing temporary image data and the original image data mixed corresponding to a pixel or a plurality of pixels whose degree of importance is greater than 0 and less than 1 is illustrated in the graph of FIG. It is possible to The characteristics of the image mixing ratio exemplified in FIG. 11 may also be configured to be changed by the user. In the graph illustrated in FIG.
Corresponding to [Temporary image data after processing]: [Original image data] = 1: 0, the mixing ratio is shown as 100%. That is, it is shown that the post-processing temporary image data and the original image data are mixed such that the higher the image mixing ratio, the higher the post-processing temporary image data ratio.

  Various methods can be used in the process of mixing the post-processing temporary image data and the original image data, and any of the lightness information, pixel value, and saturation information of both image data can be combined. It is. For example, when both the post-processing temporary image data and the original image data are defined in the RGB color space, it is possible to mix the components of each color of R, G, and B at the above mixing ratio. . In this case, the corrected image data is obtained by correcting the color coordinate values of the R, G, and B colors in the RGB color space.

  Alternatively, when both the post-processing temporary image data and the original image data are defined in the Lab color space or the YCbCr color space, the above mixing ratio for each component of L, a, b or Y, Cb, Cr Of course, it is possible to mix only the L component or the Y component, or the a component and the b component, or the Cb component and the Cr component can be mixed for each component.

  When only the L component is mixed, only the brightness information is mixed. That is, the color coordinate value of the L channel in the Lab color space is corrected. When mixing with only the Y component, only luminance information is mixed. That is, the color coordinate value of the Y channel in the YCbCr color space is corrected. When the a component and the b component, or the Cb component and the Cr component are mixed for each component, only saturation information is mixed. In this case, the color coordinate values of the channels a and b in the Lab color space or the color coordinate values of the channels Cb and Cr in the YCbCr color space are corrected.

  It should be noted that not only when the L component alone or the Y component alone is mixed, but also when the saturation information alone is mixed, the post-processing temporary image data and the original image data are In the corrected image data generated by mixing, the contrast of the image of the portion where the degree of importance is set lower is lower.

  FIG. 12 is a diagram conceptually showing the processing procedure described above with reference to the flowchart of FIG. According to the first embodiment, as shown in FIG. 12, the image processing parameters set in S508 are uniformly applied to the temporary image data generated from the original image data to perform the reduction process. The processed temporary image data is generated. The original image data and the post-processing temporary image data are combined at a mixing ratio based on the degree of importance map generated in the degree of importance setting process in S514, and corrected image data is generated. At the time of synthesis, corrected image data is generated by mixing each pixel or a plurality of pixels at a mixing ratio corresponding to the degree of importance defined by the degree of importance map. As a result, the image corresponding to the higher-priority area is reduced in at least one of the saturation, brightness, and / or contrast of the image corresponding to the lower-priority area. An image that looks more prominent than an image and looks good can be obtained.

− Second Embodiment −
FIG. 13 is a flowchart illustrating a procedure of image processing executed by the image processing apparatus 100. In the flowchart of FIG. 13, processing steps having the same contents as the processing in the flowchart of FIG. 5 in the first embodiment will be simplified as appropriate and will be described focusing on differences from the first embodiment.

In S1300, processing for acquiring original image data is performed. The processing in S1300 can be the same as the processing in S500 described with reference to FIG. 5 in the first embodiment. In step S <b> 1302, the image processing apparatus 100 analyzes the original image data and performs processing for setting one or more main parts and peripheral parts. This process corresponds to the process in the area setting unit 104. Depending on the acquired original image, the number of main parts set in S1302 may be more than one. In setting the main part in S1302, the same method as described in the first embodiment can be used. In other words, the color and position of each pixel in the original image data are analyzed, and based on their similarity, several areas to be judged, that is, areas to be judged whether or not they are main parts are extracted. From these determination target areas, it is possible to select the main part based on the size of the determination target area, the height of saturation, and the like. In addition, if there is an area that satisfies the following conditions, the image processing apparatus 100 sets the area as a main part.
Condition 1: The region is surrounded by a relatively thick edge component.
Condition 2: The image in the region includes a relatively high spatial frequency component.

  In step S <b> 1304, the image processing apparatus 100 performs an image processing execution determination process, that is, a process of determining whether to perform a process of analyzing the main part image and generating corrected image data. At this time, when a plurality of main parts are set in the process of S1302, the image processing apparatus 100 performs image processing execution determination for each of the main parts. The details of the image processing execution determination are the same as those described with reference to the flowchart of FIG. 6 in the first embodiment.

  In response to the determination processing result in S1304, the image processing apparatus 100 determines whether or not to perform image processing in S1306. If the result is affirmative, the process proceeds to S1308. If the result is negative, the image processing is not performed. The process of FIG. 13 is finished.

  If the determination in S1306 is affirmed, the image processing apparatus 100 performs the processes of S1308, S1310, S1312, and S1314. In the second embodiment, a series of processing in S1308, S1310, S1312, and S1314 corresponds to processing by the corrected image data generation unit 108.

  In S1308, processing for setting image processing parameters is performed, and in S1310, processing for generating temporary image data from original image data is performed. In step S1312, the temporary image data generated in step S1310 is subjected to reduction processing based on the image processing parameters set in step S1308 to generate post-processing temporary image data. As described above, the processing from S1308 to S1312 can be the same as the processing from S508 to S512 described in the first embodiment.

  In step S <b> 1314, the image processing apparatus 100 performs processing for generating the corrected image data by combining the partial image data in the post-processing temporary image data with the image data at the corresponding position in the original image data. The partial image data is image data of an area corresponding to the peripheral portion in the post-processing temporary image data. In this specification, the partial image data of the area corresponding to the peripheral part is referred to as peripheral image data. Although it has been described above that one or more main parts are set in S1302, the image data of an area other than the part corresponding to the one or more main parts is the peripheral image data. When combining the peripheral image data in the post-processing temporary image data and the image data at the corresponding position in the original image data, simply processing the image data corresponding to the peripheral portion in the original image data after the processing It is possible to replace it with the surrounding image data. Alternatively, it is possible to mix the peripheral image data and the original image data at a predetermined mixing ratio. At this time, as the mixing ratio, a uniform mixing ratio may be set for the entire image, or a different mixing ratio may be set for each different position in the image.

  When the surrounding image data and the original image data are mixed and synthesized at a predetermined mixing ratio, any one of the plurality of methods described in the first embodiment can be used. . That is, when the peripheral image data and the original image data are mixed at a certain mixing ratio, even if they are mixed for each color component of R, G, and B, they are mixed using luminance information and lightness information. Alternatively, mixing may be performed using only the saturation information. As described in the first embodiment, when the post-processing temporary image data and the original image data are image data of different color spaces, the color space of the post-processing temporary image data The original image data is converted into image data in the same color space. Alternatively, the post-processing temporary image data may be converted so as to have the same color space as that of the original image data.

  On the other hand, if it is determined in the image processing execution determination in S1304 that the image processing is not performed, the determination in S1306 is denied in the flowchart of FIG. 13, and thus the processing from S1308 to S1314 is skipped. That is, the determinations in S602 and S606 in FIG. 6 are denied, the saturation of the main part is originally high, and there are not so many regions having a relatively fine texture in the main part. Corresponds to the situation. In this case, the main part is sufficiently conspicuous without performing the reduction processing of the peripheral part, and a natural image can be obtained.

  FIG. 14 is a diagram conceptually showing the processing procedure described above with reference to the flowchart of FIG. According to the second embodiment, the image processing parameters set in S508 are uniformly applied to the temporary image data generated from the original image data, and the processed temporary image data is generated. In the post-processing temporary image data, the partial image data that is image data other than the portion corresponding to one or a plurality of main portions (image data of the portion corresponding to the peripheral portion), that is, the peripheral image data, and the original image data are combined. Thus, corrected image data is generated.

  The image based on the corrected image data generated as described above is one in which at least one of the saturation, brightness, and contrast of the image corresponding to the peripheral region is reduced. As a result, the image of the region corresponding to the main part can be seen more conspicuously than the image of the other region, and an image that looks good can be obtained.

− Third embodiment −
FIG. 15 is a flowchart illustrating a procedure of image processing executed by the image processing apparatus 100. In step S1500, the image processing apparatus 100 acquires original image data. This process can be the same as the process of S500 described with reference to FIG. 5 in the first embodiment. In step S <b> 1502, the image processing apparatus 100 analyzes the original image data and performs processing for setting one or more main parts and peripheral parts. This process corresponds to the process in the area setting unit 104. This process is the same as the process in S1302 described with reference to FIG. 13 in the second embodiment, and the number of main parts set in S1502 is not limited to one, depending on the acquired original image. There may be multiple.

  In step S <b> 1504, the image processing apparatus 100 performs an image processing execution determination process, that is, a process of determining whether to perform a process of analyzing a main part image and generating corrected image data. At this time, when a plurality of main parts are set in the process of S1502, the image processing apparatus 100 performs image processing execution determination for each of the plurality of main parts. The details of the image processing execution determination are the same as those described with reference to the flowchart of FIG. 6 in the first embodiment.

  In response to the determination processing result in S1504, the image processing apparatus 100 determines whether or not to perform image processing in S1506. If the result is affirmative, the process proceeds to S1508. If the result is negative, the image processing is not performed. The process of FIG. 15 is finished.

  If the determination in S1506 is affirmed, the image processing apparatus 100 performs the processing from S1508 to S1514. In the third embodiment, a series of processing from S1508 to S1514 corresponds to processing by the corrected image data generation unit.

  In S1508, processing for setting image processing parameters is performed, and in S1510, processing for generating temporary image data from the original image data is performed. The processing in S1508 and S1510 can be the same as the processing in S508 and S510 described in the first embodiment.

  In step S <b> 1512, the image processing apparatus 100 performs reduction processing on the partial image data in the temporary image data to generate post-processing temporary image data. This partial image data is image data of an area corresponding to the peripheral portion in the temporary image data. That is, although one or more main parts are set in S1502, the image data of a region other than the part corresponding to the one or more main parts, that is, peripheral image data.

  In step S1514, the image processing apparatus 100 combines the peripheral image data in the post-processing temporary image data and the image data at the corresponding position in the original image data to generate corrected image data. In the combining process in S1514, it is possible to simply replace the image data corresponding to the peripheral portion in the original image data with the peripheral image data. Alternatively, the surrounding image data and the original image data can be mixed at a predetermined mixing ratio. At this time, as the mixing ratio, a uniform mixing ratio may be set for the entire image, or a different mixing ratio may be set for each different position in the image.

  When the surrounding image data and the original image data are mixed and synthesized at a predetermined mixing ratio, any one of the plurality of methods described in the first embodiment can be used. . That is, when the peripheral image data and the original image data are mixed at a certain mixing ratio, even if they are mixed for each color component of R, G, and B, they are mixed using luminance information and lightness information. Alternatively, mixing may be performed using only the saturation information. As described in the first embodiment, when the post-processing temporary image data and the original image data are image data of different color spaces, the color space of the post-processing temporary image data The original image data is converted into image data in the same color space. Alternatively, the post-processing temporary image data may be converted so as to have the same color space as that of the original image data.

  On the other hand, if it is determined in the image processing execution determination in S1504 that the image processing is not performed, the determination in S1506 is denied in the flowchart of FIG. 15, and thus the processing from S1508 to S1514 is skipped. That is, as described in the second embodiment, the negative determination in S602 and S606 in FIG. 6 means that the saturation of the main part is originally high and the main part is relatively This corresponds to a situation where there are not so many regions having fine textures. In this case, the main part is sufficiently conspicuous without performing the reduction processing of the peripheral part, and a natural image can be obtained.

  FIG. 16 is a diagram conceptually showing the processing procedure described above with reference to the flowchart of FIG. According to the third embodiment, the temporary image data after processing is generated by performing reduction processing on the peripheral image data corresponding to the peripheral portion in the temporary image data generated from the original image data. The post-processing temporary image data and the original image data are combined to generate corrected image data.

  The image based on the corrected image data generated as described above is one in which at least one of the saturation, brightness, and contrast of the image corresponding to the peripheral region is reduced. As a result, the image of the region corresponding to the main part can be seen more conspicuously than the image of the other region, and an image that looks good can be obtained. In the third embodiment, since the reduction process is performed only on the peripheral image data in the temporary image data, the main area is wider (the peripheral area is narrower and the data size of the peripheral image data is smaller). When it is small), the processing time can be shortened.

-Fourth embodiment-
FIG. 17 is a flowchart illustrating the procedure of image processing executed by the image processing apparatus 100 according to the fourth embodiment. In step S1700, the image processing apparatus 100 acquires image data. This process corresponds to the process in the image data acquisition unit 102. The acquired image data is original image data. The processing in S1700 is the same as the processing in S500 described with reference to FIG. 5 in the first embodiment.

  In step S <b> 1702, the image processing apparatus 100 performs processing for analyzing the original image data and setting the main part and the peripheral part. This process corresponds to the process in the area setting unit 104. The processing in S1702 can be the same as the processing in S502 described with reference to FIG. 5 in the first embodiment.

  In step S <b> 1704, the image processing apparatus 100 analyzes the main part image and performs a process of determining whether to perform a process of generating corrected image data. This process corresponds to the process in the image processing execution determination unit 106. The processing performed in S1704 can be the same as that described with reference to FIG. 6 in the first embodiment.

  In response to the determination processing result in S1704, the image processing apparatus 100 determines whether or not to perform image processing in S1706. If the determination in S1706 is affirmative, the process proceeds to S1708, and if negative, the process of FIG. 17 is terminated without performing image processing.

  If the determination in S1706 is affirmed, the image processing apparatus 100 performs the processes of S1708, S1710, and S1712. In the fourth embodiment, the processing of S1708, S1710, and S1712 corresponds to the processing by the corrected image data generation unit.

  In step S1708, the image processing apparatus 100 analyzes the original image data, derives the degree of importance for each pixel or for each of a plurality of pixels, and generates a degree-of-importance map. The method for deriving the degree of importance can be the same as that described in the first embodiment. As shown in the conceptual diagram of FIG. 18, the importance map is a data table in which the distribution of the importance in the image formed by the original image data is recorded. The method of determining the data size and value of the importance map can be the same as that described in the first embodiment.

  In step S <b> 1710, the image processing apparatus 100 sets a processing parameter for each pixel or for each of a plurality of pixels based on the importance map created in step S <b> 1708. When setting the processing parameters, it is possible to use the same method as described with reference to FIGS. 8 and 9 in the first embodiment.

  In S1712, the image processing apparatus 100 performs a reduction process based on the processing parameters set in S1710. Unlike the first to third embodiments, the target to be reduced is original image data. The strength of the reduction process increases as the degree of importance decreases. At least one of brightness, contrast, and saturation is reduced by the reduction process. Note that the brightness and saturation can be reduced in units of pixels, but the contrast reduction processing is performed in units of a plurality of pixels. The reason is that the contrast is based on a difference in brightness between a plurality of pixels or a difference in saturation.

  When the contrast reduction process is performed in the fourth embodiment, for example, the following method can be executed. That is, in the importance map created in S1708, a plurality of areas are partitioned so that an area composed of pixels that fall within a predetermined class width is defined as one area, and processing parameters are set according to the level of importance of each area. Set. Then, it is possible to perform contrast reduction processing according to the level of importance for each partitioned area.

  FIG. 18 is a diagram conceptually showing the processing described above with reference to the flowchart of FIG. As described above, in the fourth embodiment, temporary image data is not generated, and image processing (reduction processing) is performed on the original image data. The processing parameters for the reduction process are determined for each pixel or a plurality of pixels of the original image data based on the importance map generated by analyzing the original image data.

  As described above, according to the fourth embodiment, the degree of importance map is generated based on the degree of importance derived for each pixel or every plurality of pixels, and the processing parameter is set based on the degree of importance map. The reduction process is performed. As a result, it is possible to set the processing parameters more finely and obtain a more natural image as compared with the case where the reduction processing is performed on the entire peripheral portion with one processing parameter.

− Emphasis processing for images of main areas or areas of high importance −
As described above, in the first to fourth embodiments, the example in which the reduction process is performed on the less important area in the image has been described. In the following, an example will be described in which, in addition to the reduction process described above, a process of making an image of a higher-priority area stand out than an image of another area is also performed. In the following, first, a specific example of processing (hereinafter, referred to as emphasis processing) that makes an image of a higher-priority area stand out than images of other areas will be described, and then the first to fourth processes described above. An example in which the enhancement process is performed together with the reduction process described in the embodiment will be described.

  FIG. 19 is a diagram illustrating examples of histograms of various images, where the horizontal axis represents brightness and the vertical axis represents frequency. In each of FIGS. 19 (a) to 19 (f), a solid line and a broken line histogram are shown. The broken line is a histogram of the image before the enhancement process, and the solid line is the image of the image after the enhancement process. A histogram is shown. With reference to FIG. 19, a specific example in the case where processing for correcting brightness and contrast is performed as enhancement processing will be described. Note that all the histograms illustrated in FIG. 19 are not derived from the image data of the entire original image, but are derived from the image data of the main part.

  FIG. 19A shows an example in which the histogram is extremely biased to the dark side. For example, such a histogram is obtained when a person standing at the window in the room is photographed and the outside of the window is sunny in the daytime. In other words, because the background is bright, the exposure is cut off, and the image of the person in the main part is crushed in black. In such a case, as enhancement processing, processing for increasing brightness and increasing contrast is performed. As a result, the mode value (peak position of the distribution peak) in the histogram after processing moves to a brighter side, and the width of the distribution peak increases.

  FIG. 19B shows an example in which the histogram is biased toward the dark side. This example is also seen when the subject shown in the main part is taken under a lighting condition with a slight backlight. In addition, such a histogram is also obtained when flash photography is performed at night or in a dark room and the amount of flash light is insufficient. Even in such a case, as enhancement processing, processing for increasing brightness and increasing contrast is performed. As a result, in the histogram after processing, the mode value moves to the brighter side, and the width of the distribution peak increases.

  FIG. 19C shows an example in which the histogram is biased toward the dark side, as shown in FIG. 19B. This is a histogram that can be seen in the same shooting situation as described with reference to FIG. 19B. Here, it is assumed that the photographer intentionally cuts the exposure to obtain a low-key image. For example, when the brightness of not only the main part image but also the peripheral part image is dark, a process of increasing the contrast while decreasing the brightness may be performed. As a result of such processing as enhancement processing, the mode value moves to a darker side in the histogram after processing, and the width of the distribution peak increases.

  FIG. 19D shows an example in which the brightness distribution is concentrated in the intermediate region. This example can be seen in a situation in which a subject having moderate brightness is reflected in the main part in a background with a relatively wide brightness range (both bright and dark parts are present). Although the exposure level for the main subject itself is appropriate, a subject with a relatively wide luminance range from low to high brightness is shown in the peripheral area, so it is assigned to the image of the subject in the intermediate luminance range that appears in the main portion. The width of the gradation to be produced is relatively narrow. As a result, the contrast of the subject shown in the main part is low. In such a case, as the enhancement process, a process of increasing the brightness and the contrast is performed. As a result, the width of the distribution peak increases in the processed histogram. Further, since the average brightness of the main part is increased, the image of the main part stands out from the image of the peripheral part. At this time, since the enhancement process is performed only on the main image, it is possible to prevent the dark portion in the peripheral image from being crushed in black or the bright portion from being white in the processed image data. It becomes possible.

  FIG. 19E shows an example in which the brightness distribution is almost evenly distributed from the dark part to the bright part. This example is a histogram that can be seen in a situation where a subject with moderately bright parts, dark parts, and intermediate parts is photographed under relatively flat illumination conditions such as cloudy weather. An image from which such a histogram can be obtained is likely to be moderately sharp even as it is. However, in order to make the image of the main part stand out further, the following processing is performed. That is, when the histogram is divided into a dark part and a bright part, the center of gravity of the lightness distribution after processing is corrected so as to move to a darker side in the dark part and to a brighter side in the bright part. By doing so, it becomes possible to enhance the contrast of the image of the main part and make it stand out.

  FIG. 19F shows an example in which the histogram is biased toward the bright side. Here, it is assumed that the photographer intentionally sets the exposure excessively and tries to obtain a high key image. For example, when the brightness of not only the main image but also the peripheral image is bright, a process of increasing the brightness while increasing the contrast may be performed. As a result of such processing as enhancement processing, the mode value moves to a brighter side in the histogram after processing, and the width of the distribution peak increases.

  FIG. 19 (g) also shows an example in which the histogram is biased toward the bright side as in the example of FIG. 19 (f). This example is seen when the reflectance of the subject shown in the main part is higher (whiter) than the reflectance of the subject shown in the peripheral part. In such a case, as the enhancement process, a process of reducing the brightness and increasing the contrast is performed. As a result, the mode value moves to a darker side in the processed histogram, and the width of the distribution peak increases.

  FIG. 19H shows an example in which the histogram is extremely biased toward the bright side. This example is seen when the subject shown in the main part has a higher reflectance than that described with reference to FIG. This can happen when the main subject is a snowy mountain or white-walled building under direct light conditions, and a relatively low-luminance subject appears in a relatively large area around the main subject. There is. In such a case, as the enhancement process, a process of reducing the brightness and increasing the contrast can be performed. As a result, the mode value (peak position of the distribution peak) in the histogram after processing moves to a darker side, and the width of the distribution peak increases. By correcting in this way, the texture of the subject surface can be reproduced.

  When the processing described with reference to FIG. 19 is performed, it is possible to correct the color coordinate values of the L channel and the Y channel in the image data defined by a color space such as Lab, YCbCr, or HSL. . Alternatively, image data defined in a color space such as RGB or YCM may be multiplied by the same coefficient for each color coordinate value of RGB and YCM. By the way, the color coordinate values of the L channel and the Y channel are information that defines the brightness of each pixel, that is, the luminance or the brightness, and are referred to as brightness information in this specification. In addition, lightness information of each pixel constituting an image of a main part or an area of high importance is referred to as main part lightness information.

  As a contrast increase process other than that shown in FIG. 19, a histogram smoothing process may be performed. In the histogram smoothing process, the tone conversion characteristics derived based on the result of analyzing the image data are applied to the image data, and the histogram profile of the image data after the tone conversion processing is independent of the brightness. This is a process that makes the surface almost flat or more gradual. An example of the histogram smoothing procedure is described below.

1. Sort brightness information:
A process for sorting brightness information in the image data is performed. When the image data is image data defined in the RGB color space, a value obtained by simply adding R, G, and B color coordinate values for each pixel, or R, G so as to match the visual characteristics of the human eye A value obtained by weighting and adding to each color coordinate value of B is used as brightness information, and sorting is performed based on the brightness information. At this time, an average value (simple average value or weighted average value) obtained for each pixel from the values added as described above may be sorted as gradation values. When the image data is defined by a color space such as Lab, YCbCr, or HSL, the L channel and Y channel values are sorted as lightness information.

2. Deriving cumulative frequency:
If the brightness information is assumed to be an integer value, the brightness information takes the number of pixels having a value from 0 to 1, the number of pixels having a value from 0 to 2, ..., the value from 0 to the maximum value. Find the number of pixels. That is, the cumulative frequency characteristic is obtained. Based on the cumulative frequency characteristics obtained in this way, plotting the graph with the brightness information on the horizontal axis and the cumulative frequency on the vertical axis, plotting the value of the brightness information as a variable Can do.

3. Tone conversion processing:
The gradation conversion characteristic is derived by making the profile of the curve of the cumulative frequency characteristic described above directly the profile of the gradation conversion characteristic curve. By applying gradation conversion processing to the image data using the gradation conversion characteristics, the histogram is smoothed. For example, when the histogram of the image data before gradation conversion has such characteristics that it is concentrated and distributed in a narrow gradation region, a peak profile appears in the histogram. By performing the above-described gradation conversion processing, a broader gradation width can be given to a gradation region where the peaks of the histogram appear to be densely distributed and appear (the peak height is reduced, The peak width increases). On the other hand, in the gradation region with a relatively low frequency, the gradation width is narrowed by performing the gradation conversion process described above. As a result, the histogram after gradation conversion processing becomes more gradual, and the contrast of the image can be increased.

  The enhancement processing performed in the corrected image data generation unit 108 may be performed according to some methods of the example described above with reference to FIG. 19 and the histogram smoothing processing, or may be performed according to all methods. It may be broken. Further, the emphasis processing may be performed by a method other than that described above. That is, only the example of adjusting the brightness of the image data as the enhancement process has been described above, but the enhancement process may be performed by adjusting the saturation, hue, or the like. That is, in the image data defined in the color space such as Lab, YCbCr, HSL, etc., the color coordinate values of a, b, Cb, Cr, and H, S are corrected during the enhancement process. May be.

  In the first to fourth embodiments, the example of setting the image processing parameter when performing the reduction processing in the processing step of setting the image processing parameter has been described. When emphasizing processing is performed on an image of a main part or a region having a relatively high degree of importance, processing steps for setting the above-described image processing parameters (S508 in FIG. 5, S1308 in FIG. 13, S1508 in FIG. 15). In addition to the image processing parameters for performing the reduction processing, the image processing parameters for performing the enhancement processing are set in each processing step and the processing step of S1710 in FIG. A method for setting image processing parameters when performing enhancement processing will be described below with reference to FIG.

  FIG. 20 is a diagram illustrating an example in which a brightness increase amount correction coefficient is used as an image processing parameter when performing the enhancement processing described above with reference to FIG. When performing the enhancement process, the image processing apparatus 100 performs a process of increasing the brightness of the main part image (brightness increasing process) to increase the contrast of the main part image. At this time, the amount of increase when increasing the brightness of the image of the main part is not constant, and changes according to the conditions shown in FIG. That is, when the average value of the brightness (luminance or brightness) of the main part is equal to or greater than the eleventh threshold, the brightness (luminance or brightness) increase correction coefficient is set to 0.5. When the average brightness value of the main part exceeds the twelfth threshold and falls below the eleventh threshold, the brightness increase correction coefficient is set to 1. When the average value of the brightness of the main part is equal to or less than the twelfth threshold, the brightness increase amount correction coefficient is set to 1.5. That is, the brightness increase amount correction coefficient is a coefficient for adjusting the increase amount when performing the brightness increase process.

  Here, the magnitude relationship between the eleventh threshold and the twelfth threshold will be described. It is assumed that the eleventh threshold is larger than the twelfth threshold. That is, the average value of the brightness of the main part is equal to or greater than the eleventh threshold value assumes that the main part is relatively bright. In this case, the brightness increase amount is 50% of the default value. % Is set so that the main part does not become excessively bright (brightness increase correction coefficient = 0.5). The average value of the brightness of the main part is above the twelfth threshold value and below the eleventh threshold value, assuming that the main part has moderate brightness. In that case, the brightness increase amount is It is set to a default value (brightness increase correction coefficient = 1.0). The average value of the brightness of the main part is equal to or less than the twelfth threshold value assumes that the main part is relatively dark. In this case, the brightness increase amount is 50% of the default value. % Increase (brightness increase correction coefficient = 1.5).

  Further, when the region having the brightness of the thirteenth threshold or more exists in the vicinity of the main part (see FIG. 4) with an area of the fourteenth threshold or more (the number of pixels can be considered as an area), the brightness increases. The amount correction coefficient is set to 1.5. In other words, if there is a relatively bright area in the vicinity of the main part and a certain area, that is, a conspicuous area, the brightness of the main part is prevented from being buried in the image of the vicinity. The amount of increase is set to 50% increase. The thirteenth threshold value may be a fixed value set as a default. However, the thirteenth threshold value is a value obtained by adding a predetermined value to the average brightness value of the main part, and the thirteenth threshold value varies depending on the brightness of the main part. It is desirable to do.

  By setting not only the thirteenth threshold value but also the fourteenth threshold value, the following effects can be obtained. That is, when bright spot noise or the like is present in an image, it is not desirable that the contents of image processing change due to the noise. In this regard, by setting the fourteenth threshold value as described above, when a bright portion existing in the vicinity region is generated due to the influence of noise or the like, the presence of the bright portion can be ignored. . This is because noise is generated discretely in the image, so that it is possible to discriminate whether or not the influence of noise is caused by appropriately setting the 14th threshold value.

  The conditions shown in FIG. 20 and the brightness increase amount correction coefficient corresponding thereto are examples, and the brightness increase amount correction coefficient may be determined according to more detailed conditions. It may be determined itself.

− Emphasis processing performed together with reduction processing of the first embodiment −
FIG. 21 is a diagram conceptually illustrating an example of a processing procedure when an enhancement process is performed in addition to the reduction process described in the first embodiment. As shown in FIG. 21, the image processing parameters (image processing parameters for reduction processing) set in S508 (FIG. 5) are uniformly applied to the temporary image data generated from the original image data and reduced. After the processing, temporary image data is generated. In S508, an image processing parameter for enhancement processing is set together with an image processing parameter for reduction processing. Image processing parameters for enhancement processing can be set based on the conditions described with reference to FIG. 20, for example.

  After the temporary image data and the importance map are generated, image processing parameters for enhancement processing are applied to the original image data to perform enhancement processing, and post-processing original image data is generated. The post-processing original image data and the post-processing temporary image data are combined at a mixing ratio based on the degree-of-importance map generated in the degree-of-importance setting process of S514, and corrected image data is generated. At the time of synthesis, corrected image data is generated by mixing each pixel or a plurality of pixels at a mixing ratio corresponding to the degree of importance defined by the degree of importance map. As a result, at least one of the saturation, brightness, and contrast of the image corresponding to the region of lower importance is reduced. On the other hand, since the mixing ratio of the original image data after processing is relatively increased in the high-priority area, the image corresponding to the higher-priority area becomes more noticeable than the image in the other areas. It is possible to obtain an image that looks good.

  In the above, the example in which the processed original image data generated by performing the enhancement process on the original image data and the processed temporary image data generated by performing the reduction process on the temporary image data has been described. Instead of performing the above-described processing, the original image data is not subjected to the enhancement processing, and after obtaining the corrected image data by the procedure described in the first embodiment, the main image in the corrected image data is obtained. Emphasis processing may be performed on the data.

− Emphasis processing performed together with the reduction processing of the second embodiment −
FIG. 22 is a diagram conceptually illustrating an example of a processing procedure when emphasis processing is performed in addition to the reduction processing described in the second embodiment. As shown in FIG. 22, the image processing parameters (image processing parameters for reduction processing) set in S1308 (FIG. 13) are uniformly applied to the temporary image data generated from the original image data and reduced. Processing is performed, and post-processing temporary image data is generated. In S1308, an image processing parameter for enhancement processing is set together with an image processing parameter for reduction processing. Image processing parameters for enhancement processing can be set based on the conditions described with reference to FIG. 20, for example.

  After the temporary image data is generated, image processing parameters for enhancement processing are uniformly applied to the original image data to perform enhancement processing, and the processed original image data is generated. The peripheral image data in the post-processing temporary image data and the partial image data corresponding to the main part in the post-processing original image data are combined to generate corrected image data. The peripheral image is subjected to reduction processing, and at least one of saturation, brightness, and contrast is reduced. On the other hand, since the image of the main part has been subjected to an emphasis process, it becomes more conspicuous and an image that looks good can be obtained.

  In the above, the peripheral image data in the post-processing temporary image data generated by performing the reduction process on the temporary image data, and the partial image data in the post-processing original image data generated by performing the enhancement process on the original image data An example in which is synthesized has been described. Instead of performing the above-described processing, the original image data is not subjected to enhancement processing, and after obtaining corrected image data according to the procedure described in the second embodiment, main image data in the corrected image data is obtained. Emphasis processing may be performed on the above.

− Emphasis processing performed together with the reduction processing of the third embodiment −
FIG. 23 is a diagram conceptually illustrating a procedure example when the enhancement process is performed in addition to the reduction process described in the third embodiment. As shown in FIG. 23, temporary image data is generated from the original image data, and the image processing parameters (the image for reduction processing) set in S1508 (FIG. 15) for the peripheral image data in the temporary image data. Processing parameters) are applied, reduction processing is performed, and post-processing temporary image data is generated. In S1508, an image processing parameter for enhancement processing is set together with an image processing parameter for reduction processing. Image processing parameters for enhancement processing can be set based on the conditions described with reference to FIG. 20, for example.

  After the temporary image data is generated, image processing parameters for enhancement processing are applied to the image data corresponding to the main part of the original image data, that is, the partial image data, and the enhancement processing is performed. Partial image data is generated. At this time, when a plurality of main parts are set, a uniform main degree (for example, main degree = 1) is set for each main part, and the same emphasis processing is performed on each main part. It is possible to Alternatively, it is possible to set a different degree of importance for each main part, and to apply an emphasis process with different strengths to each main part according to the set level of the main degree. The peripheral image data in the temporary image data after processing and the partial image data after processing are combined to generate corrected image data. The peripheral image is subjected to reduction processing, and at least one of saturation, brightness, and contrast is reduced. On the other hand, since the image of the main part is subjected to an emphasis process, the image becomes more conspicuous and an image that looks good can be obtained.

  In the above, the post-processing temporary image data generated by performing the reduction process on the peripheral image data in the temporary image data, and the post-processing partial image data generated by performing the enhancement process on the partial image data in the original image data, An example in which is synthesized has been described. Instead of performing the above-described processing, the original image data is not subjected to enhancement processing, and after obtaining corrected image data according to the procedure described in the third embodiment, the main image data in the corrected image data is obtained. Emphasis processing may be performed on the above.

− Emphasis processing performed together with reduction processing of the fourth embodiment −
FIG. 24 is a diagram conceptually illustrating an example of a processing procedure when emphasis processing is performed in addition to the reduction processing described in the fourth embodiment. As shown in FIG. 24, the original image data is processed by applying the processing parameters set in S1710 based on the importance map derived in S1708 (FIG. 17), and corrected image data is generated. At this time, the image processing parameter for enhancement processing is applied corresponding to the portion with relatively high importance, while the image processing parameter for reduction processing is applied to the portion with relatively low importance. Image processing parameters for enhancement processing can be set based on the conditions described with reference to FIG. 20, for example.

  Through the processing described above, the peripheral image is subjected to reduction processing, and at least one of saturation, brightness, and contrast is reduced. On the other hand, the image of the main part is subjected to an emphasis process so that it becomes more conspicuous and an image that looks good can be obtained.

  As described above, the image processing apparatus according to each embodiment described above can be incorporated in the imaging apparatus, and the image processing program can be executed by a general-purpose computer. A processing apparatus may be realized.

  The image processing technique according to the present invention can be applied to a digital still camera, a digital movie camera, and the like. Furthermore, the present invention can be applied to a video recorder or a computer.

DESCRIPTION OF SYMBOLS 100 Image processing apparatus 102 Image data acquisition part 104 Area | region setting part 106 Image processing execution determination part 108 Correction | amendment image data generation part 150 Image display part 160 Image recording part 200 Digital camera 210 Shooting optical system 212 Lens drive part 220 Imaging part 230 Image recording Medium 240 Operation unit 250 Display unit 262 ROM
H.264 RAM
270, 310 CPU
300 Computer 320 Memory 330 Auxiliary Storage Device 340 Interface 350 Memory Card Interface 360 Optical Disk Drive 370 Network Interface 380 Display Device

Claims (21)

An image processing apparatus that acquires original image data that is image data to be processed and performs correction processing on the original image data,
An image data acquisition unit for acquiring the original image data;
An area setting unit that analyzes the original image data and sets a main part that is a partial area including a main subject in the original image data and a peripheral part that is a partial area other than the main part in the original image data. When,
An image processing execution determination unit that determines whether or not correction of the original image data is necessary based on either or both of saturation information and spatial frequency information in the main part,
When the image processing execution determination unit determines that the correction of the original image data is necessary, a corrected image that performs reduction processing on the peripheral image so that the image of the main part stands out relatively A data generation unit, comprising: a corrected image data generation unit that performs the reduction process so that at least one of brightness, contrast, and saturation of the peripheral image is decreased. An image processing apparatus.   The corrected image data generation unit performs the reduction process so that the saturation of the image in the peripheral part is further reduced when the saturation of the image in the peripheral part is higher than a predetermined value. The image processing apparatus according to claim 1.   The corrected image data generation unit performs the reduction process so that the brightness of the peripheral image is greatly reduced when the brightness of the peripheral image is larger than a predetermined value. The image processing apparatus according to claim 1.   The correction image data generation unit performs the reduction processing so that the contrast of the peripheral image is greatly decreased when the contrast of the peripheral image is higher than a predetermined value. The image processing apparatus according to any one of 1 to 3. The corrected image data generation unit
A post-processing temporary image data generating unit that generates temporary image data from the original image data, performs processing on the temporary image data, and generates post-processing temporary image data;
5. The image composition processing unit according to claim 1, further comprising: an image composition processing unit that performs a process of compositing the original image data and the post-processing temporary image data in units of pixels or in units of a plurality of pixels. Image processing device.   The image composition processing unit performs composition processing on any one of lightness information, pixel value, and saturation information of the original image data and the post-processing temporary image data when performing the composition processing. The image processing apparatus according to claim 5, wherein: A degree-of-importance setting unit that sets a degree of importance for each pixel or a plurality of pixels of the original image data based on a result of analyzing the original image data, wherein the pixels existing in the main part or the main of the plurality of pixels A degree-of-majority setting unit for setting the degree of importance so that the degree becomes maximum;
The image composition processing unit performs a process of mixing while changing a mixing ratio of the post-processing temporary image data according to the level of the degree of importance set for each pixel or each of a plurality of pixels by the degree of importance setting unit. The image processing apparatus according to claim 5 or 6.   The image composition processing unit performs a mixing process so that a mixing ratio of the post-processing temporary image data is increased corresponding to the pixel or the plurality of pixels having a lower importance set by the importance setting unit. The image processing apparatus according to claim 7, wherein the apparatus is an image processing apparatus. The corrected image data generation unit includes an image synthesis processing unit that performs a process of synthesizing the original image data with peripheral image data that is a part of image data corresponding to the peripheral part in the post-processing temporary image data. Prepared,
The image composition processing unit replaces image data of a portion corresponding to the peripheral portion in the original image data with the peripheral image data in the post-processing temporary image data, or the image data in the original image data. The image processing apparatus according to claim 5, wherein a process of mixing image data of a part corresponding to a peripheral part and the peripheral image data in the post-processing temporary image data is performed. The corrected image data generation unit performs the reduction process on peripheral image data, which is image data of a portion corresponding to the peripheral portion, in the temporary image data generated from the original image data, and a post-processing temporary image An image synthesis processing unit that generates data and performs a process of synthesizing the post-processing temporary image data and the original image data;
The image composition processing unit replaces the image data of the part corresponding to the peripheral part in the original image data with the peripheral image data in the post-processing temporary image data, or the peripheral part in the original image data 6. The image processing apparatus according to claim 5, wherein a process of mixing image data of a part corresponding to a part and the peripheral image data in the post-processing temporary image data is performed. A degree-of-importance setting unit that sets a degree of importance for each pixel or a plurality of pixels of the original image data based on a result of analyzing the original image data, wherein the pixels existing in the main part or the main of the plurality of pixels A degree-of-majority setting unit for setting the degree of importance so that the degree becomes maximum;
The image processing apparatus according to claim 1, wherein the corrected image data generation unit increases the intensity of the reduction process for a pixel or a plurality of pixels having a lower level of importance set by the importance setting unit. .   The corrected image data generation unit is further defined in a predetermined color space so that an image of the main part stands out when the image processing execution determination unit determines that the correction of the original image data is necessary. The image processing apparatus according to claim 1, wherein color coordinate values in image data of a main part are corrected.   The image processing apparatus according to claim 12, wherein the corrected image data generation unit corrects main part lightness information, which is information defining brightness or lightness of each pixel in the image data of the main part.   The image processing apparatus according to claim 13, wherein the correction of the main part lightness information includes correction for increasing a contrast of an image of the main part.   The correction image data generation unit, when correcting the main part lightness information, changes a correction amount of the main part lightness information according to the brightness of the image of the main part. The image processing apparatus described.   The corrected image data generation unit corrects the main part lightness information to increase the value of the main part lightness information when correcting the main part lightness information, and corrects the brightness of the image of the main part at this time. The lightness information of the main part is corrected so that the amount of increase when the brightness of the image of the main part is less than or equal to the predetermined value is greater than the amount of increase when the value is greater than a predetermined value. The image processing apparatus according to claim 13.   The corrected image data generation unit corrects the main part lightness information to increase the value of the main part lightness information when correcting the main part lightness information, and corrects the brightness of the image of the main part at this time. The image according to any one of claims 13 to 16, wherein when an area having a brightness exceeding 1 is present in the vicinity of the main part, correction is performed so that the amount of increase when the area increases is increased. Processing equipment.   The corrected image data generation unit corrects the main part lightness information by performing a gradation conversion process based on a gradation conversion characteristic derived by analyzing a histogram of the main part lightness information, and 16. The image processing apparatus according to claim 15, wherein the gradation width of the histogram of the main part brightness information is increased. An image processing method for performing correction processing on original image data, which is image data to be processed,
An image data acquisition procedure for acquiring the original image data;
An area setting procedure for analyzing the original image data and setting a main part that is a partial area including a main subject in the original image data and a peripheral part that is a partial area other than the main part in the original image data When,
An image processing execution determination procedure for determining whether or not correction of the original image data is necessary based on either or both of saturation information and spatial frequency information in the main part,
When it is determined that the correction of the original image data is necessary by the image processing execution determination procedure, a corrected image that performs a reduction process on the peripheral image so that the image of the main part stands out relatively A data generation procedure, comprising: a corrected image data generation procedure that performs the reduction process so that at least one of brightness, contrast, and saturation of the peripheral image is reduced. Image processing method. An imaging apparatus including an imaging element capable of photoelectrically converting a subject image formed by a photographing lens and outputting an image signal,
An image data acquisition unit that acquires image data generated from the image signal output from the image sensor as original image data;
An area setting unit that analyzes the original image data and sets a main part that is a partial area including a main subject in the original image data and a peripheral part that is a partial area other than the main part in the original image data. When,
An image processing execution determination unit that determines whether or not correction of the original image data is necessary based on either or both of saturation information and spatial frequency information in the main part,
When the image processing execution determination unit determines that the correction of the original image data is necessary, a corrected image that performs reduction processing on the peripheral image so that the image of the main part stands out relatively A data generation unit, comprising: a corrected image data generation unit that performs the reduction process so that at least one of brightness, contrast, and saturation of the peripheral image is decreased. An imaging device. An image processing program for causing a computer to execute processing for correcting original image data which is image data to be processed,
An image data acquisition step of acquiring the original image data;
A region setting step of analyzing the original image data and setting a main portion that is a partial region including a main subject in the original image data and a peripheral portion that is a partial region other than the main portion in the original image data. When,
An image processing execution determination step for determining whether or not correction of the original image data is necessary based on either or both of the saturation information and the spatial frequency information in the main part,
When it is determined in the image processing execution determination step that the correction of the original image data is necessary, a corrected image that performs reduction processing on the peripheral image so that the image of the main part stands out relatively A data generation step, comprising: a corrected image data generation step that performs the reduction process so that at least one of brightness, contrast, and saturation of the peripheral image is reduced. Image processing program.

Images