JP2023066444A - Image processing device, saturation compensation method, and program - Google Patents

Abstract

To provide an image processing device capable of compensating for deterioration of the saturation of a low luminance region due to adjustment of the luminance of an image.SOLUTION: The image processing device comprises: a scene determination index calculation unit which calculates a scene determination index indicative of a multitude of bluish or reddish regions among a plurality of regions included in an image; a luminance adjustment unit which adjusts the luminance of each region among the plurality of regions and determines the output luminance of each region; and a saturation correction unit which corrects the saturation component of each region based on the luminance, the output luminance, and the scene determination index.SELECTED DRAWING: Figure 1

Description

The present disclosure relates to an image processing device, a saturation compensation method, and a program.

Patent Document 1 discloses a liquid crystal display device that increases the saturation of a video signal for a specific hue when the average video level of the input video signal is low.

Japanese Patent Application Laid-Open No. 2000-039862

The average image level is relatively high for bright images and relatively low for dark images. However, when a bright image partially includes a low-luminance area, the average image level may be relatively high. In this case, in the liquid crystal display device disclosed in Patent Document 1, processing for increasing the saturation of the video signal is not executed for a specific hue, and there is a possibility that the saturation in the low-luminance region is low. Accordingly, an object of one aspect of the present disclosure is to provide an image processing device, a saturation compensation method, and a program capable of compensating for a decrease in saturation in a low-luminance region due to adjustment of luminance of an image.

An image processing apparatus according to an aspect of the present disclosure includes a scene determination index calculation unit that calculates a scene determination index indicating the number of regions that are blue-based or red-based among a plurality of regions included in an image; a luminance adjusting unit that adjusts the luminance of each area among the plurality of areas to determine the output luminance of each area; and the coloring of each area based on the luminance, the output luminance, and the scene determination index. and a saturation correction unit that corrects the saturation component.

A saturation compensation method according to an aspect of the present disclosure includes the steps of: calculating a scene determination index indicating the number of areas that are blue-based colors or red-based colors among a plurality of areas included in an image; determining the output luminance of each area by adjusting the luminance of each area of the areas; and correcting the saturation component of each area based on the luminance, the output luminance, and the scene determination index. and

A program according to an embodiment of the present disclosure, which provides a computer with a function of calculating a scene determination index indicating the number of regions that are blue-based or red-based among a plurality of regions included in an image; A function of adjusting the brightness of each region of the regions to determine the output brightness of each region; and correcting the saturation component of each region based on the brightness, the output brightness, and the scene determination index. and the function to execute.

It is a figure showing an example of composition of an image processing device concerning a first embodiment. 4 is a flow chart showing an example of the operation of the image processing device according to the first embodiment; It is a figure which shows an example of a hue histogram. It is a figure which shows an example of the ratio of the luminance of a red component, a green component, and a blue component. 5 is a graph showing an example of output luminance according to input luminance; It is a graph which shows an example of a luminance-linked coefficient. It is a figure which shows an example of a structure of the image processing apparatus which concerns on 2nd embodiment. FIG. 4 is a diagram showing an example of image scene determination information; 9 is a flow chart showing an example of the operation of the image processing apparatus according to the second embodiment; It is a figure which shows an example of the image processing apparatus which concerns on 3rd embodiment. FIG. 4 is a diagram showing an example of content scene determination information; 9 is a flow chart showing an example of operations performed by the image processing apparatus according to the third embodiment; FIG. 11 is a diagram showing an example of the configuration of an image processing apparatus according to a fourth embodiment; FIG. FIG. 11 is a flow chart showing an example of operations performed by an image processing apparatus according to a fourth embodiment; FIG.

(First embodiment)
FIG. 1 is a diagram showing an example of the configuration of an image processing apparatus 100. As shown in FIG. The image processing apparatus 100 includes a display unit 101, a storage unit 102, a control unit 103, and the like.

The image processing apparatus 100 corrects the brightness and saturation of the image 122 indicated by the acquired image information 121 and displays the corrected brightness and saturation output image on the display unit 101 . Specifically, the image processing apparatus 100 adjusts the luminance of the image 122 and corrects the saturation so as to increase the saturation of blue-based colors or red-based colors having relatively low luminance. A display unit 101 is a liquid crystal panel, an organic EL (Electro-luminescence) panel, or the like.

The storage unit 102 is a recording medium capable of recording various data, programs, etc. For example, the storage unit 102 is a storage device such as a RAM (Random Access Memory), a hard disk drive, or a flash memory.

The control unit 103 executes various processes according to programs and data stored in the storage unit 102 . For example, the control unit 103 can be implemented by a logic circuit formed in an integrated circuit such as an IC chip. Alternatively, the control unit 103 may be realized by software using a processor such as a CPU (Central Processing Unit).

The control unit 103 controls the image acquisition unit 111, the hue histogram generation unit 112, the scene determination index calculation unit 113, the brightness adjustment unit 114, the brightness-linked correction determination unit 115, the saturation correction coefficient determination unit 116, the saturation correction unit 117, and the like. Prepare.

The image acquisition unit 111 acquires image information 121 representing an image 122 . The image information 121 indicates pixel values of a plurality of matrix-shaped pixels included in the image 122 . For example, image information 121 indicates luminance Yin and saturation component 124 for each pixel contained in image 122 . The saturation component 124 includes a blue difference component Cb and a red difference component Cr regarding the saturation and hue of each pixel. The blue difference component Cb indicates a color component related to the saturation and hue of the blue color. The red difference component Cr indicates a color component related to the saturation and hue of reddish colors. That is, the image information 121 may be in a YCbCr format that indicates the luminance Y, the blue difference component Cb, and the red difference component Cr for each pixel included in the image 122 .

Alternatively, image information 121 may indicate a red component R, a green component G, and a blue component B for each pixel included in image 122 . The red component R, green component G, and blue component B indicate the intensity of the three primary colors of light, red, green, and blue, respectively. That is, the image information 121 may be in RGB format, indicating the red component R, the green component G, and the blue component B for each pixel included in the image 122 . When the image information 121 indicates a red component R, a green component G, and a blue component B for each pixel included in the image 122, the image acquisition unit 111 obtains the red component R and the green component indicated by the image information 121. From G and the blue component B, the luminance Yin and the saturation component 124 may be calculated.

The hue histogram generator 112 generates a hue histogram 123 that indicates the frequency of hues in each section of the image 122 indicated by the image information 121 .

The scene determination index calculation unit 113 calculates a scene determination index Sc that indicates the number of regions having blue-based colors or red-based colors among the plurality of regions included in the image 122 .

The luminance adjustment unit 114 adjusts the luminance Yin of each area among the plurality of areas included in the image 122 to determine the output luminance Yout of each area. The output luminance Yout of each area is the luminance of each area of the output image displayed on the display unit 101 . For example, each region is each pixel contained in image 122 . Alternatively, each region may be a region containing multiple pixels.

The brightness-linked correction determination unit 115 determines the brightness-linked coefficient A. FIG. When the luminance Yin is equal to or less than the correction threshold, the luminance-linked coefficient A has a larger value as the luminance Yin decreases.

The saturation correction coefficient determination unit 116 determines the saturation correction coefficient α for each region based on the luminance Yin, the output luminance Yout, and the scene determination index Sc. When the luminance Yin is equal to or less than the correction threshold, the saturation correction coefficient α has a larger value as the luminance Yin decreases.

The saturation correction unit 117 corrects the saturation component 124 of each region based on the luminance Yin, the output luminance Yout, and the scene determination index Sc. Specifically, the saturation correction unit 117 corrects each region based on the luminance Yin, the output luminance Yout, and the scene determination index Sc so as to increase the saturation of the regions where the luminance Yin is equal to or less than the correction threshold. Correct the saturation component 124 of the region. More specifically, the saturation correction unit 117 corrects the saturation component 124 of each region by applying the saturation correction coefficient α to the saturation component 124 of each region.

FIG. 2 is a flow chart showing an example of the operation of the image processing apparatus 100. As shown in FIG.

In step S<b>201 , the image acquisition unit 111 acquires image information 121 representing the image 122 . For example, the image information 121 is image information of a digital television broadcast program. Also, the image information 121 may be image information of a program acquired from a network such as the Internet. Also, the image information 121 may be image information stored in an external device such as a video camera or recording device connected to the image processing apparatus 100 .

Note that when the image information 121 indicates the red component R, the green component G, and the blue component B for each pixel included in the image 122, the image acquisition unit 111 obtains the red component R indicated by the image information 121, From the green component G and blue component B, luminance Yin, blue difference component Cb, and red difference component Cr are calculated. For example, the image acquisition unit 111 inputs the red component R, the green component G, and the blue component B indicated by the image information 121 into a calculation formula defined by the video standard, thereby obtaining the luminance Yin and the blue difference component. Cb and red-difference component Cr are calculated. Also, the image information 121 may be in the YCbCr format of luminance and color difference instead of the RGB format.

In step S202, the hue histogram generation unit 112 generates a hue histogram 123 from the image 122 indicated by the image information 121 acquired in step S201. For example, the hue histogram generator 112 calculates the hue of each pixel from the blue difference component Cb and the red difference component Cr of each pixel included in the image 122 . For example, the hue histogram generation unit 112 substitutes the blue difference component Cb and the red difference component Cr of each pixel into the arithmetic expression of hue H=tan ⁻¹ (Cr/Cb) to obtain the hue H of each pixel. calculate. Note that the hue calculation method is not limited to this formula. Then, the hue histogram generator 112 generates a hue histogram 123 from the hue of each pixel.

In step S203, the scene determination index calculation unit 113 performs scene determination based on the ratio between the integrated value of frequencies of a plurality of sections of blue-based colors or red-based colors indicated by the hue histogram 123 and the total number of frequencies indicated by the hue histogram 123. An index Sc is calculated. A blue-based color is a color in a predetermined range of hues including blue. For example, when the pixel values of the red component R, the green component G, and the blue component B of each pixel in the image 122 are represented by an 8-bit value, the blue color means that the red component R=0, the green component G=0 and It is a color with a blue component B=255. Further, reddish colors are colors in a predetermined range of hues including red. For example, when the pixel values of the red component R, the green component G, and the blue component of each pixel in the image 122 are represented by 8-bit values, the red component R=255, the green component G=0, and the blue component B=0 color.

FIG. 3 is a diagram showing an example of the hue histogram 123. As shown in FIG. Hues Hr, Hg, and Hb illustrated in FIG. 3 indicate hues of red, green, and blue, respectively. For example, the frequency of red hue Hr is the number of pixels in image 122 that have pixel values of red component R=255, green component G=0, and blue component B=0. Also, for example, the frequency of the green hue Hg is the number of pixels in the image 122 having pixel values of red component R=0, green component G=255, and blue component B=0. Also, for example, the frequency of the blue hue Hb is the number of pixels having pixel values of red component R=0, green component G=0, and blue component B=255 in the image 122 .

The frequency XB ₀ indicates the frequency of the section of the blue hue Hb. The frequency XB ₋₁ and the frequency XB ₁ indicate the frequency of the hue interval adjacent to the blue hue Hb. For example, when the hue of the section adjacent to the section of the hue Hb of blue is blue, the scene determination index calculation unit 113 calculates the sum of the frequency XB ₋₁ , the frequency XB ₀ and the frequency XB ₁ , A scene determination index Sc is calculated from the ratio to the total number of frequencies shown.

Alternatively, when the hue of the section adjacent to the section of the blue hue Hb is a blue color, the scene determination index calculation unit 113 calculates the average of the frequency XB ₋₁ , the frequency XB ₀ and the frequency XB ₁ , and the hue histogram 123. The scene determination index Sc may be calculated from the ratio to the total number of frequencies shown.

Alternatively, when the hue of the section adjacent to the section of blue hue Hb is a blue-based color, the scene determination index calculation unit 113 applies different weights to the frequency XB ₋₁ , the frequency XB ₀ , and the frequency XB ₁ . The scene determination index Sc may be calculated from the ratio between the integrated value and the total number of frequencies indicated by the hue histogram 123 . Here, the weight applied to the frequency of the blue-based hue section may be set smaller according to the distance from the blue hue Hb.

Alternatively, when the hue of the section adjacent to the section of blue hue Hb is a blue-based color, the scene determination index calculation unit 113 inputs the frequency XB ₋₁ , the frequency XB ₀ , and the frequency XB ₁ into a predetermined function. , the output value may be calculated as the scene determination index Sc.

The same applies to the case where the scene determination index Sc indicates the number of reddish color areas, and detailed description thereof will be omitted. In addition, the range in which the hue frequency of a plurality of sections of blue-based color or red-based color is integrated may be a section of hue of blue-based color or red-based color, and is more than a hue section adjacent to blue hue Hb. may be a wide section.

In subsequent step S<b>204 , brightness adjustment unit 114 determines a region of interest from a plurality of regions included in image 122 . A region of interest is a region selected from a plurality of regions included in the image 122 . For example, the region of interest is a pixel selected from a plurality of pixels included in image 122 .

In step S205, the luminance adjustment unit 114 adjusts the luminance Yin according to the luminance Yin of the attention area determined in step S204 to determine the output luminance Yout.

FIG. 4 is a diagram showing an example of the luminance ratio of the red component R, the green component G, and the blue component B. In FIG. As illustrated in FIG. 4, the green component G is relatively brighter than the red component R and the blue component B. As shown in FIG.

FIG. 5 is a graph showing an example of output luminance according to input luminance. In FIG. 5, the horizontal axis represents luminance, and the vertical axis represents output luminance. In the graph 501 illustrated in FIG. 5, the output luminance is the same as the input luminance. On the other hand, in the graph 502 illustrated in FIG. 5, when the input luminance is higher than the predetermined luminance Ya, the output luminance is higher than the input luminance, and when the input luminance is lower than the predetermined luminance Ya, the output Luminance is lower than input luminance.

For example, the brightness adjustment unit 114 determines the output brightness Yout as illustrated in the graph 502 to enhance the contrast of the image 122 . Specifically, when the luminance adjustment unit 114 determines the output luminance Yout by correcting the luminance Yin as illustrated in the graph 502, for example, the output luminance Ygo when the input region is mainly green is Since high green color is dominant, the luminance tends to be high, and is often higher than the luminance Ygi before correction. On the other hand, the output luminance Yro when the input region is mainly red is lower than the luminance Yri before correction. Similarly, the output luminance Ybo when the input region is mainly blue is lower than the luminance Ybi before correction.

In subsequent step S206, the saturation correction unit 117 calculates the luminance ratio between the luminance Yin of the attention area and the output luminance Yout determined in step S205.

In step S207, the luminance-linked correction determining unit 115 determines the luminance-linked coefficient A for the attention area.

FIG. 6 is a graph showing an example of the luminance-linked coefficient A. As shown in FIG. In FIG. 6, the horizontal axis is the luminance, and the vertical axis is the luminance-linked coefficient. In the graphs 601 and 602 illustrated in FIG. 6, the value of the luminance-linked coefficient A is 1 when the luminance is higher than the correction threshold value YTH. For example, when the saturation correction unit 117 multiplies the brightness Yin by the brightness-linked coefficient A, the product of the brightness-linked coefficient A and the brightness Yin is the same as the brightness Yin if the brightness Yin is higher than the correction threshold value YTH.

On the other hand, in the graphs 601 and 602, when the luminance is equal to or less than the correction threshold value YTH, the luminance-linked coefficient A is indicated by an attenuation function. That is, in the graphs 601 and 602, when the luminance is equal to or less than the correction threshold value YTH, the luminance-linked coefficient A has a larger value as the luminance decreases. For example, when the saturation correction unit 117 multiplies the luminance Yin by the luminance interlocking coefficient A, if the luminance is equal to or less than the correction threshold value YTH, the product of the luminance interlocking coefficient A and the luminance Yin increases as the luminance Yin decreases. be.

A graph 601 indicates that the luminance-linked coefficient A linearly increases as the luminance Yin decreases in the range where the luminance Yin is equal to or less than the correction threshold. Further, the graph 602 shows that the luminance-linked coefficient A increases nonlinearly as the luminance Yin decreases in the range where the luminance Yin is equal to or less than the correction threshold. Moreover, unlike the graph 602, the luminance-linked coefficient A may increase stepwise as the luminance Yin decreases in the range where the luminance is equal to or less than the correction threshold value YTH.

In the subsequent step S208, the saturation correction coefficient determination unit 116 performs the following calculation based on the luminance ratio calculated in step S206, the scene determination index Sc calculated in step S203, and the luminance-linked coefficient A determined in step S207. Determine the saturation correction coefficient α.

As illustrated in FIG. 6, assume that the value of the luminance-linked coefficient A is 1 when the luminance Yin is higher than the correction threshold value YTH. In that case, the saturation correction coefficient α=Yout/Yin calculated by Equation (1). That is, when the luminance Yin is higher than the correction threshold value YTH, the saturation correction coefficient α is determined by the ratio between the luminance Yin and the output luminance Yout.

On the other hand, as illustrated in FIG. 6, when the luminance is equal to or less than the correction threshold YTH, the value of the luminance-linked coefficient A is assumed to be greater than one. Here, since the scene determination index Sc indicates the number of blue-based or red-based color regions, the larger the number of blue-based or red-based regions in the image 122, the larger the value of the scene determination index Sc. . Therefore, when the luminance is equal to or less than the correction threshold value YTH, the more bluish or reddish color regions in the image 122, the larger the saturation correction coefficient α calculated by Equation (1). That is, in the image 122, the more blue-based or red-based color regions with relatively low luminance, the larger the saturation correction coefficient α calculated by Equation (1).

In step S209, the saturation correction unit 117 corrects the saturation component 124 of the attention area based on the saturation correction coefficient α calculated in step S208. Specifically, the saturation correction unit 117 applies the saturation correction coefficient α to at least one selected from the group consisting of the blue-difference component Cb and the red-difference component Cr to correct the saturation of the region of interest. Correct component 124 .

For example, it is assumed that the saturation correction unit 117 corrects the blue difference component Cb of the attention area according to expression (2). Cbi shown in Equation (2) is the blue difference component before correction of the region of interest. Cbo shown in Equation (2) is the corrected blue-difference component of the region of interest. When the saturation correction coefficient α>1, Cbo>Cbi. That is, when the saturation correction coefficient α>1, the value of the corrected blue difference component Cbo in the region of interest is greater than the value of the uncorrected blue difference component Cbi in the region of interest.

Similarly, for example, the chroma correction unit 117 corrects the red-difference component Cr of the region of interest according to Equation (3). Cri shown in Equation (3) is the red color difference component before correction of the region of interest. Cro shown in Equation (3) is the corrected red-difference component of the region of interest. If the saturation correction coefficient α>1, then Cro>Cri. That is, when the saturation correction coefficient α>1, the value of the corrected red-difference component Cro of the region of interest is greater than the value of the red-difference component Cri of the region of interest before correction.

The saturation S increases as the absolute value of the blue difference component Cb and the absolute value of the red difference component Cr increase. For example, when the saturation S is calculated by an arithmetic expression of saturation S=(Cb ² +Cr ² ) ^1/2 , the arithmetic expression includes the blue difference component Cbo after correction of the attention area and the after correction of the attention area. By substituting the red difference component Cro of , the corrected chroma of the attention area can be calculated.

As a result, even when the output luminance Yout of the blue-based color or the red-based color is higher than the luminance Yin, the saturation correction unit 117 makes the corrected blue-based color or red-based color area vivid. can.

Similarly, the saturation correction unit 117 increases the luminance of the relatively high luminance area, and the output luminance Yout of the relatively low luminance blue-based color or red-based color area is lower than the luminance Yin. Even in this case, the blue-based color or red-based color region can be made vivid.

In step S210, the saturation correction unit 117 determines whether or not all areas included in the image 122 have been selected as attention areas. If not all areas included in the image 122 have been selected as attention areas in step S210, the control unit 103 returns the process to step S204. That is, the control unit 103 repeats the processing of steps S204 to S210 until the brightness and saturation of all regions included in the image 122 are corrected. On the other hand, if all areas included in the image 122 are selected as attention areas in step S210, the control unit 103 shifts the process to step S211.

In step S<b>211 , the saturation correction unit 117 outputs to the display unit 101 an output image having the output luminance Yout and the saturation component 124 determined in step S<b>209 for all regions included in the image 122 . As a result, the display unit 101 can display an output image that compensates for a decrease in saturation in a low-luminance area due to luminance adjustment.

As described above, the image processing apparatus 100 according to the present embodiment performs correction so as to increase the saturation of the low-luminance area according to the number of blue-based color or red-based color areas. As a result, the image processing apparatus 100 according to the present embodiment can compensate for a decrease in saturation in low-luminance areas due to adjustment of the luminance of an image according to the number of blue-based color or red-based color areas.

(Second embodiment)
A second embodiment will be described with reference to FIGS. 7 to 9. FIG. In the drawings, the same or equivalent elements are denoted by the same reference numerals, and overlapping descriptions are omitted. Configurations and processes having substantially the same functions as those of the first embodiment will be referred to by common reference numerals, description thereof will be omitted, and differences from the first embodiment will be described.

FIG. 7 is a diagram showing an example of the configuration of the image processing apparatus 100 according to this embodiment. The difference between the image processing apparatus 100 illustrated in FIG. 7 and the image processing apparatus 100 illustrated in FIG. 1 is that the image processing apparatus 100 illustrated in FIG. , a scene type information acquisition unit 701 and a scene determination index calculation unit 702 are provided. Furthermore, in the image processing apparatus 100 illustrated in FIG. 7, the image scene determination information 711 is stored in the storage unit 102 .

The scene type information obtaining unit 701 obtains the image scene type information 712 from the image information 121 when the image information 121 includes the image scene type information 712 indicating the type of the scene. The image scene type information 712 is information for identifying the main subject of the image 122 indicated by the image information 121 . For example, the main subject of the image 122 is the subject with the largest subject image area in the image 122 .

When the image information 121 includes the image scene type information 712, the scene determination index calculator 702 sets the index associated with the scene type indicated by the image scene type information 712 as the scene determination index Sc. Specifically, when the image information 121 includes the image scene type information 712 , the scene determination index calculation unit 702 calculates an index associated with the scene type indicated by the image scene type information 712 in the image scene determination information 711 . The scene determination index is set to Sc.

FIG. 8 is a diagram showing an example of the image scene determination information 711. As shown in FIG. In the image scene determination information 711, registered scene type information and indices are associated. For example, in the image scene determination information 711, character strings such as sea, lake, river, blue fish, red fish, blue flower, and red flower are registered as registration scene type information. Further, in the image scene determination information 711, the character string "sea", which is the registered scene type information, is associated with the numerical value of 0.5, which is the index. Further, for example, in the image scene determination information 711 illustrated in FIG. 8, the character string "red flower" which is the scene type information is associated with the numerical value of 0.8 which is the index.

For example, the image scene determination information 711 is registered by the manufacturer of the image processing apparatus 100 or the like. Alternatively, the image processing apparatus 100 may download the image scene determination information 711 from the website of the manufacturer of the image processing apparatus 100 via the Internet.

FIG. 9 is a flow chart showing an example of the operation of the image processing apparatus 100 according to this embodiment. Since the processing of step S901 illustrated in FIG. 9 is the same as the processing of step S201 illustrated in FIG. 2, detailed description thereof will be omitted.

When the image acquisition unit 111 acquires the image information 121 in step S901, the scene determination index calculation unit 702 determines whether the image information 121 includes the image scene type information 712 in step S902. When the image information 121 does not include the image scene type information 712 in step S902, the control unit 103 shifts the processing to step S202 illustrated in FIG. On the other hand, if the image information 121 includes the image scene type information 712 in step S902, the control unit 103 shifts the process to step S903.

In step S903, the scene determination index calculation unit 702 sets the index associated with the image scene type information 712 as the scene determination index Sc. Specifically, the scene determination index calculation unit 702 sets an index associated with the same registered scene type information as the image scene type information 712 in the image scene determination information 711 as the scene determination index Sc. Then, the control unit 103 shifts the processing to step S904. Since the processing of steps S904 to S908 is the same as the processing of steps S204 to S208 illustrated in FIG. 2, detailed description thereof will be omitted.

If the saturation correction coefficient determination unit 116 determines the saturation correction coefficient α in step S908, the saturation correction unit 117 determines the saturation correction coefficient α calculated in step S908 based on the saturation correction coefficient α calculated in step S908. The degree component 124 is corrected. Specifically, the saturation correction unit 117 corrects the saturation component 124 of the attention area by applying the saturation correction coefficient α calculated in step S908 to the saturation component of the attention area. Then, the control unit 103 shifts the process to step S910. Since the processing of steps S910 to S911 is the same as the processing of steps S210 to S211 illustrated in FIG. 2, detailed description thereof will be omitted.

As described above, when the image scene type information 712 is included in the image information 121, the image processing apparatus 100 according to the present embodiment uses the index associated with the image scene type information 712 to determine whether the luminance Yin is equal to or less than the correction threshold. Correct the saturation component 124 in a certain area. As a result, the image processing apparatus 100 according to the present embodiment can correct the saturation component 124 in the area where the luminance Yin is equal to or less than the correction threshold for the image of the designated scene. Therefore, the image processing apparatus 100 according to the present embodiment can compensate for the decrease in saturation in the low-luminance region due to the adjustment of the luminance of the image for the image of the designated scene.

(Third embodiment)
A third embodiment will be described with reference to FIGS. 10 to 12. FIG. In the drawings, the same or equivalent elements are denoted by the same reference numerals, and overlapping descriptions are omitted. Configurations and processes having substantially the same functions as those of the first embodiment will be referred to by common reference numerals, description thereof will be omitted, and differences from the first embodiment will be described.

FIG. 10 is a diagram showing an example of an image processing apparatus 100 according to this embodiment. The difference between the image processing apparatus 100 illustrated in FIG. 10 and the image processing apparatus 100 illustrated in FIG. 1 is that the image processing apparatus 100 illustrated in FIG. and the scene determination index calculation unit 113, a scene type information acquisition unit 1002 and a scene determination index calculation unit 1003 are provided. Further, the storage unit 102 of the image processing apparatus 100 illustrated in FIG. 10 stores content scene determination information 1011 .

Content acquisition unit 1001 acquires content 1012 including image 122 . For example, the content 1012 is data such as digital television broadcast programs and movies. Also, the content 1012 may be data such as programs and movies acquired from a network such as the Internet. Also, the content 1012 may be data stored in an external device such as a video camera or recording device connected to the image processing apparatus 100 .

The scene type information acquisition unit 1002 acquires the content scene type information 1013 from the content 1012 when the content 1012 including the image 122 includes the content scene type information 1013 indicating the type of the scene. The content scene type information 1013 is information for identifying the type of main scene indicated by the image 122 included in the content 1012 . Here, the main scene represented by the image 122 included in the content 1012 is the scene represented by the image 122 with the highest frequency.

When the content 1012 includes the content scene type information 1013, the scene determination index calculator 1003 sets the index associated with the scene type indicated by the content scene type information 1013 as the scene determination index Sc.

FIG. 11 is a diagram showing an example of the content scene determination information 1011. As shown in FIG. In the content scene determination information 1011, registered scene type information is associated with an index. For example, as exemplified in FIG. 11, in the content scene determination information 1011, character strings such as "under the sea" and "by the lake" are registered as the registration scene type information. Furthermore, for example, in the content scene determination information 1011 illustrated in FIG. 11, the character string "under the sea", which is the registered scene type information, is associated with the numerical value of 0.5, which is the index.

For example, the content scene determination information 1011 is registered by the manufacturer of the image processing apparatus 100 or the like. Alternatively, the image processing apparatus 100 may download the content scene determination information 1011 from the site of the manufacturer of the image processing apparatus 100 via the Internet.

FIG. 12 is a flowchart showing an example of operations performed by the image processing apparatus 100 according to this embodiment.

In step S<b>1201 , the content acquisition unit 1001 acquires content 1012 including image information 121 . In step S<b>1202 , the image acquisition unit 111 acquires image information 121 included in the content 1012 .

In step S<b>1203 , the scene determination index calculation unit 702 determines whether the content 1012 includes the content scene type information 1013 . When the image information 121 does not include the content scene type information 1013 in step S1203, the control unit 103 shifts the processing to step S202 illustrated in FIG. On the other hand, if the image information 121 includes the content scene type information 1013 in step S1203, the control unit 103 shifts the process to step S1204.

In step S1204, the scene determination index calculation unit 1003 sets an index associated with the same registered scene type information as the content scene type information 1013 acquired in step S1203 in the content scene determination information 1011 as a scene determination index Sc. . Then, the control unit 103 shifts the processing to step S1205. Since the processing of steps S1205 to S1209 is the same as the processing of steps S204 to S208 illustrated in FIG. 2, detailed description thereof will be omitted.

If the saturation correction coefficient determination unit 116 determines the saturation correction coefficient α in step S1209, in step S1210 the saturation correction unit 117 determines the saturation correction coefficient α determined in step S1209 based on the saturation correction coefficient α determined in step S1209. The degree component 124 is corrected. Specifically, the saturation correction unit 117 corrects the saturation component 124 of the attention area by applying the saturation correction coefficient α to the saturation component 124 of the attention area. Then, the control unit 103 shifts the process to step S1211. Since the processing of steps S1211 and S1212 is the same as the processing of steps S210 and S211 illustrated in FIG. 2, detailed description thereof will be omitted.

As described above, when the content scene type information 1013 is included in the content 1012, the image processing apparatus 100 according to the present embodiment uses the index associated with the content scene type information 1013 to determine whether the luminance Yin is equal to or less than the correction threshold. Correct the saturation component 124 of the region. As a result, the image processing apparatus 100 according to the present embodiment can correct the saturation component 124 in the area where the luminance Yin is equal to or less than the correction threshold for the content 1012 including the image 122 of the designated scene. Therefore, the image processing apparatus 100 according to the present embodiment can compensate for a decrease in saturation in a low-luminance area due to adjustment of the luminance of the image with respect to the content 1012 including the specified scene.

(Fourth embodiment)
A fourth embodiment will be described with reference to FIGS. In the drawings, the same or equivalent elements are denoted by the same reference numerals, and overlapping descriptions are omitted. Configurations and processes having substantially the same functions as those of the first embodiment will be referred to by common reference numerals, description thereof will be omitted, and differences from the first embodiment will be described.

FIG. 13 is a diagram showing an example of the configuration of the image processing apparatus 100 according to this embodiment. The difference between the image processing apparatus 100 illustrated in FIG. 13 and the image processing apparatus 100 illustrated in FIG. 1 is that the image processing apparatus 100 illustrated in FIG. The point is that an object identification unit 1301 and a scene determination index calculation unit 1302 are provided instead.

An object identification unit 1301 identifies a subject image included in the image 122 . The scene determination index calculation unit 1302 calculates a scene determination index Sc from at least one selected from the group consisting of the type, color, and size of the subject indicated by the subject image identified by the object identification unit 1301 .

FIG. 14 is a flowchart showing an example of operations performed by the image processing apparatus 100 according to this embodiment. It is assumed that when the control unit 103 starts the process of step S1401, the feature amount of the object and the type of the object are stored in the storage unit 102 in association with each other. Since the processing of step S1401 illustrated in FIG. 14 is the same as the processing of step S201 illustrated in FIG. 2, detailed description thereof will be omitted.

When the image acquisition unit 111 acquires the image information 121 indicating the image 122 in step S1401, the object identification unit 1301 performs image processing on the image 122 in step S1402 to identify the subject image included in the image 122. do.

In step S1403, the scene determination index calculation unit 1302 calculates a scene determination index Sc from at least one selected from the group consisting of the type, color, and size of the subject image identified in step S1402. For example, the object identification unit 1301 detects the feature amount of the subject image included in the image 122 . The object identification unit 1301 identifies the type, color, and size of the subject image included in the image 122 from the detected feature amount.

For example, assume that the scene determination index calculation unit 1302 determines that the subject image included in the image 122 is a fish in the sea. In this case, the scene determination index calculation unit 1302 determines that the smaller the ratio of the subject image in the entire image 122, the higher the ratio of the seawater region, and the scene determination index calculation unit 1302 calculates the scene determination index so that the value of the scene determination index Sc increases. Calculate Sc. Then, the control unit 103 shifts the processing to step S1404. Since the processing of steps S1404 to S1411 is the same as the processing of steps S204 to S211 illustrated in FIG. 2, detailed description thereof will be omitted.

As described above, the image processing apparatus 100 according to the present embodiment corrects the chroma component 124 in the area where the luminance Yin is equal to or less than the correction threshold, according to the subject image included in the image 122 . Therefore, the image processing apparatus 100 according to the present embodiment can compensate for the decrease in saturation in the low-luminance region due to the luminance adjustment of the image according to the subject image included in the image 122 .

The present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope indicated in the claims. Embodiments obtained by appropriately combining technical means disclosed in different embodiments is also included in the technical scope of the present invention. Furthermore, new technical features can be formed by combining the technical means disclosed in each embodiment.

100 image processing device, 101 display unit, 102 storage unit, 103 control unit, 111 image acquisition unit, 112 hue histogram generation unit, 113 scene determination index calculation unit, 114 brightness adjustment unit, 115 brightness-linked correction determination unit, 116 saturation Correction coefficient determination unit 117 Saturation correction unit 121 Image information 122 Image 123 Hue histogram 124 Saturation component 701 Scene type information acquisition unit 702 Scene determination index calculation unit 711 Image scene determination information 712 Image scene Type information 1001 content acquisition unit 1002 scene type information acquisition unit 1003 scene determination index calculation unit 1011 content scene determination information 1012 content 1013 content scene type information 1301 object identification unit 1302 scene determination index calculation unit

Claims (11)

a scene determination index calculation unit that calculates a scene determination index indicating the number of regions that are blue-based or red-based among a plurality of regions included in an image;
a brightness adjustment unit that adjusts the brightness of each region among the plurality of regions to determine the output brightness of each region;
a saturation correction unit that corrects a saturation component of each region based on the luminance, the output luminance, and the scene determination index;
An image processing device comprising: The saturation correction unit corrects the saturation component based on the luminance, the output luminance, and the scene determination index so as to increase the saturation of the regions having the luminance equal to or lower than the correction threshold for each of the regions. 2. The image processing apparatus according to claim 1, wherein: determining a saturation correction coefficient for each region based on the luminance, the output luminance, and the scene determination index, and determining the saturation correction coefficient for the luminance when the luminance is equal to or less than the correction threshold further comprising a saturation correction coefficient determination unit having a value as large as
3. The image processing apparatus according to claim 2, wherein said saturation correction unit applies said saturation correction coefficient to said saturation component of each region to correct said saturation component. The saturation correction coefficient determination unit determines the saturation correction coefficient for each region further based on a luminance-linked coefficient, which is a value that increases as the luminance decreases when the luminance is equal to or less than the correction threshold. The image processing apparatus according to claim 3. a hue histogram generation unit that generates a hue histogram indicating the frequency of each hue section of the image;
The scene determination index calculation unit calculates the scene determination index from a ratio of an integrated value of frequencies of a plurality of intervals of blue-based colors or red-based colors indicated by the hue histogram to the total number of frequencies indicated by the hue histogram. The image processing apparatus according to any one of claims 1 to 4, wherein the image processing apparatus calculates. Claims 1 to 3, wherein, when image information indicating the image includes image scene type information indicating a scene type, the scene determination index calculation unit uses an index associated with the scene type as the scene determination index. 6. The image processing device according to any one of 5. Claims 1 to 6, wherein, when the content including the image includes content scene type information indicating a scene type, the scene determination index calculation unit uses an index associated with the scene type as the scene determination index. The image processing device according to any one of . further comprising an object identification unit that identifies a subject image included in the image;
8. The scene determination index calculator according to any one of claims 1 to 7, wherein the scene determination index calculation unit calculates the scene determination index from at least one selected from the group consisting of the type, color, and size of the subject indicated by the subject image. The image processing device according to . The saturation component includes a blue difference component and a red difference component,
wherein the saturation correction unit corrects the saturation component by applying the saturation correction coefficient to at least one selected from the group consisting of the blue color difference component and the red color difference component for each of the regions. Item 9. The image processing device according to any one of items 1 to 8. a step of calculating a scene determination index indicating the number of areas that are blue-based colors or red-based colors among a plurality of areas included in the image;
adjusting the brightness of each region of the plurality of regions to determine the output brightness of each region;
correcting the saturation component of each region based on the luminance, the output luminance, and the scene determination index;
Saturation compensation method including. to the computer,
A function of calculating a scene determination index indicating the number of areas that are blue-based colors or red-based colors among a plurality of areas included in an image;
a function of adjusting the brightness of each region of the plurality of regions to determine the output brightness of each region;
a function of correcting the saturation component of each region based on the luminance, the output luminance, and the scene determination index;
program to run.

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