Video viewing device and program

Abstract

To enable a user to easily confirm where particular color compensation is applied when particular color compensation is applied during conversion of a color gamut of a video.SOLUTION: A video viewing device comprises a particular color compensation determination processing unit and a display. The particular color compensation determination processing unit obtains a correction factor for correcting the chroma of a pixel in an image that is input when the color of the pixel meets a prescribed condition within the image, determines whether the pixel is subject to correction on the basis of the value of the obtained correction factor, and converts the pixel value of the pixel that is not subject to correction into a grayscale pixel value. The display displays an image output by the particular color compensation determination processing unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a video viewing device and a program. [Background technology]

[0002] In order to broadcast an HDR / wide color gamut program as an SDR / standard color gamut program on high-definition television, it is necessary to convert the dynamic range and color gamut from HDR to SDR. Note that "HDR" stands for High Dynamic Range, and "SDR" stands for Standard Dynamic Range.

[0003] For live broadcasts, the output from the broadcast camera is split into HDR and SDR, and each video signal is viewed by a video engineer (VE), allowing HDR / wide color gamut programs and SDR / standard color gamut programs to be produced simultaneously.

[0004] In this case, video engineers manage the video signals by using video signal monitoring devices such as WFMs (Waveform Monitors) and vectorscopes to combine HDR / wide color gamut video signals and SDR / standard color gamut video signals.

[0005] For example, Patent Document 1 describes a conversion process between HLG (Hybrid Log Gamma) video and SDR video.

[0006] Furthermore, in the prior art, there was a method of specifying the range of lightness and hue angle in a color space formed by lightness, hue angle, and saturation in order to extract skin color.

[0007] For example, in Non-Patent Document 1, skin color is extracted based on the range of lightness and hue angle. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] Japanese Patent Publication No. 2020-025241 [Non-patent literature]

[0009] [Non-Patent Document 1] Recommendation ITU-R BT.2020-2 “Parameter values ​​for ultra-high definition television systems for production and international program exchange”. Summary of the Invention [Problem to be solved by the invention]

[0010] In conventional techniques (for example, Non-Patent Document 1), skin color is extracted only within the range of lightness and hue angle, which causes the problem that highly saturated colors that are not perceived as skin color are also extracted as skin color. It is desirable to extract specific colors using a more appropriate method than a method that extracts specific colors only within the range of lightness and hue angle.

[0011] Furthermore, the coordinate positions of the six RGBCYM colors are determined for each color space on a vectorscope. When a test pattern such as a color bar is input, it is possible to determine whether the signal is correct or not by checking whether the six RGBCYM colors in the input signal are located at those coordinates. RGBCYM stands for red, green, blue, cyan, yellow, and magenta, respectively.

[0012] However, when simultaneously producing the above-mentioned HDR / wide color gamut program and SDR / standard color gamut program, the following problem occurs when producing the SDR / standard color gamut program by converting the video from the HDR / wide color gamut program: the six RGBCYM colors differ from the coordinate positions prepared in advance within the vectorscope due to differences in the conversion algorithm.

[0013] In other words, the first issue is that when producing SDR / standard color gamut program footage through dynamic range conversion and color gamut conversion from HDR / wide color gamut program footage, it is not possible to determine whether the intended conversion algorithm has been applied correctly.

[0014] Furthermore, in a video viewing device for HDR / wide color gamut video signals, if skin color correction processing is added during dynamic range conversion and color gamut conversion from HDR to SDR, there is a problem in that it is not possible to confirm on the picture screen of the video viewing device which parts of the skin color will be applied to by the skin color correction processing.

[0015] The method of extracting skin color based only on the range of lightness and hue angle, as described in Non-Patent Document 1, has the problem that highly saturated colors that are not actually perceived as skin color are also extracted as skin color.

[0016] In other words, the second problem is that when specific color correction processing is added during video conversion processing, it is not possible to confirm which part of the HDR / wide color gamut video signal the specific color correction processing will be applied to.

[0017] The present invention was made based on the recognition of the above problems, and aims to provide an image viewing device and a program that can solve at least one of the first and second problems mentioned above. [Means for solving the problem]

[0018] [1] In order to solve the above problem, a video viewing device according to one aspect of the present invention is provided, which is configured to adjust the saturation of pixels in an input image whose color satisfies a predetermined condition in the image by using a correction factor f cor and calculate the correction factor f cora specific color correction determination processing unit that determines whether the pixel is a correction target or not based on the value of the specific color correction determination processing unit, and converts the pixel value of the pixel that is not a correction target into a grayscale pixel value; and a display unit that displays the image output by the specific color correction determination processing unit.

[0019] [2] In addition, in one aspect of the present invention, in the video viewing device (the video viewing device described in [1] above), the specific color correction determination processing unit determines the correction factor f cor and the correction factor f is continuously changed in response to a change in the hue angle of the pixel. cor , which is what we seek.

[0020] [3] Furthermore, one aspect of the present invention is that in the above-mentioned video viewing device (the video viewing device described in [1] or [2] above), the specific color correction determination processing unit changes the saturation to zero when the color of the pixel that is not the target of correction is expressed by lightness, hue angle, and saturation.

[0021] [4] In addition, according to one aspect of the present invention, in the above-mentioned video viewing device (the video viewing device described in the above [3]), the specific color correction determination processing unit is cor If the value of f indicates that the saturation of the pixel is not to be corrected, the saturation of the pixel is changed to zero, and the correction factor f cor If the value of indicates that the saturation of the pixel is to be corrected, the saturation of the pixel is not changed.

[0022] [5] Furthermore, one aspect of the present invention is the video viewing device described above (the video viewing device described in [3] above), wherein the correction factor f cor has the effect of reducing the saturation of the pixel, and the specific color correction judgment processing unit further changes the saturation of the pixel to zero if the degree to which the saturation of the pixel is reduced by the correction is lower than a predetermined threshold value.

[0023] [6] Furthermore, one aspect of the present invention is that the above-mentioned video viewing device (the video viewing device described in any one of [1] to [5] above) further comprises an average / maximum level calculation unit that calculates at least one of the maximum level and the average level for pixels in the image that are determined by the specific color correction determination processing unit to be pixels to be corrected, and the display unit further displays at least one of the maximum level and the average level calculated by the average / maximum level calculation unit.

[0024] [7] Furthermore, one aspect of the present invention is a video viewing device (video viewing device described in any one of [1] to [6] above), further comprising: a color gamut determination processing unit that determines the color gamut of the image; a vector data conversion unit that converts the colors contained in the image into vector data representing coordinates in a predetermined color space based on the determined color gamut; a reference color coordinate selection unit that selects coordinate values ​​in the predetermined color space of a reference color based on the determined color gamut; an image synthesis processing unit that synthesizes an image obtained by superimposing an image represented by the vector data that is the conversion result by the vector data conversion unit and a mark indicating the position represented by the coordinate value selected by the reference color coordinate selection unit; and an image selection unit that selects whether to display the image output by the specific color correction determination processing unit or the image output by the image synthesis processing unit, and the display unit displays the image selected by the image selection unit.

[0025] [8] Furthermore, one aspect of the present invention is that in the above-mentioned video viewing device (the video viewing device described in [7] above), the reference colors are red (R), green (G), blue (B), cyan (C), magenta (M), and yellow (Y) for 75% Hybrid Log Gamma (HLG) and 100% Hybrid Log Gamma (HLG), respectively.

[0026] [9] In addition, one aspect of the present invention is a method for correcting the saturation of pixels in an input image whose color satisfies a predetermined condition in the image by using a correction factor f cor and calculate the correction factor f corand a specific color correction determination processing unit that determines whether the pixel is a correction target or not based on the value of the specific color correction determination processing unit, and converts the pixel value of the pixel that is not a correction target into a grayscale pixel value. [Effects of the Invention]

[0027] According to the present invention, the video viewing device displays the areas of the image that are not subject to saturation correction in grayscale, allowing the user of the video viewing device to easily distinguish the areas that are subject to correction from the other areas by viewing the displayed image. [Brief explanation of the drawings]

[0028] [Figure 1] 1 is a block diagram showing a schematic functional configuration of a video viewing device according to an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram showing the internal functional configuration of a picture image generating unit in the embodiment. [Figure 3] 3 is a block diagram showing the internal functional configuration of a specific color correction application area extraction unit in the embodiment. FIG. [Figure 4] 2 is a schematic diagram showing a range that should be extracted as skin color in the CIELAB color space by the image viewing device according to the embodiment. FIG. [Figure 5] FIG. 2 is a block diagram showing the internal functional configuration of a vector image generation unit in the embodiment. [Figure 6] 10 is a schematic diagram showing an example of a vectorscope diagram displayed by the video viewing device according to the embodiment (in the case of a wide color gamut (BT.2020)). FIG. [Figure 7] 10 is a schematic diagram showing an example of a vectorscope diagram displayed by the video viewing device according to the embodiment (in the case of a standard color gamut (BT.709)). FIG. [Figure 8] 10 is an example of a graph showing the relationship between the hue angle hab and the lightness function value L* f in the image correction process that is the premise of the embodiment. [Figure 9]10 is an example of a graph showing the relationship between the hue angle hab and the saturation correction parameter function value σf in the image correction process that is the premise of the embodiment. [Figure 10] 10 is an example of a graph showing the relationship between lightness L* and saturation correction parameter σf in image correction processing that is a premise of the embodiment. [Figure 11] 10 is a graph showing an example of the input / output relationship of a decreasing function that has the effect of making the effect of skin color correction processing less effective as saturation increases in the image correction processing according to the embodiment. [Figure 12] FIG. 2 is a block diagram showing an example of the internal configuration of the video viewing device of the embodiment when implemented by a computer. [Figure 13] 10 is a schematic diagram showing an example of an image (binary image) representing a region to be subjected to specific color correction extracted by a specific color correction determination processing unit in the embodiment. FIG. [Figure 14] 10 is a schematic diagram showing an example of an image in which the specific color correction determination processing unit in the embodiment retains the color of only the area to be corrected for the specific color and grayscales the other areas. FIG. [Figure 15] FIG. 10 is a schematic diagram showing the coordinates of each color (reference color) on a vectorscope output by a vector image generation unit in the embodiment when converting an HDR / wide color gamut video signal into an SDR / standard color gamut video signal. DETAILED DESCRIPTION OF THE INVENTION

[0029] Next, an embodiment of the present invention will be described with reference to the drawings.

[0030] As mentioned above, when producing SDR / standard color gamut program video by performing dynamic range conversion and color gamut conversion from HDR / wide color gamut program video, there is a problem in that it is not possible to determine whether the intended conversion algorithm has been applied correctly. This embodiment solves this problem by making it possible to display the vectorscope coordinates obtained by the intended conversion algorithm on the video viewing device.

[0031] Furthermore, when specific color (e.g., skin tone) correction processing is added to the conversion processing, there is a problem in that it is not possible to confirm which parts of the HDR / wide color gamut video signal have been subjected to the skin tone correction processing. This embodiment solves this problem by displaying only the parts to which the specific color correction processing has been applied in color, and displaying the parts to which the specific color correction processing has not been applied in grayscale (displaying in white, black, and intermediate colors). Furthermore, this embodiment extracts only the skin tone area, and makes it possible to display the average skin level and maximum skin level as numerical data.

[0032] In this embodiment, the specific color is a color within a predetermined range in a three-dimensional space expressed by lightness, hue angle, and saturation. An example of the specific color is skin color. Skin color is also known as pale orange, and is one of the names for human skin colors commonly seen in East Asia. A specific example of specific color correction in this embodiment is skin color correction. Examples of the procedure for specific color correction processing will be described later.

[0033] The video to be processed by the video viewing device according to this embodiment is a series of consecutive frame images arranged in the time direction. In other words, the video processing by the video viewing device is reduced to processing of each of these frame images. In the following explanation, an RGB signal is a signal that represents an image (video) in the form of independent R (red), G (green), and B (blue). Furthermore, a CIELAB signal is an image (video) signal that conforms to the color space established by the International Commission on Illumination (CIE). L represents lightness, a represents the position between magenta and green, and b represents the position between yellow and blue. Furthermore, YC b C r The video signal is YC b C r Y represents the luminance, and C represents the color space. b and C r represents the color difference.

[0034] FIG. 1 is a block diagram showing a schematic functional configuration of a video viewing device according to this embodiment. As shown in the figure, video viewing device 100 includes a picture image generating unit 1, a vector image generating unit 2, an image selecting unit 3, a display unit 4, and a control unit 5. At least some of the functions of the video viewing device according to this embodiment can be realized, for example, by a computer and a program. Each unit also has a storage means as needed. The storage means is, for example, a program variable or memory allocated by the execution of the program. Non-volatile storage means such as a magnetic hard disk drive or a solid-state drive (SSD) may also be used as needed. At least some of the functions of each unit may also be realized as a dedicated electronic circuit rather than a program.

[0035] Video viewing device 100 can display a picture image generated by picture image generator 1. This picture image is an image that allows areas of an image that are to be corrected for a specific color to be distinguished from areas that are not to be corrected at a glance. Video viewing device 100 can also display a vector image generated by vector image generator 2. This vector image is an image that visually indicates the position of vector coordinates corresponding to reference colors on a plane within a predetermined gamut according to the color gamut of the input image. The reference colors may be, for example, red (R), green (G), blue (B), cyan (C), magenta (M), and yellow (Y) for 75% HLG and 100% HLG, respectively. Video viewing device 100 can select and display either a picture image or a vector image.

[0036] The picture image generating unit 1 converts the video signal and outputs the converted video signal. Note that this conversion includes converting the image of the area to which the specific color correction process is not applied into a grayscale image. The picture image generating unit 1 also calculates the average level (average brightness; the same applies below) and maximum level (maximum brightness; the same applies below) for the area to which the specific color correction process is applied, and passes this numerical information to the display unit 4.

[0037] The specific processing contents of the picture image generating unit 1 are as follows. That is, the picture image generating unit 1 determines the color gamut of the input image. The picture image generating unit 1 performs a matrix operation according to the determined color gamut, thereby generating the input video signal (YC b C r The picture image generation unit 1 converts the RGB video signal obtained from the CIELAB video signal into an RGB video signal. The picture image generation unit 1 then distinguishes between areas (e.g., pixel by pixel) to which the specific color correction process is applied and areas (e.g., pixel by pixel) to which the specific color correction process is not applied for each frame image of the CIELAB video signal obtained as a result of the conversion. The picture image generation unit 1 removes color (sets saturation to zero) from areas within the frame image to which the specific color correction process is not applied, to create a grayscale image. The picture image generation unit 1 maintains the color of areas to which the specific color correction process is applied. The picture image generation unit 1 also extracts only areas to which the specific color correction process is applied (i.e., areas of a specific color) for each frame image of the CIELAB video signal obtained as a result of the conversion, calculates the average and maximum levels of those areas, and passes these numerical values ​​to the display unit 4. The picture image generation unit 1 then reconverts the video signal after the specific color correction process into an RGB video signal (returning the color space). The picture image generating unit 1 passes the corrected RGB video signal thus obtained to the image selecting unit 3.

[0038] The vector image generator 2 generates and outputs a vector image corresponding to the input video signal.

[0039] The specific processing contents of the vector image generation unit 2 are as follows. That is, the vector image generation unit 2 determines the color gamut of the input video signal. Then, the vector image generation unit 2 converts the input video signal into vector data. When the input video signal is an RGB video signal, the vector image generation unit 2 performs a matrix operation corresponding to the color gamut determined above to convert the input video signal into YC b C rThe input video signal is converted into a video signal (i.e., a signal expressed as brightness and color values). As a result, the vector image generation unit 2 determines vector coordinate values ​​corresponding to the colors contained in the input video signal according to the color gamut determined above. If the color gamut is a standard color gamut, the vector image generation unit 2 selects either the standard color gamut or the standard color gamut converted from the wide color gamut video signal. The vector image generation unit 2 also generates a vector background image. This vector background image may be a pre-stored image read from a storage means. The vector image generation unit 2 then renders the vector data of the input video signal by superimposing points corresponding to the vector coordinate values ​​determined above on the vector background image.

[0040] The image selection unit 3 selects a screen to be passed to the display unit 4 in response to a control signal from the control unit 5. Specifically, the image selection unit 3 selects either an image generated by the picture image generation unit 1 or an image generated by the vector image generation unit 2, and passes the selected screen so that it can be displayed on the display unit 4. In other words, the image selection unit 3 selects and outputs either an image output by a specific color correction determination processing unit 132 (described later) or an image output by an image synthesis processing unit 25 (described later).

[0041] The display unit 4 displays the screen (image, video) passed from the image selection unit 3. That is, the display unit 4 displays the image selected by the image selection unit 3. That is, the display unit 4 may display the image output by the picture image generation unit 1 (specific color correction determination processing unit 132). The display unit 4 may also generate an image output by the vector image generation unit 2 (image synthesis processing unit 25). The display unit 4 may further display at least one of the maximum level and average level values ​​calculated by the average / maximum level calculation unit 135 (specific color correction application area extraction unit 13 in the picture image generation unit 1). The display unit 4 may also display both the maximum level and average level values. The display unit 4 is equipped with, for example, a liquid crystal display device, and displays the screen.

[0042] The control unit 5 controls each unit of the video viewing device 100. Specifically, the control unit 5 performs the following controls.

[0043] The control unit 5 outputs a signal for controlling the image switching unit 14 in the picture image generating unit 1. That is, based on the signal from the control unit 5, the image switching unit 14 switches between outputting the input video as is, or outputting the video output by the specific color correction application area extraction unit 13 (video in which only the specific color correction application area is in color and the other areas are grayscaled).

[0044] Furthermore, the control unit 5 can pass the vector coordinate data set by the user to the vector coordinate data selection unit 23, which will be described later. In other words, the control unit 5 can set vector coordinates for the vector coordinate data selection unit 23.

[0045] The control unit 5 also controls the image selection unit 3. That is, based on a control signal sent from the control unit 5, the image selection unit 3 selects and outputs either the image sent from the picture image generation unit 1 or the image sent from the vector image generation unit 2.

[0046] Note that the control unit 5 may also perform controls within the video viewing device 100 other than those described above.

[0047] 2 is a block diagram showing the internal functional configuration of the above-mentioned picture image generating unit 1. As shown in the figure, the picture image generating unit 1 includes a color gamut determination processing unit 11, a matrix conversion unit 12, a specific color correction application area extraction unit 13, and an image switching unit 14.

[0048] The color gamut determination processor 11 determines the color space of the input video signal. Specifically, the color gamut determination processor 11 determines the color space based on information about ancillary areas superimposed on the video signal. The video signal may be, for example, a wide color gamut video signal or a standard color gamut video signal, and color gamut determination processing unit 11 determines the color gamut of these signals. Color gamut determination processing unit 11 passes color space information of the determination result to matrix conversion unit 12. In addition, color gamut determination processing unit 11 passes the video signal to matrix conversion unit 12 and image switching unit 14, respectively.

[0049] The matrix conversion unit 12 converts the YC b C r The video signal is converted into an RGB video signal. That is, the matrix conversion unit 12 determines matrix coefficients for conversion according to the color gamut determined by the color gamut determination processing unit 11. The matrix conversion unit 12 may store matrix coefficients corresponding to the color space in advance. Known values ​​may be used as the matrix coefficients for this conversion. Matrix coefficients when the input signal is a wide color gamut video signal are described, for example, in the document [Recommendation ITU-R BT.2020-2, "Parameter values ​​for ultra-high definition television systems for production and international program exchange"]. Matrix coefficients when the input signal is a standard color gamut video signal are described, for example, in the document [Recommendation ITU-R BT.709-6, "Parameter values ​​for the HDTV standards for production and international program exchange"].

[0050] The specific color correction application area extraction unit 13 performs a process of converting areas in the image to which the specific color correction process is applied into color, and removing the color of other areas to which the specific color correction process is not applied, to grayscale. The specific color correction application area extraction unit 13 also extracts only the specific color area and calculates numerical data for the average level (brightness) and maximum level (brightness) in the specific color area. The specific color correction application area extraction unit 13 passes the image after the above process (an image in which the areas to which the specific color correction process is not applied have been grayscaled) to the image switching unit 14. The specific color correction application area extraction unit 13 also passes the numerical data for the average level (brightness) and maximum level (brightness) in the specific color area to the display unit 4. A more detailed functional configuration of the specific color correction application area extraction unit 13 will be described later with reference to FIG. 3.

[0051] The processing by the matrix conversion unit 12 and the specific color correction application area extraction unit 13 depends on the color space determination result. That is, the matrix conversion unit 12 receives information on the color space determination result from the color gamut determination processing unit 11. When the input video signal is a wide color gamut video signal, the matrix conversion unit 12 and the specific color correction application area extraction unit 13 each perform the processing described above. When the input video signal is not a wide color gamut video signal, the matrix conversion unit 12 controls the matrix conversion unit 12 and the specific color correction application area extraction unit 13 so that they do not operate.

[0052] The image switching unit 14 switches between the input video signal passed from the color gamut determination processing unit 11 and the video signal passed from the specific color correction application area extraction unit 13, and passes one of the video signals to the display unit 4. The image switching unit 14 switches the video signal based on, for example, a control signal from the control unit 5. The video signal passed from the color gamut determination processing unit 11 is the video signal input to the video viewing device 100. The video signal passed from the specific color correction application area extraction unit 13 is an image obtained by performing matrix conversion by the matrix conversion unit 12 and grayscaling the area to which the specific color correction application area extraction unit 13 does not apply the specific color correction process. The control unit 5 transmits a control signal to the image switching unit 14 to select one of the video signals based on, for example, an instruction (selection) from a user. Note that, as described above, if the input video signal is not a wide color gamut video signal, the matrix conversion unit 12 and the specific color correction application area extraction unit 13 do not operate, and therefore the image switching unit 14 may always output the input video signal passed from the color gamut determination processing unit 11.

[0053] 3 is a block diagram showing the internal functional configuration of the above-mentioned specific color correction application area extraction unit 13. As shown in the figure, the specific color correction application area extraction unit 13 includes a color space conversion processing unit 131, a specific color correction determination processing unit 132, a color space reconversion processing unit 133, a specific color extraction unit 134, and an average / maximum level calculation unit 135.

[0054] The color space conversion processing unit 131 converts the input R'G'B' video signal into a video signal in the CIELAB space that supports HDR (high dynamic range). The color space conversion processing by the color space conversion processing unit 131 will be explained later as part of "Example of assumed specific color correction processing." The color space conversion processing unit 131 passes the converted signal to the specific color correction determination processing unit 132 and the specific color extraction unit 134.

[0055] The specific color correction determination processing unit 132 determines whether or not each area (for example, each pixel) included in the image passed from the color space conversion processing unit 131 is an area that is to be subjected to correction processing for a specific color. That is, the specific color correction determination processing unit 132 outputs a binary image that indicates whether or not an area is an area that is to be subjected to correction processing. An example of this binary image will be described later with reference to another drawing.

[0056] Specifically, the specific color correction determination processing unit 132 determines whether the color of a pixel included in an input image satisfies a predetermined condition in the image by using a correction factor f cor and calculate the correction factor f cor The specific color correction determination processing unit 132 determines whether the pixel is a correction target or not based on the value of the correction factor f cor and a correction factor f that changes continuously in response to changes in the hue angle of the pixel color. cor , the correction factor f cor (In particular, if the color to be corrected is skin color, the correction factor f cor,skin The method for determining this will be explained later.

[0057] The correction process for a specific color will be described later as "an example of a prerequisite correction process for a specific color." The specific color correction determination processing unit 132 determines the value of the correction factor f cor The specific color is, for example, skin color. The correction factor value f cor is the value f cor,skin is the same value as

[0058] Specifically, the specific color correction determination processing unit 132 determines the value of the correction factor f when correcting the saturation of the skin color for the video signal passed from the color space conversion processing unit 131. cor,skin Calculate the correction factor f cor,skinis 1 is equivalent to the region (for example, pixel) not being a specific color correction application region.

[0059] Therefore, the specific color correction determination processing unit 132 first calculates the correction factor f in the same manner as when performing specific color correction processing. cor,skin Then, calculate the correction factor f using the following formula (U1): cor,skin Update the value of

[0060]

number

[0061] In other words, the correction factor before updating f cor,skin If the value of is 1, the updated correction factor f cor,skin The value of is set to 0. Also, the correction factor f before updating is cor,skin If the value of is other than 1, the updated correction factor f cor,skin The value of is set to 1.

[0062] The updated correction factor f based on the above formula (U1) cor,skin is the saturation C of the pixel in the input image. ab By multiplying by , the color of the pixels in the area to which the specific color correction process is applied is maintained (as color), and the saturation of the pixels in the area to which the specific color correction process is not applied becomes zero (grayscaled). The specific color correction determination processing unit 132 performs this process for all pixels in the image. Note that the specific color correction determination processing unit 132 also uses the lightness (L * ) and hue angle (h ab ) maintains the value in the input image.

[0063] As a modified example, the specific color correction determination processing unit 132 calculates the correction factor f according to the following equation (U2): cor,skin may be updated.

[0064]

number

[0065] In this formula (U2), th skin is a threshold that can be set in advance, and 0≦th skin ≦1. In other words, in this case, the correction factor before updating f cor,skin The value of th skin If it is equal to or greater than this, the updated correction factor f cor,skin The value of is set to 0. Also, the correction factor f before updating is cor,skin The value of th skin If it is less than the updated correction factor f cor,skin In this modified example, the specific color correction determination processing unit 132 sets the value of the correction factor f cor,skin The value of th skin The image is converted to grayscale for the above-mentioned region. That is, the specific color correction determination processing unit 132 changes the saturation of a pixel to zero even if the degree of reduction in the saturation of the pixel due to correction is lower than a predetermined threshold.

[0066] That is, the specific color correction determination processing unit 132 changes the saturation of the pixel color not to be corrected, when the color is expressed by lightness, hue angle, and saturation, to zero. Also, as shown in the above formula U1, the specific color correction determination processing unit 132 changes the correction factor f cor (f cor,skin ) indicates that the saturation of the pixel is not to be corrected, the saturation of the pixel is changed to zero, and the correction factor f cor If the value of f indicates that the saturation of the pixel is to be corrected, the saturation of the pixel may not be changed. Furthermore, as shown in the above formula U2, the specific color correction judgment processing unit 132 may also change the saturation of the pixel to zero if the degree to which the saturation of the pixel is reduced by the correction is lower than a predetermined threshold. In this case, the correction factor f cor has the effect of reducing the saturation of pixels.

[0067] That is, the specific color correction determination processing unit 132 calculates the correction factor f cor,skinIf the value of satisfies a predetermined condition, the area is converted to grayscale. In other words, if an area is not subject to specific color correction or if the degree of specific color correction is relatively small, the area is displayed in grayscale. Furthermore, specific color correction determination processing unit 132 displays other areas in color. This allows the user of video viewing device 100 to see at a glance which areas in the input video will be subjected to specific color correction.

[0068] The specific color extraction unit 134 extracts a specific color area from the image passed from the color space conversion processing unit 131 .

[0069] Specifically, the specific color extraction unit 134 extracts the lightness L output by the color space conversion processing unit 131 as a conversion result. * and color coordinate a * , b * and the hue angle h ab The specific color extraction unit 134 calculates the lightness L * and hue angle h ab Therefore, a process is performed to extract specific color areas that exceed the upper limit of the specific color level (skin level) assumed in the tone mapping process in dynamic range conversion. The upper limit of the specific color level assumed here may be a specified value, or may be a value that can be set arbitrarily by the user. When a specific color (skin color) of an HDR / wide color gamut video signal that exceeds the upper limit assumed in the tone mapping process is converted to the CIELAB color space corresponding to HDR, it falls within the following range. That is, when the lightness is L * min,skin That's all for now. * max,skin The range is as follows, and the hue angle is h ab,min That's all. ab,max The following range and saturation is C ab,min That's it for C. ab,max The specific color falls within the following range (see also FIG. 4): The specific color extraction unit 134 sets the brightness and saturation to 0 for areas outside this range, thereby extracting only the specific color area.

[0070] Here, the lightness L * min,skinis the brightness that corresponds to the upper limit of the skin level assumed in the tone mapping process. * min,skin is the HDR display luminance parameter HDR, which is the inflection point between the linear and logarithmic functions of the tone mapping process. ip The upper limit of the video signal is the upper limit of the brightness of the skin color area, L * max,skin is 95, and the video signal level at that time is 70.5% HLG (see also Figure 4). Here, the upper limit of operational brightness L * max,skin can be set to 100. * =100 corresponds to 75% HLG.

[0071] According to the reference [ICtCp Dolby White Paper, Version 7.1, https: / / professional.dolby.com / siteassets / pdfs / ictcp_dolbywhitepaper_v071.pdf], the hue angle of skin tones in the HDR ICtCp space falls within a range of approximately 102° (degrees) to 132° (degrees). The hue angle in the ICtCp space can be converted to the hue angle in the HDR-compatible CIELAB color space as follows: The difference in hue angle between the ICtCp space and the HDR-compatible CIELAB color space is as follows: For example, for a monochrome red video signal with 100% red and 0% green and blue components, the hue angle in the ICtCp space is approximately 110° (degrees), while the corresponding hue angle in the HDR-compatible CIELAB color space is approximately 43° (degrees). In other words, the difference between the two is 67° (degrees). Considering this difference in phase angle, the lower and upper limits of the hue angle range for skin tones in the CIELAB color space corresponding to HDR are h ab、min = 35° (degrees), and h ab、max =65° (degrees).

[0072] The range of saturation of skin color may be set as follows: The lower and upper limits of the saturation range are, for example, as shown in FIG. ab、min= 25, and the upper limit of saturation C ab、max =45 can be used.

[0073] The specific color extraction unit 134 can extract only the specific color (here, skin color) with high accuracy by using the ranges of lightness, hue angle, and saturation described above.

[0074] The color space reconversion processing unit 133 performs a process of reconverting (returning) the CIELAB space video signal to an R'G'B' video signal. The process of the color space reconversion processing unit 133 will also be described later in "Example of assumed specific color correction process."

[0075] The average / maximum level calculation unit 135 calculates the average level value and maximum level value of the specific color (skin color) based on the image output by the color space reconversion processing unit 133, and outputs them. That is, the average / maximum level calculation unit 135 calculates the numerical values ​​of the maximum level and the average level for pixels in the image that have been determined to be pixels to be corrected by the specific color correction determination processing unit 132. As a modified example, the average / maximum level calculation unit 135 may calculate at least one of the numerical values ​​of the maximum level and the average level for pixels that have been determined to be pixels to be corrected.

[0076] In other words, the average / maximum level calculation unit 135 calculates the average skin level and the maximum skin level from an image in which all colors other than the specific color (skin color) are expressed as 0% HLG. The average / maximum level calculation unit 135 outputs the level value corresponding to the maximum level among all pixels corresponding to skin color as the maximum skin level. The average / maximum level calculation unit 135 also calculates the sum of the levels of all pixels corresponding to skin color and divides this sum by the number of corresponding pixels to calculate and output the average skin level. To calculate the average value, the average / maximum level calculation unit 135 needs to know the total number of skin-colored pixels. To do this, the average / maximum level calculation unit 135 generates and manages information corresponding to a binary image indicating whether a pixel is skin-colored or not, for example. The average / maximum level calculation unit 135 passes the calculated numerical data (average level and maximum level values) to the display unit 4. This allows the display unit 4 to superimpose the numerical data passed from the average / maximum level calculation unit 135 onto the input video or onto a screen such as a vectorscope.

[0077] With the above configuration, the specific color correction application area extraction unit 13 passes an image representing the specific color correction application area to the image switching unit 14. In addition, the specific color correction application area extraction unit 13 passes the average level value and maximum level value of the specific color (for example, skin color) to the display unit 4.

[0078] 4A and 4B are schematic diagrams showing the range that should be extracted as skin color in the CIELAB color space by the video viewing device 100 of this embodiment. In FIG. 4A, the horizontal axis represents saturation (C * ab ) and the vertical axis is lightness (L * ) In Figure 4(B), the horizontal axis is a * and the vertical axis is b * is.

[0079] In conventional techniques (for example, Non-Patent Document 1), skin color is extracted only within the range of lightness and hue angle, which causes the problem that highly saturated colors that are not perceived as skin color are also extracted as skin color. In contrast, in this embodiment, as described above, color is extracted by limiting the range of saturation in addition to lightness and hue angle, thereby solving the problems of the conventional technique.

[0080] 5 is a block diagram showing the internal functional configuration of the above-mentioned vector image generation unit 2. As shown in the figure, the vector image generation unit 2 includes a color gamut determination processing unit 21, a vector data conversion unit 22, a vector coordinate data selection unit 23, a background image storage unit 24, and an image synthesis processing unit 25.

[0081] The color gamut determination processing unit 21 determines the color gamut of the input video signal (image). The method by which the color gamut determination processing unit 21 determines the color gamut is the same as the method already explained as the function of the color gamut determination processing unit 11. The color gamut determination processing unit 21 passes information on the determination result (color gamut) to the vector data conversion unit 22 and the vector coordinate data selection unit 23. The color gamut determination processing unit 21 also passes the input video signal to the vector data conversion unit 22.

[0082] The vector data conversion unit 22 converts the colors represented by the input video into vector data according to the determination result (color gamut) passed from the color gamut determination processing unit 21. The conversion process itself by the vector data conversion unit 22 is similar to the process in video viewing devices using existing technology. That is, the vector data conversion unit 22 converts the colors contained in the image into vector data representing coordinates in a predetermined color space based on the color gamut determined by the color gamut determination processing unit 21. In other words, the vector data conversion unit 22 generates a vectorscope image corresponding to the input video. A vectorscope is a circular graph that shows the directionality (hue wheel) and intensity of colors. In this circular graph, the closer to the center of the circle, the lower the saturation (chroma), and the further out from the circle, the higher the saturation.

[0083] The vector coordinate data selection unit 23, also referred to as the "reference color coordinate selection unit," selects vector coordinate data for a reference color corresponding to the color gamut determined by the color gamut determination processing unit 21. In other words, the vector coordinate data selection unit 23 selects coordinate values ​​(vector coordinates) of a predetermined reference color in a predetermined color space based on the color gamut determined by the color gamut determination processing unit 21. The reference colors may be, for example, 12 colors in total: red (R), green (G), blue (B), cyan (C), magenta (M), and yellow (Y) for 75% Hybrid Log Gamma (HLG) and 100% Hybrid Log Gamma (HLG). The reference colors may also be a collection of other colors. Examples of vector coordinate data corresponding to color gamuts will be described later with reference to FIGS. 6 and 7. In this embodiment, in the case of a standard color gamut, the user can select vector coordinate data for an SDR / standard color gamut video signal converted from an HDR / wide color gamut video signal. If the conversion algorithm is limited to one, the coordinate data selected by vector coordinate data selection unit 23 may be fixed values. Furthermore, the coordinate position set by the user may be stored in video viewing device 100. Furthermore, if conversion using a 3D-LUT (three-dimensional lookup table) is used, the same 3D-LUT may be made available for uploading into video viewing device 100, and the 3D-LUT may be used to convert internal signals into numerical values ​​and calculate coordinate positions.

[0084] The background image storage unit 24 stores a background image for displaying a vectorscope diagram. This background image can be read out by the image synthesis processing unit 25.

[0085] The image synthesis processing unit 25 synthesizes the coordinate positions represented by the vector data output by the vector data conversion unit 22, the positions of each color (RGBCMY for each of 75% HLG and 100% HLG) represented by the vector coordinates selected by the vector coordinate data selection unit 23, and the background image read out from the background image storage unit 24, and outputs the image resulting from the synthesis. In other words, the image synthesis processing unit 25 synthesizes an image formed by superimposing at least the image represented by the vector data converted by the vector data conversion unit 22 and a mark indicating the position represented by the coordinate values ​​selected by the vector coordinate data selection unit 23 (reference color coordinate selection unit).

[0086] That is, using the functions of the above-described units, vector image generation unit 2 converts the video signal input to video viewing device 100 into a vector image and generates an image to be displayed on display unit 4. In this embodiment, as described above, vector coordinate data selection unit 23 selects a vector coordinate position according to the color gamut of the input video. As a result, when an HDR / wide color gamut video signal is converted into an SDR / standard color gamut video signal, it is possible to display the vector coordinate position to determine whether the conversion algorithm is as expected.

[0087] 6 and 7 are schematic diagrams showing examples of vectorscope diagrams. Each of these vectorscope diagrams is based on vector coordinate data selected by the vector coordinate data selection unit 23 according to the color gamut of the input video. Specifically, FIG. 6 corresponds to the case of a wide color gamut (BT.2020) and shows a vectorscope diagram for viewing a wide color gamut video signal. FIG. 7 corresponds to the case of a standard color gamut (BT.709) and shows a vectorscope diagram for viewing a standard color gamut video signal.

[0088] In each of Figures 6 and 7, (RY) and (BY) are coordinate axes of the color difference signals. I (skin tones) and Q (cool tones) are also coordinate axes corresponding to the signals. The coordinate system of I and Q is obtained by rotating the coordinate system of (RY) and (BY) within its plane. In other words, the value of I is obtained by multiplying the value of the (RY) signal and the value of the (BY) signal by a predetermined coefficient and then adding the result. The value of Q is obtained by multiplying the value of the (RY) signal and the value of the (BY) signal by another coefficient and then adding the result.

[0089] The vectorscope diagrams shown in Figures 6 and 7 each show a diagram connecting the coordinates corresponding to each color in each gamut: 75%R-75%M-75%G-75%C-75%Y-75%B. They also show a diagram connecting the coordinates corresponding to each color in each gamut: 100%R-100%M-100%G-100%C-100%Y-100%B.

[0090] [Example of specific color correction processing] Next, a specific color correction process that is a prerequisite for this embodiment will be described. In the following, a skin color correction process will be described as an example. When the specific color is skin color, the above-mentioned f cor,skin The value of f in the explanation below cor is the same as

[0091] In conventional technology, broadcast programs using HDR video (HDR stands for "High Dynamic Range") are produced taking into consideration the HDR reference white in order to reduce variations in brightness between programs. When using the HLG format (HLG stands for "Hybrid Log Gamma"), the HDR reference white is 75% of the HLG video signal level (hereinafter sometimes referred to as "75% HLG").

[0092] The level of human facial skin is important when composing video. Prior art (e.g., JP 2020-025241 A) has reported that the level of human facial skin falls within the range of 45% HLG to 55% HLG when considering HDR reference white. However, when the intentions of the video creator or the person and lighting conditions change, facial skin may be expressed at a level higher than 55% HLG. The HLG method adjusts brightness so that skin becomes white at 75% HLG, so skin expressed between 55% HLG and 75% HLG maintains its saturation as a skin color.

[0093] On the other hand, another conventional technology (Report ITU-R BT.2408-3 "Guidance for operational practices in HDR television production", July 2019, ITU-R (Radiocommunication Sector of ITU)) reports that in programs produced using conventional SDR video (SDR stands for "Standard Dynamic Range"), the facial skin tone is higher for women than for men.

[0094] In SDR video programs, the higher the level of a woman's facial skin, the more emphasis is placed on gradation expression and the lower the saturation is displayed. When attempting to express this using the saturation correction process described in the prior art (JP Patent Publication No. 2020-025241 mentioned above), many skin tones have a brightness lower than that equivalent to 75% HLG, and the saturation correction process cannot be applied, resulting in the problem of not being able to express skin tones with low saturation.

[0095] Furthermore, even if the brightness corresponding to 75% HLG, which is the inflection point of the saturation correction process, is reduced to the brightness corresponding to 55% HLG, the saturation is reduced equally at all hue angles, which poses the problem of reducing the saturation of colors other than facial skin.

[0096] One possible solution would be to lower the inflection point of the saturation correction process to a lightness equivalent to 55% HLG only for the skin-color hue angle range. However, when switching from a skin-color hue angle to a non-skin-color hue angle, or vice versa, if the correction process formula results in a mathematically steep conversion, discontinuity in the gradation expression after conversion may occur. Furthermore, when limiting the skin-color range using lightness and hue angle, there is a risk that highly saturated colors that are not perceived as skin colors may also be subject to the correction process, even though they have the same hue angle.

[0097] Therefore, the specific color correction process described here can reduce the saturation of only specific color areas when, according to production intent, it is desired to increase the facial skin level in HDR program production and reduce the saturation to represent facial skin in the same way as in conventional SDR program production. Furthermore, it can prevent discontinuities from appearing in the gradation representation after saturation correction, and it can prevent colors other than the intended color from being corrected by the correction process.

[0098] According to the image correction process described below, it is possible to correct the saturation only in areas that meet specific conditions regarding hue and brightness.

[0099] The image correction process here corrects the input HDR (high dynamic range) video signal. Specifically, when the HDR video signal expresses a high level of skin tone in a human face, the image correction process corrects the skin color in the image by reducing saturation and preserving the gradation. In this embodiment, "skin color" refers to a color also known as pale orange, a color commonly seen in Japan and other Far Eastern regions. The video targeted by the image correction process is a time series of frame images. The video may or may not include audio. When the image correction process corrects the video signal, correction is performed on each individual frame image.

[0100] The image correction process here performs the following overall processing. That is, the image correction process inputs an HDR video signal. The image correction process then converts the input HDR video signal sequentially into a linear signal and a signal in the CIELAB color space (CIE 1976 (L*, a*, b*) color space) that corresponds to HDR, and then corrects the saturation of only the skin color region. The image correction process then converts the signal after the saturation correction into an HDR video signal and outputs that HDR video signal. The image correction process will be described in detail below.

[0101] The image correction process includes a color space conversion process, a saturation correction process, and a color space reconversion process. Each of these processes can be realized using electronic circuits. Alternatively, at least a part of these processes can be realized using a computer and a program.

[0102] The image correction process inputs an HDR video signal (a signal standardized under the BT.2020 standard), corrects the signal, and outputs the corrected HDR video signal. Specifically, the image correction process corrects the saturation of only the areas of the input HDR video signal with a high facial skin level, and then returns the corrected signal to an HDR video signal for output (a signal standardized under the BT.2020 standard, just like the input signal). Details of each step in the image correction process are as follows.

[0103] The color space conversion process converts the input HDR input video signal into a signal in the CIELAB color space that is compatible with HDR. In other words, the color space conversion process converts the image contained in the input HDR video into a signal in the CIELAB color space that is compatible with HDR, and passes it to the saturation correction process. The color space conversion process converts the image contained in the CIELAB color space HDR video into a CIELAB color space signal in which 75% HLG scene luminance corresponds to diffuse white (lightness 100). The CIELAB color space in which 75% HLG scene luminance corresponds to diffuse white (lightness 100) is called the "HDR-compatible CIELAB color space."

[0104] Specifically, the color space conversion process involves converting the HDR input video signal E' hin ={R′ HDRin ,G′ HDRin ,B′ HDRin}, the display luminance signal Fd HDRin ={R HDRin ,G HDRin ,B HDRin Furthermore, the color space conversion process is carried out to obtain the display luminance signal Fd HDRin By matrix calculation, the tristimulus value X HDRin Y HDRin Z HDRin Furthermore, the color space conversion process converts these tristimulus values ​​into signals in the CIELAB color space that correspond to HDR. This process in the color space conversion process converts the lightness L * and color coordinate a * , b * is calculated.

[0105] In addition, a * is in the red direction (a * positive direction) and green direction (a * The value indicates the degree of the negative direction of * is the yellow direction (b * positive direction) and blue direction (b * The value indicates the degree of the color (in the negative direction of the color coordinate a). * , b * Once the value of is determined, the hue angle and saturation are determined.

[0106] In the color space conversion process, to obtain an RGB linear signal, an inverse OETF function conforming to the HDR method may be used to convert the signal into a scene luminance signal, which may then be converted into a CIELAB color space in which 75% HLG scene luminance corresponds to diffuse white (lightness 100).

[0107] The color space conversion process itself is a conventional technique and is equivalent to the process described in, for example, Japanese Patent Application Laid-Open No. 2020-025241.

[0108] In the color space conversion process, the CIELAB space signal corresponding to HDR obtained in the above process is passed to the saturation correction process.

[0109] The saturation correction process involves calculating a correction factor f to correct the saturation of pixels in the image that meet certain conditions. cor is calculated, and the saturation of the pixel is adjusted by the correction factor f cor The saturation correction process is carried out by adjusting the correction factor f, which continuously changes in response to a change in the brightness, based on at least the brightness and hue angle of the pixel. cor and the correction factor f is continuously changed in response to the change in the hue angle. cor The saturation correction process is carried out by applying the correction factor f determined for the saturation of the pixel. cor The saturation of the pixel is corrected by multiplying the saturation of the pixel by the CIELAB color space signal corresponding to the HDR signal passed from the color space conversion process.

[0110] The saturation correction process corrects the saturation of skin color areas. Specifically, the saturation correction process corrects the saturation of only skin color areas exceeding 55% HLG in the HDR-compatible CIELAB space by equal lightness and equal hue conversion. When an HDR signal is converted to the HDR-compatible CIELAB color space, skin color areas exceeding 55% HLG have a lightness of L. * min From L * max and hue angle is within the range of h ab,min From h ab,max Here, the brightness L * min is the brightness equivalent to 55% HLG, and when calculated from the display brightness, L * min = 63, calculated from the scene luminance, L * min = 76. Lightness L * maxis the brightness equivalent to the upper limit of the video signal, 109% HLG, and is calculated from the display brightness. * max =224, calculated from scene luminance, L * max = 217. The lower limit of the hue angle range for skin tones in the HDR-compatible CIELAB color space, h ab,min and upper limit h ab,max is, h ab,min =35°, h ab,max = 65°. Here, L * min , L * max , h ab,min , and h ab,max Although the above description assumes that these are fixed values, each of these may be parameters that can be freely set by the user. Also, although the upper limit of the video signal is set to 109% HLG, it may be set to 100% HLG.

[0111] In the saturation correction process, as shown in the following formula (1), chroma C * ab and hue angle h ab Calculate the hue angle h ab h ab ≧h ab,min Kats H ab ≦h ab,max In the range of luminosity L * L * >L * min The correction factor f for reducing the saturation of skin tones is cor However, as a result of the calculation using formula (1), f cor If <0, we force f cor =0.

[0112] Furthermore, as shown in equation (1), if the above conditions are not met, the correction factor f cor Set the value to 1 (no saturation correction).

[0113]

number

[0114] In the formula (1), σ is an arbitrarily adjustable user parameter, and σ ≥ 0.

[0115] When performing correction as in the above formula (1), the hue angle h ab is h ab,min or h ab,max changes such that the saturation rapidly (discontinuously) decreases at the boundary part. Therefore, discontinuity in the gradation expression may occur in the result after conversion. Thus, in this embodiment, the lightness L * f at the inflection point is functionalized as shown in the following formula (2) so that the lightness at the inflection point changes continuously according to the hue angle.

[0116]

Equation

[0117] Here, L * ref is the lightness corresponding to 75% HLG. Also, L * ip is the lightness corresponding to 55% HLG. Also, each of h1, h2, h3, and h4 is the hue angle at the inflection point on the hue angle side of the lightness at the inflection point. h1, h2, h3, and h4 are user parameters that can be arbitrarily adjusted by the user as long as they satisfy the relationships of h1 ≤ h ab,min ≤ h2, h3 ≤ h ab,max ≤ h4, and h1 ≤ h2 < h3 ≤ h4, respectively. In particular, a constraint may be provided to limit the case to h1 < h2 < h3 < h4, excluding the case where h1 = h2 or h3 = h4. As an example, h1 = 34°, h2 = 38°, h3 = 62°, h4 = 66°, etc. may be used.

[0118] FIG. 8 is a graph showing the relationship between the hue angle h ab and the lightness function value L * f in the case of the above example (h1 = 34°, h2 = 38°, h3 = 62°, h4 = 66°). In this graph, the horizontal axis is the hue angle hab and its unit is degrees (°). Hue angle h ab The range of 0≦h ab <360. The vertical axis is the brightness L * f Lightness L * f is the hue angle h ab In this graph, the thick solid line indicates the brightness of the inflection point according to this embodiment (Equation (2)). The thin solid line indicates the brightness of the inflection point when Equation (1) is used. The dashed line indicates the brightness of the inflection point when L * ref (Lightness equivalent to 75% HLG). The dashed line indicates the * ip (Lightness equivalent to 55% HLG) is shown. * ref = 100, and L * ip =63.

[0119] When using equation (1) (thin solid line graph), the hue angle h ab,min and h ab,max The brightness of the inflection point L * f In contrast, when formula (2) is used (thick solid line graph), the hue angle h ab,min and h ab,max In each vicinity of * f is made to change continuously.

[0120] In other words, in the thick solid line graph, the hue angle h ab From 0° to h1, the brightness L * f is L * ref (Lightness equivalent to 75% HLG) and the hue angle h ab is between h1 and h2 (h1≦h ab,min ≦h2), the lightness of the inflection point L * f L * ref(75% HLG equivalent brightness) to L * ip (Lightness equivalent to 55% HLG) ab From h2 to h3, the brightness of the inflection point L * f is L * ip (Lightness equivalent to 55% HLG) ab is between h3 and h4 (h3≦h ab,max ≦h4), the lightness of the inflection point L * f L * ip (55% HLG equivalent brightness) to L * ref (Lightness equivalent to 75% HLG) ab In the area where h4 is larger than h4, the lightness L * f is L * ref (brightness equivalent to 75% HLG) is constant.

[0121] In addition, the brightness of the inflection point L * f As shown in this graph, ab The method of linearly changing the lightness L at the inflection point (for each range) is just an example, and it is not necessary to use such a method. However, as shown in this graph (as in formula (2)), * f The method for determining ρ can simplify the calculation.

[0122] In other words, the lightness L of the inflection point * f Equation (2) was shown above as an example of a function to calculate the brightness of the inflection point L * f The function for calculating is preferably as follows: That is, the lightness L of the inflection point * f The function to calculate the hue angle h abIt is desirable that the function be continuous over the entire domain. Also, in the region where h1 ≤ h ab ≤ h2, the brightness L of the inflection point * f is such that L * ref (or in its vicinity) decreases (it may be monotonically decreasing) towards L * ip (or in its vicinity). Note that in the region where h1 ≤ h ab ≤ h2, there are points where h ab = h ab,min . Also, in the region where h2 < h ab < h3, the brightness L of the inflection point * f is constant (or almost constant) at L * ip (or in its vicinity). Also, in the region where h3 ≤ h ab ≤ h4, the brightness L of the inflection point * f is such that L * ip (or in its vicinity) increases (it may be monotonically increasing) towards L * ref (or in its vicinity). Note that in the region where h3 ≤ h ab ≤ h4, there are points where h ab = h ab,max . And in other regions (i.e., h ab < h1 and h4 < h ab ), the brightness L of the inflection point * f is constant (or almost constant) at L * ref (or in its vicinity).

[0123] Next, the amount for correcting the saturation is determined using the above L * f as the inflection point. When performing correction using Equation (1), σ (where σ > 0) that can be arbitrarily adjusted by the user can also be used as the saturation correction parameter. However, in the case of the above Equation (2), since the inflection point of the brightness changes continuously, it is desirable that the saturation correction parameter also changes accordingly. Therefore, the saturation correction parameter also depends on the brightness L of the inflection point* f For example, as shown in the following equation (3), the saturation correction parameter σ f Determine.

[0124]

number

[0125] In formula (3), σ1 and σ2 are parameters that are set appropriately. The values ​​of σ1 and σ2 can be adjusted arbitrarily by the user within the range that satisfies σ1≦σ2. Note that the σ calculated using formula (3) f The value of σ f < 1, then σ f =1.

[0126] Figure 9 shows the hue angle h when σ1=1 and σ2=2 as an example. ab and the saturation correction parameter function value σ f In this graph, the horizontal axis represents the hue angle h ab The unit is degrees (°). The domain of definition is 0≦h ab <360. The vertical axis is the saturation correction parameter σ f is.

[0127] The thick solid line in the graph shown in FIG. 9 represents the saturation correction parameter σ f and is calculated using equation (3). The thin solid line graph is for comparison, and saturation when using equation (1) is an example of a positive parameter (σ f = 1.0).

[0128] The saturation correction parameter σ shown in the thick solid line in Figure 9 f is the lightness L shown in the graph in Figure 2. * f In other words, the hue angle h ab From 0° to h1, the saturation correction parameter σ fis constant at 1.0. ab is between h1 and h2, and the saturation correction parameter σ f The hue angle h changes linearly (increases) from 1.0 to 2.0. ab From h2 to h3, the saturation correction parameter σ f is constant at 2.0. ab is between h3 and h4, and the saturation correction parameter σ f The hue angle h changes linearly from 2.0 to 1.0. ab In the region where h is greater than h4, the saturation correction parameter σ f is a constant 1.0.

[0129] Figure 10 shows the brightness L * and the saturation correction parameter σ f Graph G0 in the figure shows the saturation correction parameter when using the conventional technology, and its value is the lightness L * The graph G1 shows the saturation correction parameters when σ1=1 and σ2=2 in this embodiment. In the graph G1, the lightness L * =L * ip (=63) when σ f = 2.0, and L * ip <L * <L * ref In σ f varies linearly from 2.0 to 1.0, and L * ≧L * ref (=100) is σ f = 1.0. Graph G2 shows the saturation correction parameters when σ1 = 1 and σ2 = 3 in this embodiment. In graph G2, the lightness L * =L * ip (=63) when σ f = 3.0, and L * ip <L * <L * ref In σf varies linearly from 3.0 to 1.0, and L * ≧L * ref (=100) is σ f = 1.0. Graph G3 shows the saturation correction parameters when σ1 = 1 and σ2 = 4 in this embodiment. Graph G2 shows the saturation correction parameters when the lightness L * =L * ip (=63) when σ f = 4.0, and L * ip <L * <L * ref In σ f varies linearly from 4.0 to 1.0, and L * ≧L * ref (=100) is σ f = 1.0. In addition, in the case of the combination of values ​​of σ1 and σ2 other than those illustrated in FIG. 4, the formula (3) (where σ f The lower limit of σ is 1.0) f is required.

[0130] The saturation correction process further performs correction processing to maintain the saturation of highly saturated colors that are not perceived as skin colors within the hue angle range of skin colors without changing it. To achieve this, the saturation correction process performs calculations using a decreasing function that makes the skin color correction process less effective as the saturation becomes higher.

[0131] FIG. 11 is a graph showing an example of the relationship between the input and output of a decreasing function that reduces the effectiveness of skin color correction processing as the saturation increases. In this graph, the horizontal axis represents the saturation C * ab The vertical axis corresponds to the coefficient C * func Corresponds to.

[0132] The effect of this decrease function is as follows: 0≦C where there is skin color above 55% HLG, as shown. *ab In the region ≦50, the decreasing function value C * func is greater than 0.95. That is, C * ab When is less than about 50, skin color correction is effective. And this reduction function is * ab In the region >50, the decreasing function value C * func has the characteristic that C * ab If C exceeds 50, the skin color correction process becomes less effective. * ab In the region of ≧150, the decreasing function value C * func is less than 0.02 and is very close to 0. In other words, C * ab If the value is 150 or more, the skin color correction process is almost ineffective.

[0133] As a decreasing function that satisfies the above requirements, for example, a sigmoid function can be used to realize a function such as the following formula (4).

[0134]

number

[0135] C in Equation (4) * cusp,min is the range of hue angles h1≦h in the CIELAB space corresponding to HDR to which skin color correction processing defined by equation (2) is applied. ab It is the smallest saturation among the saturations that form the color gamut boundary when h1=34° and h4=66°. For example, when h1=34° and h4=66°, C * cusp,min is approximately 253.3, and the hue angle is then 66°.

[0136] The saturation correction process is performed using the lightness function L * f and the saturation correction parameter function σ f and the decreasing function C *func and a correction factor f to reduce the saturation of skin tones. cor Calculate the correction factor f cor is calculated using, for example, the following equation (5).

[0137]

number

[0138] However, the result calculated by equation (5) is f cor If <0, we force f cor = 0. Then, the saturation correction process is performed by using the above correction factor f cor Chroma C * ab Multiply by to get the corrected chroma C * ab,cor That is, we obtain the following equation (6).

[0139] C * ab,cor =C * ab ×f cor (6)

[0140] As shown in equation (5), the correction factor f cor has the effect of reducing the saturation of the pixel. In other words, the process of saturation correction reduces the saturation C * ab The higher the correction factor f cor Reduces the degree of desaturation caused by

[0141] As a specific processing method, the saturation correction process is performed by * ab Depending on the value of the decreasing function C * func That is, the reduction function calculates the saturation C of the pixel before correction. * ab The decreasing function value C * func is the correction factor f corAs already explained with reference to the example of FIG. 11, the decreasing function value C * func is the pixel saturation before correction, C * ab As an example, this decreasing function is as follows: * ab If is less than 50, the decreasing function value C * func is 0.95 or more, and the pixel's uncorrected saturation C * ab When the value of the decreasing function C is 150 or more, * func is 0.02 or less. In other words, in this example, 50≦C * ab In the region of ≦150, the decreasing function value C * func As a result, the effect of saturation correction is limited in pixels with high saturation, and the effect of saturation correction is strong in pixels with low saturation. Note that the saturation correction process is performed by using a predetermined value (σ in Equation (5)) determined based on the lightness and hue angle of the pixel. f and (L * -L * f ) / (L * max -L * f ) and the product of the decreasing function value C * func By multiplying by the correction factor f cor Determine the degree of saturation loss due to

[0142] As mentioned above, the saturation correction process is performed using the correction factor f cor is calculated using equation (5). However, the result calculated using equation (5) is f cor If <0, we force f cor = 0. The meanings of the values ​​that appear in the formula are as follows: L * max is the maximum value of lightness. * is the brightness of the pixel (0≦L *≦L * max ) is L * f is the hue angle h of the pixel ab h1 and h4 are the predetermined inflection point values ​​for the lightness that are determined to change continuously according to the change in hue angle h ab These are parameters (where h1≦h4) that are determined appropriately depending on the region. f is a saturation correction parameter that is determined so as to change continuously in accordance with the change in the brightness of the pixel. * func is the decreasing function value.

[0143] The saturation correction process is performed on the corrected chroma C * ab,cor And brightness L * and the hue angle h ab Thus, the corrected LAB signal is calculated.

[0144] In the process of the saturation correction process, saturation correction is not performed on areas other than those that satisfy the above conditions for correction.

[0145] In the saturation correction process, the video signal after the saturation correction process is passed to the color space reconversion process.

[0146] The color space reconversion process converts the signal passed from the saturation correction process into an HDR output video signal and outputs it. In other words, the color space reconversion process reconverts the CIELAB color space signal corresponding to HDR after processing in the saturation correction process into an HDR video and outputs it.

[0147] Specifically, the color space reconversion process converts the saturation-corrected signal from the CIELAB color space corresponding to HDR to the tristimulus value X HDRout Y HDRout Z HDRout Furthermore, the color space reconversion process involves a matrix operation to convert the display luminance signal Fd HDRout ={R HDRout ,G HDRout ,BHDRout This process converts the HDR output video signal E' into the inverse EOTF function that complies with the HDR standard. hout ={R′ HDRout ,G′ HDRout ,B′ HDRout Note that if conversion to a scene luminance signal has been performed in the color space conversion process, the color space reconversion process converts the signal to a video signal using an OETF function that complies with the HDR method.

[0148] As described above, the image correction process proceeds as follows: First, in the first step, color space conversion converts the input HDR input video signal into a CIELAB color space signal that corresponds to HDR. Next, in the second step, saturation correction corrects the saturation of the CIELAB color space signal converted in the first step in a region of the image that satisfies certain conditions. Specifically, the saturation correction corrects the saturation of a skin color region that satisfies certain conditions. Next, in the third step, color space reconversion converts the CIELAB color space signal corrected in the second step into an HDR output video signal for output.

[0149] The above-described process allows image correction processing. In other words, even if the facial skin level of a person in an HDR program production is higher than the video signal level assumed in conventional technology (JP 2020-025241 A) due to production intent, gender, etc., it is possible to reproduce skin tones similar to those in conventional SDR program production. Furthermore, the image correction processing makes it possible to perform correction only on areas of a specific color (skin color).

[0150] The image processing described above can also be implemented in the following modified example.

[0151] [Variation 1 of specific color correction processing] In the above processing method, various parameters (L * min , L * max , h ab,min , hab,max , h1, h2, h3, h4, etc.) have been described, different values ​​may be used as parameter values. Also, these values ​​may be variable.

[0152] [Variation 2 of specific color correction processing] In the above processing method, the skin color area is the area to be subjected to saturation correction, but other areas may also be subjected to saturation correction. * ,b * The color terms for a region may alternatively be expressed in terms of hue angle, saturation, and brightness.

[0153] [Variation 3 of specific color correction processing] In the above processing method, the image correction process is configured to include all of the steps of color space conversion, saturation correction, and color space reconversion. As a modified example, the image correction process may include only the saturation correction. In this case, it is still possible to perform the saturation correction itself in the same manner as described above. Note that the color space conversion and color space reconversion processes may be performed in a device separate (external) from the device that performs the saturation correction.

[0154] According to the image correction process (including the modified examples) described above, it is possible to correct the saturation of only areas in an image that satisfy specific conditions. More specifically, as an image correction process, when the level of an area having human skin color becomes high, it is possible to correct only the area having human skin color while maintaining the saturation of areas of other colors. This makes it possible to express the skin color contained in the input HDR video signal in the same way as the skin color in a conventional SDR video signal.

[0155] According to the image correction process described above (including the modified examples), the numerical values ​​of the processing results are made continuous at the boundary parts of the correction process within the image, which has the effect of enabling smooth gradation expression in the corrected image.

[0156] According to the image correction process described above (including the modified examples), the effect is that for pixels that have the same hue angle as the area of ​​the color to be corrected (for example, skin color) but do not belong to the color to be corrected (saturation is out of range), the original color is (almost) maintained even after correction.

[0157] [1] One aspect of the device for performing the image correction process described above is as follows. That is, the image correction processing device includes: Correction factor f for correcting the saturation of pixels in an image whose color meets certain conditions cor is calculated, and the saturation of the pixel is adjusted by the correction factor f cor a saturation correction processing unit that performs correction based on Equipped with The saturation correction processing unit calculates the correction factor f, which continuously changes in response to a change in the lightness, based on at least the lightness and the hue angle of the pixel. cor and the correction factor f is continuously changed in response to the change in the hue angle. cor , and the correction factor f determined for the saturation of the pixel is cor Correct the saturation of the pixel by multiplying it by An image correction processing device.

[0158] [2] One aspect of an image correction processing device for performing image correction processing is the image correction processing device of [1] above, a color space conversion processing unit that converts an image included in an input high dynamic range (HDR) video into a signal in a CIELAB color space corresponding to HDR and passes the signal to the saturation correction processing unit; a color space reconversion processing unit that reconverts the signal in the CIELAB color space corresponding to HDR after being processed by the saturation correction processing unit into an HDR image and outputs the HDR image; Furthermore, the saturation correction processing unit corrects the saturation of the pixel based on a signal in a CIELAB color space corresponding to HDR passed from the color space conversion processing unit; An image correction processing device.

[0159] [3] One aspect of an image correction processing device for performing image correction processing is the image correction processing device according to [1] or [2] above, The correction factor f cor has the effect of reducing the saturation of the pixel, The saturation correction processing unit calculates the saturation C of the pixel before correction. * ab The higher the correction factor f cor Reduce the degree of desaturation caused by An image correction processing device.

[0160] [4] One aspect of an image correction processing device for performing image correction processing is the image correction processing device of [3] above, The saturation correction processing unit calculates the saturation C of the pixel before correction. * ab The correction factor f cor The decrease function value C represents the degree of decrease in saturation due to * func It calculates The decreasing function value C * func is the saturation C of the pixel before correction * ab It decreases monotonically with increasing The pixel's uncorrected saturation C * ab When is 50 or less, the decreasing function value C * func is 0.95 or more, The pixel's uncorrected saturation C * ab When is 150 or more, the decreasing function value C * func is less than or equal to 0.02, The saturation correction processing unit adjusts the decreasing function value C to a predetermined value determined based on the lightness and hue angle of the pixel. * func By multiplying the correction factor f cor Determine the degree of desaturation caused by An image correction processing device.

[0161] [5] One aspect of an image correction processing device for performing image correction processing is the image correction processing device of [4] above, The saturation correction processing unit calculates the correction factor f cor The formula below;

[0162]

number

[0163] (However, the result of the calculation using the above formula is f cor If <0, f cor = 0), (However, L * max is the maximum brightness, and L * is the brightness of the pixel (0≦L * ≦L * max ) and L * f is the hue angle h of the pixel ab h1 and h4 are the values ​​of the predetermined inflection points for the lightness that are determined to change continuously according to the change in the hue angle h ab are parameters (where h1≦h4) that are determined appropriately depending on the region of σ f is a saturation correction parameter determined to change continuously in accordance with the change in the brightness of the pixel, and C * func is the value of the decreasing function) This is an image correction processing device.

[0164] FIG. 12 is a block diagram showing an example of the internal configuration of the video viewing device 100 of this embodiment. At least some of the functions of the video viewing device 100 can be implemented using a computer. As shown in the figure, the computer includes a central processing unit 901, a RAM 902, an input / output port 903, input / output devices 904 and 905, and a bus 906. The computer itself can be implemented using existing technology. The central processing unit 901 executes instructions contained in a program read from the RAM 902 or the like. In accordance with each instruction, the central processing unit 901 writes data to the RAM 902, reads data from the RAM 902, and performs arithmetic and logical operations. The RAM 902 stores data and programs. Each element included in the RAM 902 has an address and can be accessed using the address. RAM is an abbreviation for "random access memory." The input / output port 903 is a port through which the central processing unit 901 exchanges data with external input / output devices. The input / output devices 904 and 905 are input / output devices. Input / output devices 904 and 905 exchange data with the central processing unit 901 via an input / output port 903. A bus 906 is a common communication path used within the computer. For example, the central processing unit 901 reads and writes data from and to RAM 902 via the bus 906. Also, for example, the central processing unit 901 accesses the input / output port via the bus 906.

[0165] At least some of the functions of the video viewing device 100 in the above-described embodiment can be realized by a computer and a program. In this case, the functions can be realized by recording a program for realizing the functions on a computer-readable recording medium and loading and executing the program recorded on the recording medium into a computer system. Note that the term "computer system" as used herein includes hardware such as an OS and peripheral devices. Furthermore, the term "computer-readable recording medium" refers to portable media such as flexible disks, optical magnetic disks, ROMs, CD-ROMs, DVD-ROMs, and USB memory, as well as storage devices such as hard disks built into computer systems. In other words, a "computer-readable recording medium" may be a non-transitory computer-readable recording medium. Furthermore, the term "computer-readable recording medium" may also include media that temporarily and dynamically store programs, such as communication lines used when transmitting programs over networks such as the Internet or telephone lines, or media that store programs for a certain period of time, such as volatile memory within a computer system that serves as a server or client in such cases. The program may also be a program that realizes some of the functions described above, or it may be a program that can realize the functions described above in combination with a program already stored in the computer system.

[0166] [Effects of this embodiment] As described above, the video viewing device 100 according to this embodiment provides the following advantages. First, the video viewing device 100 of this embodiment visualizes the area to which correction processing for a specific color (e.g., skin color) is applied, allowing the user to intuitively understand the results. In contrast, in this embodiment, the specific color is extracted by limiting the range of saturation in addition to the range of lightness and hue angle, thereby enabling more accurate color extraction. Second, the video viewing device 100 of this embodiment displays numerical values ​​(average level and maximum level) for the level of a specific color (e.g., skin color) in HDR / wide color gamut video. This allows the user to clearly understand the level of the specific color. Third, the video viewing device 100 of this embodiment displays a vectorscope that shows the coordinates in the color space of the color that serves as the reference for color gamut conversion. This allows the user of the video viewing device 100 to easily check whether the algorithm applied in the color gamut conversion process is correct. In other words, when a user views an SDR / standard color gamut video signal converted from an HDR / wide color gamut video signal, they can check whether the conversion algorithm set in the production system is being applied correctly.

[0167] 13 is a schematic diagram showing an example of image information representing a region to be subjected to specific color correction extracted by the specific color correction determination processing unit 132 according to the embodiment. That is, in the image shown in this figure, the region shown in white is the region to be subjected to specific color correction. Furthermore, the region shown in black is the other region (region not to be subjected to correction). The image in this figure is calculated based on an input image. The input image in this example is an image of a person (anchor) sitting and facing forward in a television program. As shown in the figure, the region to be subjected to specific color (skin color) correction mainly includes the person's face (excluding the eyes and lips) and neck.

[0168] 14 is a schematic diagram showing an example of an image in which the specific color correction determination processing unit 132 according to the embodiment leaves the color of only the area to be corrected for a specific color and grayscales the other areas (areas not to be corrected). In the figure, the area indicated by P is the area to be corrected for a specific color and is displayed in color. The area indicated by P is the person's face and neck, and some of the flowers placed in front of the person. The other areas are displayed in grayscale (white, black, and intermediate colors).

[0169] That is, video viewing device 100 visualizes the area to which specific color correction (skin color correction) is applied in a manner that allows the area to be seen at a glance. By displaying an image such as that shown in Fig. 14 on the screen of video viewing device 100, the user (video engineer) can intuitively grasp the area to which correction processing is applied.

[0170] FIG. 15 is a schematic diagram showing the coordinates of each color on a vectorscope output by the vector image generator 2 when converting an HDR / wide color gamut video signal into an SDR / standard color gamut video signal. The diagram shows the coordinate axes of the I and Q coordinate system and the coordinate axes of the (RY) and (BY) coordinate system. As shown in the diagram, the 100% and 75% video signal levels of the six RGBCYM colors are plotted at the correct vector coordinate positions. This allows the user of the video viewing device 100 to easily determine whether the conversion algorithm set in the video production system is correct.

[0171] The conversion from HDR / wide color gamut video signals to SDR / standard color gamut video signals here uses the specific color (skin tone) correction process described above, the dynamic range conversion described in reference [Report ITU-R BT.2446-0 “Methods for conversion of high dynamic range], and the color gamut conversion described in reference [Report ITU-R BT.2407-0 “Colour gamut conversion from Recommendation].

[0172] The vector coordinates of each color (100% video signal level and 75% video signal level for six colors of RGBCYM) shown in FIG. 15 are as shown in Table 1 below.

[0173] [Table 1]

[0174] The above coordinates are Cartesian coordinate values ​​defined by the B'-Y' axis and the R'-Y' axis. The vector coordinate data selection unit 23 selects vector coordinate values ​​according to the color gamut. As mentioned above, the vector coordinate data selection unit 23 uses vector coordinate values ​​written in a lookup table or the like as appropriate.

[0175] The vector coordinate values ​​in Table 1 above were calculated using the following method. That is, except for the specific color (skin tone) correction process, where σ2 = 2.5, the same parameter values ​​were used as in the example of specific color (skin tone) correction process described above. Dynamic range conversion was performed using Method C, with the crosstalk matrix parameter α = 0.33 and the saturation correction parameter σ = 1. For the tone mapping curve parameters, 50% HLG has a linear function gain corresponding to 64.55% SDR, the inflection point from the linear function to the logarithmic function is 88.8% SDR, and the corresponding point of the reference white is 75% HLG, which corresponds to 100% SDR. Color gamut conversion was performed using Annex 2.

[0176] [Variations] In the above embodiment, the video viewing device 100 was equipped with both a picture image generation unit 1 and a vector image generation unit 2. The image selection unit 3 selected an image to be displayed on the display unit 4 from among the images from the picture image generation unit 1 and the vector image generation unit 2. As a modification, the video viewing device 100 may be equipped with only one of the picture image generation unit 1 and the vector image generation unit 2. In this case, the following applies. That is, if the video viewing device 100 is equipped with the picture image generation unit 1, the display unit 4 displays the image output from the picture image generation unit 1. Furthermore, if the video viewing device 100 is equipped with the vector image generation unit 2, the display unit 4 displays the image output from the vector image generation unit 2.

[0177] Although an embodiment of the present invention has been described above in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and includes designs within the scope of the gist of the present invention. [Industrial Applicability]

[0178] The image viewing device according to the present invention can be used for the purpose of, for example, producing images, etc. However, the scope of use of the present invention is not limited to the examples given here. [Explanation of symbols]

[0179] 1. Picture image generation unit 2 Vector image generation section 3 Image selection section 4 Display 5. Control section 11 Color gamut determination processing unit 12 Matrix conversion section 13 Specific color correction application area extraction unit 14 Image switching section 21 Color gamut determination processing unit 22 Vector data conversion section 23 Vector coordinate data selection section (reference color coordinate selection section) 24 Background image storage section 25 Image synthesis processing unit 100 Video viewing device 131 Color space conversion processing unit 132 Specific color correction judgment processing unit 133 Color space reconversion processing unit 134 Specific color extraction section 135 Average and maximum level calculation section 901 Central Processing Unit 902 RAM 903 Input / Output Ports 904,905 Input / Output Devices 906 Bus

Claims

1. A correction factor f used to correct the saturation of pixels in the input image whose color meets certain conditions. ｃｏｒ The correction factor f ｃｏｒ a specific color correction determination processing unit that determines whether the pixel is a correction target or not based on the value of a display unit that displays an image output by the specific color correction determination processing unit; A video viewing device comprising:

2. The specific color correction determination processing unit calculates the correction factor f that changes continuously in response to changes in the brightness of the pixel. ｃｏｒ and the correction factor f is continuously changed in response to a change in the hue angle of the pixel. ｃｏｒ , seeking, 2. The video viewing device according to claim 1.

3. the specific color correction determination processing unit changes the saturation of the pixel that is not the correction target, when the color of the pixel is expressed by lightness, hue angle, and saturation, to zero; 2. The video viewing device according to claim 1.

4. The specific color correction determination processing unit The correction factor f ｃｏｒ If the value of indicates that the saturation of the pixel is not to be corrected, the saturation of the pixel is changed to zero, and The correction factor f ｃｏｒ If the value of indicates that the saturation of the pixel is to be corrected, the saturation of the pixel is not changed.

4. The video viewing device according to claim 3.

5. The correction factor f ｃｏｒ has the effect of reducing the saturation of the pixel, The specific color correction determination processing unit further changes the saturation of the pixel to zero when the degree of reduction in the saturation of the pixel due to the correction is lower than a predetermined threshold.

4. The video viewing device according to claim 3.

6. an average / maximum level calculation unit that calculates at least one of a maximum level and an average level for pixels in the image that are determined by the specific color correction determination processing unit to be pixels to be corrected; Furthermore, the display unit further displays at least one of the maximum level and the average level calculated by the average / maximum level calculation unit.

2. The video viewing device according to claim 1.

7. a color gamut determination processing unit that determines the color gamut of the image; a vector data conversion unit that converts the colors included in the image into vector data that represent coordinates in a predetermined color space based on the color gamut that is the determination result; a reference color coordinate selection unit that selects a coordinate value of a reference color in the predetermined color space based on the color gamut that is the determination result; an image synthesis processing unit that synthesizes an image obtained by superimposing an image represented by the vector data that is the result of conversion by the vector data conversion unit and a mark indicating the position represented by the coordinate values ​​selected by the reference color coordinate selection unit; an image selection unit that selects which of the image output by the specific color correction determination processing unit and the image output by the image synthesis processing unit is to be displayed; Furthermore, the display unit displays the image selected by the image selection unit.

2. The video viewing device according to claim 1.

8. The reference colors are red (R), green (G), blue (B), cyan (C), magenta (M), and yellow (Y) for 75% Hybrid Log Gamma (HLG) and 100% Hybrid Log Gamma (HLG), respectively; 8. The video viewing device according to claim 7.

9. A correction factor f used to correct the saturation of pixels in the input image whose color meets certain conditions. ｃｏｒ The correction factor f ｃｏｒ a specific color correction determination process for determining whether the pixel is a correction target based on the value of A program that causes a computer to function as a video viewing device equipped with the above.

Images