Image display device and program

Abstract

To display a beautiful skin color even in a content whose environment (condition) in the time of imaging and editing is not known.SOLUTION: An image display device for performing image processing on input video data and outputting the data to a display unit comprises: a face detection unit which detects the face of a person from the video data; a histogram detection unit which performs histogram detection related to color information from the video data; a shift detection unit which detects a shift degree related to the color information of the skin color of the video data by using the face detection result in the face detection unit and the histogram detection result in the histogram detection unit; a color correction parameter generation unit which generates a parameter for color correction on the basis of the shift degree related to the color information of the skin color detected by the shift detection unit; and a color correction unit which performs color correction of the video data on the basis of the parameter for color correction generated by the color correction parameter generation unit.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an image display device and a program. [Background technology]

[0002] Conventionally, in imaging devices such as digital cameras, a technology has been disclosed that detects faces from captured images of people using AI (Artificial Intelligence) technology and then performs color correction on the skin color portions of the detected faces. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 4983643 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when applying conventional technology to image display devices such as televisions, there is a problem in that the environment when the input video was shot and edited is unknown, and the video characteristics differ for each content or scene, making it difficult to perform color correction appropriate for the content or scene. [Means for solving the problem]

[0005] An image display device according to an embodiment is an image display device that processes input video data and outputs the processed video data to a display unit, and includes a face detection unit that detects a human face from the video data, a histogram detection unit that detects a hue histogram from the video data, and a red shift degree that is a degree to which the hue of the skin color of the video data is shifted toward red, using a face detection result from the face detection unit and a histogram detection result from the histogram detection unit. andthe color correction parameter generation unit has a standard first color correction parameter applied when the degree of red shift and the degree of yellow shift are minimum, a second color correction parameter that is optimal when the degree of red shift is maximum, and a third color correction parameter that is optimal when the degree of yellow shift is maximum, and when the first color correction parameter is a value that adds red to a skin color region, the second color correction parameter is a value obtained by subtracting the amount of redness to be added from the first color correction parameter, and the third color correction parameter is a value obtained by adding the amount of redness to be added from the first color correction parameter. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a schematic diagram illustrating an example of an image display device according to a first embodiment. [Figure 2] FIG. 2 is a functional block diagram showing the functional configuration of the skin image correction unit. [Figure 3] FIG. 3 is a diagram showing an example of a face detection method in the face detection unit. [Figure 4] FIG. 4 is a diagram showing an example of a histogram detection method in the histogram detection unit. [Figure 5] FIG. 5 is a diagram showing an example of adding restrictions to histogram detection. [Figure 6] FIG. 6 is a diagram showing an example of color correction in the color correction unit. [Figure 7] FIG. 7 is a flowchart showing an example of the flow of the skin image correction process executed by the skin image corrector. [Figure 8] FIG. 8 is a schematic diagram showing a modified example of the image display device. [Figure 9] FIG. 9 is a functional block diagram showing the functional configuration of a skin image correction unit according to the second embodiment. [Figure 10] FIG. 10 is a diagram showing an example of a histogram detection method in the histogram detection unit. [Figure 11] FIG. 11 is a flowchart showing an example of the flow of the skin image correction process executed by the skin image corrector. DETAILED DESCRIPTION OF THE INVENTION

[0007] The image display device and the program will be described in detail below with reference to the accompanying drawings.

[0008] (First embodiment) FIG. 1 is a schematic diagram showing an example of an image display device 1 according to the first embodiment.

[0009] The image display device 1 includes an image processing unit 10 and a display unit 12. Data that has undergone image processing in the image processing unit 10 is transferred to the display unit 12 and displayed on the display.

[0010] Video data 40 is input to the image processing unit 10 from a tuner unit, an HDMI (High-Definition Multimedia Interface) (registered trademark) terminal, etc. (not shown). The image processing unit 10 performs image processing on the input video data 40 to generate video data 42, and outputs the video data 42 to the display unit 12.

[0011] The image processing unit 10 includes an image quality adjustment unit 20 and a skin image correction unit 22.

[0012] Image quality adjustment unit 20 has a function of adjusting gamma, hue, brightness, etc. of input image data 40. Image quality adjustment unit 20 adjusts input image data 40 to generate image data 41, and outputs the image data 41 to skin image correction unit 22.

[0013] The skin image correction unit 22 determines the scene to be corrected and performs color correction in real time on the video data 41 input from the image quality adjustment unit 20 in order to display a good image even when the environment (conditions) at the time of shooting or editing is unknown.

[0014] FIG. 2 is a functional block diagram showing the functional configuration of the skin image correction unit 22. As shown in FIG.

[0015] 2, skin image correction unit 22 has face detection unit 23, histogram detection unit 24, skin color hue shift detection unit 25 which is a shift detection unit, color correction parameter generation unit 26, and color correction unit 27. Skin image correction unit 22 generally uses the face detection result from face detection unit 23 and the histogram detection result from histogram detection unit 24 to detect the degree of hue shift of skin color in video data 41 (input video) input from image quality adjustment unit 20 in skin color hue shift detection unit 25. Based on the degree of hue shift detected in skin color hue shift detection unit 25, skin image correction unit 22 generates correction parameters according to the degree of hue shift in color using color correction parameter generation unit 26, and performs color correction using color correction unit 27.

[0016] The face detection unit 23, histogram detection unit 24, skin color hue shift detection unit 25, color correction parameter generation unit 26, and color correction unit 27 may be realized by hardware, software, or both hardware and software.

[0017] The display unit 12 includes a display driver 14 and a display unit 16. The display unit 16 is a display that displays images. The display unit 16 is, for example, an organic light emitting diode (EL) display, a liquid crystal display, or the like.

[0018] The display driver 14 converts the video data 42 input from the image processor 10 into a voltage and current for driving the display unit 16 , and drives the display unit 16 .

[0019] Next, each component of the skin image correction unit 22 will be described in detail.

[0020] The face detection unit 23 detects human faces from the video data 41 input from the image quality adjustment unit 20. Here, FIG. 3 is a diagram showing an example of a face detection method in the face detection unit 23. As shown in FIG. 3, one face detection method is to divide the video data 41 into multiple areas using a DNN (Deep Neural Network) that has been trained in advance to be able to detect various faces, and to calculate the probability (0 to 1) that each area contains a human face. With such a method, areas containing human faces have high numerical values ​​and areas not containing human faces have low numerical values, so the face detection unit 23 detects areas with values ​​greater than a certain threshold as containing a human face and areas with values ​​smaller than the threshold as not containing a human face. If the area containing a human face is equal to or greater than a certain area, the face detection unit 23 detects it as a human face.

[0021] The histogram detection unit 24 performs histogram detection of hues from the video data 41 input from the image quality adjustment unit 20. Here, FIG. 4 shows an example of a histogram detection method used by the histogram detection unit 24. FIG. 4(a) shows a hue distribution based on CbCr in a YCbCr signal, and FIG. 4(b) shows the YCbCr color space. Histogram detection by the histogram detection unit 24 involves, for example, determining the number of pixels distributed in a specific hue in the entire image related to the video data 41, or in a partial area of ​​the image related to the video data 41 that includes a person's face, and creating a histogram.

[0022] Here, Fig. 5 shows an example of limiting histogram detection. As shown in Fig. 5, the histogram detection unit 24 may limit the range of saturation in the three-dimensional YCbCr color space (Fig. 5(a)), or may limit the range of luminance in the three-dimensional YCbCr color space (Fig. 5(b)).

[0023] The skin color hue shift detection unit 25 uses the face detection result from the face detection unit 23 and the histogram detection result from the histogram detection unit 24 to detect the degree of hue shift of the skin color in the video data 41 input from the image quality adjustment unit 20. The skin color hue shift detection unit 25 detects, for example, the degree to which the hue of the skin color in the video data 41 input from the image quality adjustment unit 20 has shifted toward red or yellow.

[0024] For example, when the skin color hue is shifted toward red, the skin color hue shift detection unit 25 calculates a "red shift amount" indicating the degree of red shift. When the skin color hue is shifted toward yellow, the skin color hue shift detection unit 25 calculates a "yellow shift amount" indicating the degree of yellow shift. On the other hand, when the skin color hue is not shifted toward red or when the skin color hue is not shifted toward yellow, the skin color hue shift detection unit 25 sets the "red shift amount" and "yellow shift amount," indicating the degree of red shift, to 0.

[0025] The color correction parameter generation unit 26 generates color correction parameters to be applied to the color correction unit 27 based on the “amount of shift toward red” or “amount of shift toward yellow” detected by the skin color hue shift detection unit 25 .

[0026] For example, the color correction parameter generation unit 26 has a standard color management table (CMS[m]) that is applied when there is no hue shift, a color management table (CMR[m]) that is optimal when the degree of red shift (RH; 0 to 1) is 1, and a color management table (CMY[m]) that is optimal when the degree of yellow shift (YH; 0 to 1) is 1.

[0027] The color correction parameter generation unit 26 generates the color correction parameters as a color management table (CM[m]) that is ultimately applied to the color correction unit 27. Here, CM[m] consists of elements of hue H[h], saturation S[s], and lightness V[v]. That is, m=h×s×v.

[0028] When both the degree of red shift and the degree of yellow shift in the detection result by the skin color hue shift detection unit 25 are 0, the color correction parameter generation unit 26 sets CM[m]=CMS[m] as a color correction parameter to be applied to the color correction unit 27. Furthermore, when the degree of red shift in the detection result by the skin color hue shift detection unit 25 is not 0, the color correction parameter generation unit 26 sets CM[m]=RH×CMR[m]+(1−RH)×CMS[m] as a color correction parameter to be applied to the color correction unit 27. Furthermore, when the degree of yellow shift in the detection result by the skin color hue shift detection unit 25 is not 0, the color correction parameter generation unit 26 sets CM[m]=YH×CMY[m]+(1−YH)×CMS[m] as a color correction parameter to be applied to the color correction unit 27.

[0029] Here, when CMS[m] is a value that adds a little red to the skin color area, CMR[m] is a value that is a certain minus (-) amount of red to be added, and CMY[m] is a value that is a certain plus (+) amount of red to be added. If the video data 41 (input video) input from the image quality adjustment unit 20 is shifted toward red, excessive correction can be suppressed. Also, if the video data 41 (input video) input from the image quality adjustment unit 20 is shifted toward yellow, insufficient correction can be compensated for.

[0030] The color correction unit 27 performs color correction on the video data 41 input from the image quality adjustment unit 20 based on the color management table (CM[m]) applied by the color correction parameter generation unit .

[0031] 6 is a diagram showing an example of color correction in the color correction unit 27. CM[m] consists of elements of hue H[h], saturation S[s], and lightness V[v]. Hue H[h], saturation S[s], and lightness V[v] represent the degree of correction of hue, saturation, and lightness at the point where h, s, and v overlap in the three-dimensional YCbCr space (see FIG. 6(d)).

[0032] It should be noted that the color correction unit 27 performs interpolation for intermediate values ​​between points using correction values ​​of adjacent points.

[0033] Next, an example of the flow of the skin image correction process executed by the skin image corrector 22 will be described.

[0034] Fig. 7 is a flowchart showing an example of the flow of skin image correction processing executed by skin image correction unit 22. As shown in Fig. 7, face detection unit 23 divides video data 41 input from image quality adjustment unit 20 into a plurality of areas, and detects whether a human face is included in each area (step S1).

[0035] If the area containing a human face is equal to or larger than a certain area (Yes in step S2), face detection unit 23 determines that a human face has been detected in video data 41, and proceeds to step S3. On the other hand, if the area containing a human face is smaller than a certain area (No in step S2), face detection unit 23 determines that a human face has not been detected in video data 41, and proceeds to step S6.

[0036] In step S 3 , the histogram detection unit 24 obtains a hue histogram from the video data 41 input from the image quality adjustment unit 20 .

[0037] Next, the skin color hue shift detection unit 25 uses the face detection result from the face detection unit 23 and the histogram detection result from the histogram detection unit 24 to detect the degree to which the skin color hue of the video data 41 input from the image quality adjustment unit 20 has shifted toward red and the degree to which the skin color hue has shifted toward yellow (step S4).

[0038] If the skin color hue has shifted toward red or toward yellow (Yes in step S4), the skin color hue shift detection unit 25 calculates a "red shift amount" indicating the degree of red shift or a "yellow shift amount" indicating the degree of yellow shift (step S5). On the other hand, if the skin color hue has not shifted toward red or has not shifted toward yellow (No in step S4), or if the area containing a human face is less than a certain area (No in step S2), the skin color hue shift detection unit 25 sets the "red shift amount" indicating the degree of red shift and the "yellow shift amount" indicating the degree of yellow shift to 0 (step S6).

[0039] Next, the color correction parameter generation unit 26 generates color correction parameters to be applied to the color correction unit 27 based on the "amount of shift toward red" or "amount of shift toward yellow" detected by the skin color hue shift detection unit 25 (step S7).

[0040] Finally, the color correction unit 27 performs color correction on the video data 41 input from the image quality adjustment unit 20 based on the color correction parameters applied by the color correction parameter generation unit 26 (step S8).

[0041] In this way, according to the image display device of the first embodiment, by detecting faces and the degree of hue shift in real time and correcting skin color to match the characteristics of the input image, it is possible to display beautiful skin color even in content where the environment (conditions) at the time of shooting or editing are unknown, and to display good images.

[0042] In this embodiment, the histogram detection unit 24 acquires a hue histogram from the video data 41 input from the image quality adjustment unit 20, but the present invention is not limited to this. FIG. 8 is a schematic diagram showing a modified example of the image display device 1. As shown in FIG. 8, the image display device 1 may further include a face region extraction unit 28 in the skin image correction unit 22. The face region extraction unit 28 extracts only those areas of the input video that are highly likely to contain a human face based on the face detection results of the face detection unit 23. The histogram detection unit 24 then acquires a hue histogram from only those areas of the input video that are highly likely to contain a human face.

[0043] By doing so, it is possible to prevent components other than human faces from being included in the histogram detection result as much as possible.

[0044] (Second embodiment) Next, a second embodiment will be described.

[0045] The second embodiment differs from the first embodiment in that a saturation histogram is detected from video data 41. In the following description of the second embodiment, the same parts as those in the first embodiment will be omitted, and only the parts that differ from the first embodiment will be described.

[0046] FIG. 9 is a functional block diagram showing the functional configuration of the skin image correction unit 22 according to the second embodiment.

[0047] As shown in FIG. 9, the skin image correction unit 22 of the image display device 1 according to this embodiment has a histogram detection unit 34, a skin color saturation shift detection unit 35 which is a shift detection unit, and a color correction parameter generation unit 36, instead of the histogram detection unit 24, the skin color hue shift detection unit 25, and the color correction parameter generation unit 26 described in the second embodiment.

[0048] The histogram detection unit 34 performs saturation histogram detection from the video data 41 input from the image quality adjustment unit 20. FIG. 10 shows an example of a histogram detection method used by the histogram detection unit 34. FIG. 10(a) shows a saturation distribution based on CbCr in a YCbCr signal, and FIG. 10(b) shows a YCbCr color space. The histogram detection performed by the histogram detection unit 34 involves, for example, determining the number of pixels distributed at a specific saturation in the entire image related to the video data 41 or in a partial area of ​​the image related to the video data 41 that includes a person's face, and creating a histogram. As shown in FIG. 10(a), the histogram detection unit 34 may impose a saturation restriction in a three-dimensional YCbCr color space during histogram detection.

[0049] The skin color saturation shift detection unit 35 detects the degree of saturation shift of skin color in the video data 41 input from the image quality adjustment unit 20, using the face detection result from the face detection unit 23 and the histogram detection result from the histogram detection unit 34. The skin color saturation shift detection unit 35 detects, for example, a "high saturation shift amount" which is the degree to which the saturation of skin color has shifted to a higher saturation than expected, and a "low saturation shift amount" which is the degree to which the saturation of skin color has shifted to a lower saturation than expected.

[0050] The color correction parameter generation unit 36 ​​generates color correction parameters to be applied to the color correction unit 27 based on the “high saturation shift amount” and “low saturation shift amount” detected by the skin color saturation shift detection unit 35 .

[0051] For example, the color correction parameter generation unit 36 ​​has a standard color management table (CMS[m]) that is applied when there is no saturation shift, a color management table (CMR[m]) that is optimal when the degree of high saturation shift (RH; 0 to 1) is 1, and a color management table (CMY[m]) that is optimal when the degree of low saturation shift (YH; 0 to 1) is 1.

[0052] The color correction parameter generation unit 36 ​​generates the color correction parameters as a color management table (CM[m]) that is ultimately applied to the color correction unit 27. Here, CM[m] consists of elements of hue H[h], saturation S[s], and lightness V[v]. That is, m=h×s×v.

[0053] When both the degree of high saturation shift and the degree of low saturation shift in the detection result by the skin color saturation shift detection unit 35 are 0, the color correction parameter generation unit 36 ​​sets CM[m]=CMS[m] as a color correction parameter to be applied to the color correction unit 27. Furthermore, when the degree of high saturation shift in the detection result by the skin color saturation shift detection unit 35 is not 0, the color correction parameter generation unit 36 ​​sets CM[m]=RH×CMR[m]+(1−RH)×CMS[m] as a color correction parameter to be applied to the color correction unit 27. Furthermore, when the degree of low saturation shift in the detection result by the skin color saturation shift detection unit 35 is not 0, the color correction parameter generation unit 36 ​​sets CM[m]=YH×CMY[m]+(1−YH)×CMS[m] as a color correction parameter to be applied to the color correction unit 27.

[0054] Here, when CMS[m] is a value that slightly increases the saturation for the skin color region, CMR[m] is a value that is a certain negative (-) amount of increase in saturation, and CMY[m] is a value that is a certain positive (+) amount of increase in saturation. If the video data 41 (input video) input from the image quality adjustment unit 20 is shifted to high saturation, excessive correction can be suppressed. If the video data 41 (input video) input from the image quality adjustment unit 20 is shifted to low saturation, insufficient correction can be compensated for.

[0055] Next, an example of the flow of the skin image correction process executed by the skin image corrector 22 will be described.

[0056] Fig. 11 is a flowchart showing an example of the flow of skin image correction processing executed by skin image correction unit 22. As shown in Fig. 11, face detection unit 23 divides video data 41 input from image quality adjustment unit 20 into a plurality of areas, and detects whether a human face is included in each area (step S11).

[0057] If the area containing a human face is equal to or larger than a certain area (Yes in step S12), face detection unit 23 determines that a human face has been detected in video data 41, and proceeds to step S13. On the other hand, if the area containing a human face is smaller than a certain area (No in step S12), face detection unit 23 determines that a human face has not been detected in video data 41, and proceeds to step S16.

[0058] In step S13, the histogram detection unit 34 obtains a saturation histogram from the video data 41 input from the image quality adjustment unit 20.

[0059] Next, the skin color saturation shift detection unit 35 uses the face detection result from the face detection unit 23 and the histogram detection result from the histogram detection unit 34 to detect the degree to which the skin color saturation of the video data 41 input from the image quality adjustment unit 20 has shifted to a higher saturation than expected (step S14).

[0060] If the saturation of skin color is shifted higher than expected or if the saturation of skin color is shifted lower than expected (Yes in step S14), the skin color saturation shift detection unit 35 calculates a "high saturation shift amount" indicating the degree of shift to high saturation or a "low saturation shift amount" indicating the degree of shift to low saturation (step S15). On the other hand, if the saturation of skin color is not shifted higher than expected or if the saturation of skin color is not shifted lower than expected (No in step S14), or if the area containing a human face is less than a certain area (No in step S12), the skin color saturation shift detection unit 35 sets the "high saturation shift amount" indicating the degree of shift to high saturation and the "low saturation shift amount" indicating the degree of shift to low saturation to 0 (step S16).

[0061] Next, the color correction parameter generation unit 36 ​​generates color correction parameters to be applied to the color correction unit 27 based on the “high saturation shift amount” or “low saturation shift amount” detected by the skin color saturation shift detection unit 35 (step S17).

[0062] Finally, the color correction unit 27 performs color correction on the video data 41 input from the image quality adjustment unit 20 based on the color correction parameters applied by the color correction parameter generation unit 26 (step S18).

[0063] In this way, according to the image display device of the second embodiment, by detecting faces and the degree of saturation shift in real time and correcting skin color to match the characteristics of the input image, it is possible to display beautiful skin color even in content where the environment (conditions) at the time of shooting or editing are unknown, and to display good images.

[0064] In this embodiment, the histogram detection unit 34 acquires a saturation histogram from the video data 41 input from the image quality adjustment unit 20, but the present invention is not limited to this. For example, the histogram detection unit 34 may acquire a hue histogram as described in the first embodiment, in addition to the saturation histogram acquired from the video data 41 input from the image quality adjustment unit 20. In this way, by detecting faces in real time and detecting the degree of hue shift and the degree of saturation shift, and correcting skin colors in accordance with the characteristics of the input video, it is possible to display beautiful skin colors in any content.

[0065] The program (software) executed by the image display device 1 of this embodiment is provided in a state that it is pre-installed in a ROM or the like.

[0066] The program (software) executed by the image display device 1 of this embodiment may be configured to be provided by being recorded in an installable or executable file format on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD (Digital Versatile Disc).

[0067] Furthermore, the program (software) executed by the image display device 1 of this embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the program (software) executed by the image display device 1 of this embodiment may be provided or distributed via a network such as the Internet.

[0068] Although the embodiments and modifications of the present invention have been described above, they are presented as examples and are not intended to limit the scope of the invention. These novel embodiments and modifications can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The above embodiments and modifications are included within the scope and spirit of the invention, and are also included in the inventions and their equivalents as defined in the claims. [Explanation of symbols]

[0069] 1 Image display device 12 Display section 23 Face detection unit 24, 34 Histogram detector 25, 35 Shift detection section 26, 36 Color correction parameter generation section 27 Color Correction Section 28 Face area extraction unit

Claims

1. An image display device that processes input video data and outputs the processed video data to a display unit, a face detection unit that detects a person's face from the video data; a histogram detection unit that detects a hue histogram from the video data; a shift detection unit that uses the face detection result from the face detection unit and the histogram detection result from the histogram detection unit to detect a red shift degree, which is the degree to which the hue of the skin color of the video data is shifted toward red, and a yellow shift degree, which is the degree to which the hue of the skin color of the video data is shifted toward yellow; a color correction parameter generation unit that generates parameters for color correction based on the degree of red shift and the degree of yellow shift detected by the shift detection unit; a color correction unit that performs color correction on the video data based on the color correction parameters generated by the color correction parameter generation unit; Equipped with The color correction parameter generation unit a standard first color correction parameter to be applied when the degree of red shift and the degree of yellow shift are at their minimum values, a second color correction parameter that is optimal when the degree of red shift is at its maximum value, and a third color correction parameter that is optimal when the degree of yellow shift is at its maximum value, When the first color correction parameter is a value for adding reddishness to a skin color region, the second color correction parameter is a minus value obtained by comparing the amount of reddishness to the first color correction parameter, and the third color correction parameter is a plus value obtained by comparing the amount of reddishness to the first color correction parameter. An image display device characterized by:

2. An image display device that processes input video data and outputs the processed video data to a display unit, a face detection unit that detects a person's face from the video data; a histogram detection unit that detects a saturation histogram from the video data; a shift detection unit that uses the face detection result from the face detection unit and the histogram detection result from the histogram detection unit to detect a high saturation shift degree, which is a degree to which the saturation of the skin color of the video data has shifted to a higher saturation than an assumed value, and a low saturation shift degree, which is a degree to which the saturation of the skin color of the video data has shifted to a lower saturation than an assumed value; a color correction parameter generation unit that generates parameters for color correction based on the degree of the high saturation shift and the degree of the low saturation shift detected by the shift detection unit; a color correction unit that performs color correction on the video data based on the color correction parameters generated by the color correction parameter generation unit; Equipped with The color correction parameter generation unit a standard first color correction parameter applied when the degree of the high saturation shift and the degree of the low saturation shift are at their minimum values, a second color correction parameter that is optimal when the degree of the high saturation shift is at its maximum value, and a third color correction parameter that is optimal when the degree of the low saturation shift is at its maximum value, When the first color correction parameter is a value that increases saturation for a skin color region, the second color correction parameter is a value obtained by subtracting the amount of saturation increase from the first color correction parameter, and the third color correction parameter is a value obtained by adding the amount of saturation increase from the first color correction parameter. An image display device characterized by:

3. the histogram detection unit limits the range of saturation in a three-dimensional YCbCr color space in detecting a histogram from the video data.

3. The image display device according to claim 1, wherein the image display device is a display device having a plurality of display areas.

4. the histogram detection unit limits a luminance range in a three-dimensional YCbCr color space in detecting a histogram from the video data.

2. The image display device according to claim 1, wherein the image display device is a display device having a plurality of display areas.

5. a face region extraction unit that extracts only a region of the video data that is highly likely to contain a human face based on the face detection result of the face detection unit; the histogram detection unit acquires a hue histogram only from the area extracted by the face area extraction unit that has a high probability of being the person's face.

2. The image display device according to claim 1, wherein the image display device is a display device having a plurality of display areas.

6. A computer that controls an image display device that processes input video data and outputs the processed video data to a display unit, a face detection unit that detects a person's face from the video data; a histogram detection unit that detects a hue histogram from the video data; a shift detection unit that uses the face detection result from the face detection unit and the histogram detection result from the histogram detection unit to detect a red shift degree, which is the degree to which the hue of the skin color of the video data is shifted toward red, and a yellow shift degree, which is the degree to which the hue of the skin color of the video data is shifted toward yellow; a color correction parameter generation unit that generates parameters for color correction based on the degree of red shift and the degree of yellow shift detected by the shift detection unit; a color correction unit that performs color correction on the video data based on the color correction parameters generated by the color correction parameter generation unit; It functions as The color correction parameter generation unit a standard first color correction parameter to be applied when the degree of red shift and the degree of yellow shift are at their minimum values, a second color correction parameter that is optimal when the degree of red shift is at its maximum value, and a third color correction parameter that is optimal when the degree of yellow shift is at its maximum value, When the first color correction parameter is a value for adding reddishness to a skin color region, the second color correction parameter is a minus value obtained by comparing the amount of reddishness to the first color correction parameter, and the third color correction parameter is a plus value obtained by comparing the amount of reddishness to the first color correction parameter. Program for.

7. A computer that controls an image display device that processes input video data and outputs the processed video data to a display unit, a face detection unit that detects a person's face from the video data; a histogram detection unit that detects a saturation histogram from the video data; a shift detection unit that uses the face detection result from the face detection unit and the histogram detection result from the histogram detection unit to detect a high saturation shift degree, which is a degree to which the saturation of the skin color of the video data has shifted to a higher saturation than an assumed value, and a low saturation shift degree, which is a degree to which the saturation of the skin color of the video data has shifted to a lower saturation than an assumed value; a color correction parameter generation unit that generates parameters for color correction based on the degree of the high saturation shift and the degree of the low saturation shift detected by the shift detection unit; a color correction unit that performs color correction on the video data based on the color correction parameters generated by the color correction parameter generation unit; It functions as The color correction parameter generation unit a standard first color correction parameter applied when the degree of the high saturation shift and the degree of the low saturation shift are at their minimum values, a second color correction parameter that is optimal when the degree of the high saturation shift is at its maximum value, and a third color correction parameter that is optimal when the degree of the low saturation shift is at its maximum value, When the first color correction parameter is a value that increases saturation for a skin color region, the second color correction parameter is a value obtained by subtracting the amount of saturation increase from the first color correction parameter, and the third color correction parameter is a value obtained by adding the amount of saturation increase from the first color correction parameter. Program for.

Images