Image processing apparatus and method, display device, electronic device, and storage medium

Abstract

The invention provides an image processing device and method, display equipment, electronic equipment and a storage medium. The image processing apparatus includes: an acquisition unit configured to acquire a multi-view image; the adjusting unit is used for adjusting the pixel gray value of at least one target pixel in at least one target area in the multi-view image according to a preset mapping relation to obtain an adjusted multi-view image, and the preset mapping relation is obtained by measuring the ghosting sensitivity of the display device; and the output unit is used for obtaining a processed image displayed by the display device according to the adjusted multi-view image and outputting the processed image.

Description

Image processing device, method, display device, electronic device, and storage medium Technical Field

[0001] The present disclosure relates to the field of image processing technology, and in particular to an image processing apparatus, method, display device, electronic device, and storage medium. Background Art

[0002] With the development of information science and technology, display technology has also advanced. Glasses-free 3D technology achieves a stereoscopic visual effect without the use of external devices such as polarized glasses. It provides users with a stereoscopic visual experience and a sense of immersion, bringing a whole new visual experience. Glasses-free 3D technology is a significant breakthrough in display technology, enhancing visual quality.

[0003] Crosstalk is a key metric for evaluating naked-eye 3D display performance. It's generally believed that ghosting begins to be noticeable when the crosstalk rate exceeds 2%. When the crosstalk rate exceeds 10%, ghosting becomes noticeable. Reducing the crosstalk rate for naked-eye 3D displays is difficult, requiring improvements to the device's design parameters. Therefore, reducing crosstalk to improve ghosting in naked-eye 3D displays is difficult.

[0004] Summary of the Invention

[0005] In view of this, the present disclosure provides an image processing apparatus, method, display device, electronic device, and storage medium.

[0006] One aspect of the present disclosure provides an image processing apparatus, comprising:

[0007] an acquisition unit, configured to acquire multi-viewpoint images;

[0008] an adjusting unit, configured to adjust the pixel grayscale value of at least one target pixel in at least one target area in the multi-view image according to a preset mapping relationship to obtain an adjusted multi-view image, wherein the preset mapping relationship is obtained by measuring ghosting sensitivity of a display device; and

[0009] An output unit is used to obtain a processed image for display on the display device based on the adjusted multi-viewpoint image, and output the processed image.

[0010] For example, the multi-viewpoint image includes an adjacent first viewpoint image and a second viewpoint image, the first viewpoint image includes N pixels, the second viewpoint image includes N pixels, and N is an integer greater than 1;

[0011] The above-mentioned device also includes a first determination unit, which is used to determine the first area in the above-mentioned first viewpoint image and the second area corresponding to the above-mentioned first area in the above-mentioned second viewpoint image based on the difference between the grayscale values ​​of the N pixels of the above-mentioned first viewpoint image and the grayscale values ​​of the N pixels of the above-mentioned second viewpoint image, and use the above-mentioned first area and the above-mentioned second area as the above-mentioned at least one target area.

[0012] For example, the first determining unit determines, based on the difference between the grayscale values ​​of the N pixels of the first viewpoint image and the grayscale values ​​of the N pixels of the second viewpoint image, the first area in the first viewpoint image and the second area corresponding to the first area in the second viewpoint image, including:

[0013] Determining differences between grayscale values ​​of N pixels of the first viewpoint image and grayscale values ​​of N pixels of the second viewpoint image to obtain N difference values; and

[0014] Based on the above-mentioned N difference values, determine a first area in the above-mentioned first viewpoint image and a second area corresponding to the above-mentioned first area in the above-mentioned second viewpoint image, wherein the first area and the second area both include n adjacent pixels, and the differences between the pixel values ​​of the n pixels in the first area and the pixel values ​​of the n pixels in the second area are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0015] For example, the multi-viewpoint image includes M viewpoint images, where M is an integer greater than 2; each of the M viewpoint images includes N pixels;

[0016] The above device also includes a second determining unit, which is used to

[0017] determining, based on differences between grayscale values ​​of N pixels of the m-th viewpoint image and grayscale values ​​of N pixels of the m+1-th viewpoint image, an m-th region in the m-th viewpoint image and an m+1-th region corresponding to the m-th region in the m+1-th viewpoint image, and using the m-th region and the m+1-th region as the at least one target region to obtain an adjusted m-th viewpoint image and an adjusted m+1-th viewpoint image, where m is greater than or equal to 1 and less than or equal to M-2; and

[0018] According to the difference between the grayscale values ​​of N pixels of the adjusted m+1th viewpoint image and the grayscale values ​​of N pixels of the m+2th viewpoint image, the adjusted m+1th region in the adjusted m+1th viewpoint image and the m+2th region corresponding to the adjusted m+1th region in the m+2th viewpoint image are determined, and the adjusted m+1th region and the m+2th region are used as the at least one target region.

[0019] For example, the second determining unit determines, based on the difference between the grayscale values ​​of N pixels of the m-th viewpoint image and the grayscale values ​​of N pixels of the m+1-th viewpoint image, the m-th region in the m-th viewpoint image and the m+1-th region corresponding to the m-th region in the m+1-th viewpoint image, including:

[0020] Determine the difference between the grayscale values ​​of the N pixels of the m-th viewpoint image and the grayscale values ​​of the N pixels of the m+1-th viewpoint image to obtain N difference values; and

[0021] Based on the above N difference values, the mth region in the above mth viewpoint image and the m+1th region corresponding to the above mth region in the above m+1th viewpoint image are determined, wherein the mth region and the m+1th region both include n adjacent pixels, and the differences between the pixel values ​​of n pixels in the mth region and the pixel values ​​of n pixels in the m+1th region are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0022] For example, the adjusting unit adjusting the pixel grayscale value of at least one target pixel in the at least one target area includes:

[0023] In response to determining that the grayscale value of the at least one target pixel is less than or equal to a first threshold, adjusting the grayscale value of the at least one target pixel to the first threshold;

[0024] In response to determining that the grayscale value of the at least one target pixel is greater than a first threshold and less than or equal to a second threshold, adjusting the grayscale value of the at least one target pixel to a first target value, where the first target value is determined based on the first threshold and the second threshold; and

[0025] In response to determining that the grayscale value of the at least one target pixel is greater than the second threshold, maintaining the grayscale value of the at least one target pixel unchanged;

[0026] The first threshold and the second threshold are determined according to the preset mapping relationship.

[0027] For example, the adjusting unit adjusting the pixel grayscale value of at least one target pixel in the at least one target area includes:

[0028] In response to determining that the grayscale value of the at least one target pixel is greater than or equal to a third threshold, adjusting the grayscale value of the at least one target pixel to the third threshold;

[0029] In response to determining that the grayscale value of the at least one target pixel is less than the third threshold and greater than or equal to a fourth threshold, adjusting the grayscale value of the at least one target pixel to a second target value, where the second target value is determined based on the third threshold and the fourth threshold; and

[0030] In response to determining that the grayscale value of the at least one target pixel is less than the fourth threshold, maintaining the grayscale value of the at least one target pixel unchanged;

[0031] The third threshold and the fourth threshold are determined according to the preset mapping relationship.

[0032] For example, the output unit obtains a processed image for display on a display device based on the adjusted multiple viewpoint images, including:

[0033] The adjusted multi-viewpoint images are stitched together to obtain a processed image for display on a display device.

[0034] For example, the above-mentioned preset mapping relationship includes a mapping relationship between the grayscale values ​​of pixels in the above-mentioned target area and multiple thresholds, and the grayscale values ​​of the above-mentioned pixels include the highest grayscale value, the lowest grayscale value and the average grayscale value of the pixels in the target area; the above-mentioned multiple thresholds include the first threshold, the second threshold, the third threshold and the above-mentioned fourth threshold.

[0035] Another aspect of the present disclosure provides a display device, comprising:

[0036] The image processing device mentioned above; and

[0037] A display device is used to display the output image from the above image processing device.

[0038] Another aspect of the present disclosure provides an image processing method, comprising:

[0039] Acquire multi-view images;

[0040] Adjusting the pixel grayscale value of at least one target pixel in at least one target area in the multi-view image according to a preset mapping relationship to obtain an adjusted multi-view image, wherein the preset mapping relationship is obtained by measuring ghosting sensitivity of the display device;

[0041] Obtaining a processed image for display on the display device according to the adjusted multi-viewpoint image; and

[0042] Output the processed image.

[0043] For example, the multi-viewpoint image includes an adjacent first viewpoint image and a second viewpoint image, the first viewpoint image includes N pixels, the second viewpoint image includes N pixels, and N is an integer greater than 1;

[0044] The above method further includes:

[0045] determining a first region in the first viewpoint image and a second region corresponding to the first region in the second viewpoint image based on differences between grayscale values ​​of the N pixels in the first viewpoint image and grayscale values ​​of the N pixels in the second viewpoint image; and

[0046] The first area and the second area are used as the at least one target area.

[0047] For example, determining the first area in the first viewpoint image and the second area corresponding to the first area in the second viewpoint image based on the difference between the grayscale values ​​of the N pixels in the first viewpoint image and the grayscale values ​​of the N pixels in the second viewpoint image includes:

[0048] Determining differences between grayscale values ​​of N pixels of the first viewpoint image and grayscale values ​​of N pixels of the second viewpoint image to obtain N difference values; and

[0049] Based on the above-mentioned N difference values, determine a first area in the above-mentioned first viewpoint image and a second area corresponding to the above-mentioned first area in the above-mentioned second viewpoint image, wherein the first area and the second area both include n adjacent pixels, and the differences between the pixel values ​​of the n pixels in the first area and the pixel values ​​of the n pixels in the second area are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0050] For example, the multi-viewpoint image includes M viewpoint images, where M is an integer greater than 2; each of the M viewpoint images includes N pixels;

[0051] The above method further includes:

[0052] determining, based on differences between grayscale values ​​of N pixels of the m-th viewpoint image and grayscale values ​​of N pixels of the m+1-th viewpoint image, an m-th region in the m-th viewpoint image and an m+1-th region corresponding to the m-th region in the m+1-th viewpoint image, and using the m-th region and the m+1-th region as the at least one target region to obtain an adjusted m-th viewpoint image and an adjusted m+1-th viewpoint image, where m is greater than or equal to 1 and less than or equal to M-2; and

[0053] According to the difference between the grayscale values ​​of N pixels of the adjusted m+1th viewpoint image and the grayscale values ​​of N pixels of the m+2th viewpoint image, the adjusted m+1th region in the adjusted m+1th viewpoint image and the m+2th region corresponding to the adjusted m+1th region in the m+2th viewpoint image are determined, and the adjusted m+1th region and the m+2th region are used as the at least one target region.

[0054] For example, determining the mth region in the mth viewpoint image and the m+1th region corresponding to the mth region in the m+1th viewpoint image based on the difference between the grayscale values ​​of N pixels in the mth viewpoint image and the grayscale values ​​of N pixels in the m+1th viewpoint image includes:

[0055] Determine the difference between the grayscale values ​​of the N pixels of the m-th viewpoint image and the grayscale values ​​of the N pixels of the m+1-th viewpoint image to obtain N difference values; and

[0056] Based on the above N difference values, the mth region in the above mth viewpoint image and the m+1th region corresponding to the above mth region in the above m+1th viewpoint image are determined, wherein the mth region and the m+1th region both include n adjacent pixels, and the differences between the pixel values ​​of n pixels in the mth region and the pixel values ​​of n pixels in the m+1th region are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0057] For example, adjusting the pixel grayscale value of at least one target pixel in the at least one target area includes:

[0058] In response to determining that the grayscale value of the at least one target pixel is less than or equal to a first threshold, adjusting the grayscale value of the at least one target pixel to the first threshold;

[0059] In response to determining that the grayscale value of the at least one target pixel is greater than a first threshold and less than or equal to a second threshold, adjusting the grayscale value of the at least one target pixel to a first target value, where the first target value is determined based on the first threshold and the second threshold; and

[0060] In response to determining that the grayscale value of the at least one target pixel is greater than the second threshold, maintaining the grayscale value of the at least one target pixel unchanged;

[0061] The first threshold and the second threshold are determined according to the preset mapping relationship.

[0062] For example, adjusting the pixel grayscale value of at least one target pixel in the at least one target area further includes:

[0063] In response to determining that the grayscale value of the at least one target pixel is greater than or equal to a third threshold, adjusting the grayscale value of the at least one target pixel to the third threshold;

[0064] In response to determining that the grayscale value of the at least one target pixel is less than the third threshold and greater than or equal to a fourth threshold, adjusting the grayscale value of the at least one target pixel to a second target value, where the second target value is determined based on the third threshold and the fourth threshold; and

[0065] In response to determining that the grayscale value of the at least one target pixel is less than the fourth threshold, maintaining the grayscale value of the at least one target pixel unchanged;

[0066] The third threshold and the fourth threshold are determined according to the preset mapping relationship.

[0067] For example, obtaining a processed image for display on a display device based on the adjusted multiple viewpoint images includes:

[0068] The adjusted multi-viewpoint images are stitched together to obtain a processed image for display on a display device.

[0069] For example, the above-mentioned preset mapping relationship includes a mapping relationship between the grayscale values ​​of pixels in the above-mentioned target area and multiple thresholds, and the grayscale values ​​of the above-mentioned pixels include the highest grayscale value, the lowest grayscale value and the average grayscale value of the pixels in the target area; the above-mentioned multiple thresholds include the first threshold, the second threshold, the third threshold and the above-mentioned fourth threshold.

[0070] Another aspect of the present disclosure provides an electronic device including a memory and a processor, wherein the memory stores instructions executable by the processor, and when the instructions are executed by the processor, the processor executes the method described above.

[0071] Another aspect of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute and implement the method described above.

[0072] Another aspect of the present disclosure provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0073] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0075] FIG1 is a block diagram of an image processing apparatus according to an embodiment of the present disclosure;

[0076] FIG2 is a mapping relationship curve according to an embodiment of the present disclosure;

[0077] 3 illustrates a process of adjusting a multi-view image by an image processing apparatus when the multi-view image includes two adjacent view images according to an embodiment of the present disclosure;

[0078] 4 illustrates a process of adjusting a multi-view image by an image processing apparatus when the multi-view image includes at least three view images according to an embodiment of the present disclosure;

[0079] FIG5 is an image displayed by a display device according to an embodiment of the present disclosure;

[0080] FIG6 is a flowchart of an image processing method according to an embodiment of the present disclosure; and

[0081] FIG7 is a block diagram of an electronic device suitable for implementing an image processing method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0082] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of them. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure. It should be noted that throughout the drawings, the same elements are represented by the same or similar figure marks. In the following description, some specific embodiments are only for descriptive purposes and should not be understood as any limitation to the present disclosure, but are only examples of the embodiments of the present disclosure. Conventional structures or configurations will be omitted when they may cause confusion in the understanding of the present disclosure. It should be noted that the shapes and sizes of the components in the figures do not reflect the actual size and proportion, but only illustrate the contents of the embodiments of the present disclosure.

[0083] Unless otherwise defined, technical or scientific terms used in the embodiments of the present disclosure shall have the same general meaning as those skilled in the art. The terms "first," "second," and similar terms used in the embodiments of the present disclosure do not denote any order, quantity, or importance, but are merely used to distinguish different components.

[0084] FIG1 is a block diagram of an image processing apparatus according to an embodiment of the present disclosure.

[0085] As shown in FIG. 1 , the image processing apparatus 100 may include an acquiring unit 101 , an adjusting unit 102 , and an output unit 103 .

[0086] The acquisition unit 101 can be used to acquire a multi-view image. The adjustment unit 102 can be used to adjust the grayscale value of at least one target pixel in at least one target area of ​​the multi-view image according to a preset mapping relationship to obtain an adjusted multi-view image, wherein the preset mapping relationship is obtained by measuring the ghosting sensitivity of a display device. The output unit 103 can be used to obtain a processed image for display on a display device based on the adjusted multi-view image and output the processed image.

[0087] According to an embodiment of the present disclosure, a multi-view image includes multiple viewpoint images. The multiple viewpoint images have parallax differences between each other. The number of multiple viewpoint images can be configured based on actual business needs and is not limited here. For example, the number of multiple viewpoint images can be 2 or 9, etc.

[0088] According to an embodiment of the present disclosure, a naked-eye 3D display device achieves a naked-eye 3D display effect by transmitting two images with parallax to the left and right eyes, respectively. Because multiple viewpoint images have parallax with each other, two adjacent viewpoint images among the multiple viewpoint images, when transmitted to the human eye through the display device, can achieve a naked-eye 3D display effect.

[0089] According to an embodiment of the present disclosure, the target region represents a region where the brightness difference between the same position of two adjacent viewpoint images is large.

[0090] According to an embodiment of the present disclosure, ghosting sensitivity represents a crosstalk rate between multiple preset viewpoint images when a display device displays multiple preset viewpoint images simultaneously.

[0091] According to the embodiments of the present disclosure, when two viewpoint images with parallax are sent to the left and right eyes respectively, a phenomenon in which some of the brightness of the image intended for the left eye reaches the right eye, or vice versa, is called crosstalk. The left view image represents the parallax image sent to the left eye, and the right view image represents the parallax image sent to the right eye. The crosstalk rate represents the ratio of the brightness of the left view image entering the right eye to the overall brightness of the right eye.

[0092] According to an embodiment of the present disclosure, crosstalk rates between a plurality of preset viewpoint images may be obtained through relevant testing equipment.

[0093] According to an embodiment of the present disclosure, after measuring the crosstalk ratio between multiple preset viewpoint images and the brightness curves of each grayscale, the grayscale corresponding to the crosstalk of a certain grayscale brightness of the left viewpoint image to the brightness of the right viewpoint image in the multiple preset viewpoint images can be obtained based on the crosstalk ratio and the brightness curve. A preset mapping relationship can then be obtained based on this grayscale.

[0094] According to an embodiment of the present disclosure, for example, for a naked-eye 3D display device with a crosstalk rate of 2%, the brightness corresponding to grayscale 255 is 250 nits, and the brightness corresponding to grayscale 10 is 5 nits. When the grayscale of any pixel position in the left view image is 255, the brightness of the left view image crosstalked to the right view image is 250*2%=5 nits, which corresponds to grayscale 10. Subsequently, a preset mapping relationship can be obtained based on the grayscale 10, and then the pixel grayscale of the pixel with a grayscale of 255 in the left view image and the pixel corresponding to the pixel in the right view image can be adjusted according to the mapping relationship.

[0095] According to an embodiment of the present disclosure, the preset mapping relationship can be obtained by a mapping relationship formula composed of the grayscale value of the pixel in the target area and multiple thresholds. The preset mapping relationship can include a linear mapping relationship and a curve mapping relationship.

[0096] According to an embodiment of the present disclosure, the size of ghosting is not only related to the crosstalk rate, but also to the brightness difference at the same position in the disparity map. The larger the difference, the larger the ghosting. Therefore, the ghosting can be reduced by adjusting the brightness difference at the same position in the disparity map.

[0097] According to an embodiment of the present disclosure, a multi-view image is acquired by an acquisition unit, and then an adjustment unit adjusts the pixel grayscale value of at least one target pixel in at least one target area of ​​the multi-view image according to a preset mapping relationship to obtain an adjusted multi-view image. This adjusts the target area with a large crosstalk rate, reduces the difference in the corresponding pixel grayscale values ​​of the left and right images in the multi-view image in the target area, and outputs a processed image obtained from the adjusted multi-view image by an output unit, thereby reducing ghosting and improving the display effect. Compared with improving ghosting in a naked-eye 3D display device by reducing the crosstalk rate, this method does not require improving the design parameters of the naked-eye 3D display device, thereby improving the efficiency of improving ghosting in the naked-eye 3D display device.

[0098] According to an embodiment of the present disclosure, the preset mapping relationship includes a mapping relationship between the grayscale values ​​of pixels in the target area and multiple threshold values. The grayscale values ​​of the pixels include the highest grayscale value, the lowest grayscale value, and the average grayscale value of the pixels in the target area. The multiple threshold values ​​include a first threshold value, a second threshold value, a third threshold value, and a fourth threshold value.

[0099] According to an embodiment of the present disclosure, the preset mapping relationship is shown in Table 1.

[0100] Table 1

[0101] In Table 1, N1 represents the first threshold, N2 represents the second threshold, N3 represents the third threshold, and N4 represents the fourth threshold.

[0102] According to an embodiment of the present disclosure, the lowest grayscale, the highest grayscale, and the average grayscale of the multi-view image can be obtained by traversing all pixels of the multi-view image.

[0103] According to an embodiment of the present disclosure, after determining the lowest grayscale, highest grayscale and average grayscale of a multi-view image, the pixel grayscale value of at least one target pixel in at least one target area in the multi-view image can be adjusted according to the first threshold N1, the second threshold N2, the third threshold N3 and the fourth threshold N4 corresponding to the lowest grayscale, the highest grayscale and the average grayscale to obtain an adjusted multi-view image.

[0104] As shown in Table 1, when the highest grayscale value of the multi-view image is 255, the lowest grayscale value is 0, and the average grayscale value is 125, the grayscale values ​​of the pixels in the target area can be updated according to N1 "20", N2 "90", N3 "220", and N4 "180". When the highest grayscale value of the multi-view image is 220, the lowest grayscale value is 10, and the average grayscale value is 110, the grayscale values ​​of the pixels in the target area can be updated according to N1 "30", N2 "90", N3 "200", and N4 "175".

[0105] According to an embodiment of the present disclosure, the highest grayscale value, lowest grayscale value, and average grayscale value of the multi-view image actually calculated may have a grayscale difference with the highest grayscale value, lowest grayscale value, and average grayscale value in Table 1, respectively, and the grayscale difference is less than or equal to a preset value. For example, if the preset value is 1, and the highest grayscale value, lowest grayscale value, and average grayscale value of the multi-view image actually calculated are 249.5, 0.4, and 125.6, the grayscale values ​​of the pixels in the target area can be updated based on N1 "20", N2 "90", N3 "220", and N4 "180".

[0106] According to an embodiment of the present disclosure, based on the preset mapping relationship in Table 1, the adjustment unit adjusts the pixel grayscale value of at least one target pixel in at least one target area, including: in response to determining that the grayscale value of the at least one target pixel is less than or equal to the first threshold, adjusting the grayscale value of the at least one target pixel to the first threshold. In response to determining that the grayscale value of the at least one target pixel is greater than the first threshold and less than or equal to the second threshold, adjusting the grayscale value of the at least one target pixel to the first target value, the first target value being determined based on the first threshold and the second threshold. In response to determining that the grayscale value of the at least one target pixel is greater than the second threshold, maintaining the grayscale value of the at least one target pixel unchanged. Wherein, the first threshold and the second threshold are determined based on the preset mapping relationship.

[0107] According to an embodiment of the present disclosure, in response to determining that the grayscale value of at least one target pixel is less than or equal to a first threshold, the grayscale value of at least one target pixel is adjusted to the first threshold, thereby reducing the contrast of the brightness at the same position of the disparity map by increasing the brightness of the low grayscale, thereby reducing ghosting when the display device displays the disparity map.

[0108] In response to determining that the grayscale value of at least one target pixel is greater than a first threshold and less than or equal to a second threshold, the grayscale value of at least one target pixel is adjusted to a first target value, where the first target value is determined based on the first threshold and the second threshold, so that the grayscale value of at least one target pixel is adjusted by the first target value determined by the first threshold and the second threshold, so that the adjusted grayscale value greater than the first threshold and less than or equal to the second threshold can change slowly according to a certain rule, thereby achieving a slower reduction in the contrast of the brightness at the same position of the disparity map, thereby reducing ghosting when the display device displays the disparity map.

[0109] FIG2 is a mapping relationship curve according to an embodiment of the present disclosure.

[0110] The abscissa of the coordinate system shown in FIG2 represents the pixel grayscale value of at least one target pixel in the target area, and the ordinate represents the adjusted pixel grayscale value.

[0111] As shown in Figure 2, when the pixel grayscale value of at least one target pixel in the target area is not adjusted, the pixel grayscale value of at least one target pixel in the target area is kept unchanged. When it is determined that the grayscale value of at least one target pixel is less than or equal to the first threshold, the grayscale value of at least one target pixel can be adjusted to the first threshold N1. In the example of Figure 2, N1 is 0. For example, it can also be set to a value between 5 and 10, which is not limited here. When it is determined that the grayscale value of at least one target pixel is greater than the first threshold 0 and less than or equal to the second threshold N2, and the pixel grayscale value of at least one target pixel in the target area is adjusted, the change in the pixel grayscale value of at least one target pixel in the target area can conform to the change law of curve 1, curve 2 or curve 3.

[0112] According to an embodiment of the present disclosure, for example, when the grayscale value of at least one target pixel in the target area is adjusted according to Curve 1 in FIG. 4 using the preset mapping relationship in Table 1, the highest grayscale value of the multi-view image can be 255, the lowest grayscale value can be 0, and the average grayscale value can be 125. By looking up Table 1, N1 is obtained as 20 and N2 as 90. Then, the grayscale value of the pixel in the target area equal to 0 can be adjusted to N1 "20", and the grayscale values ​​of the pixels in the target area greater than 0 and less than or equal to 90 can be adjusted according to the variation pattern of Curve 1.

[0113] According to an embodiment of the present disclosure, when it is determined that the grayscale value of at least one target pixel is greater than a first threshold value and less than or equal to a second threshold value, and the grayscale value of the pixel in the target area is adjusted according to Curve 1, the first target value can be calculated according to Formula (1) corresponding to Curve 1. Y1=(N2-N1) / N2*X+N1 (1)

[0114] Where X represents the grayscale value of the pixels in the target area.

[0115] According to an embodiment of the present disclosure, when the grayscale value of the pixel in the target area is adjusted according to Curve 2, the first target value can be calculated according to Formula (2) corresponding to Curve 2. Y1 = N1*N2*N2 / ((N1-N2)*X+N2*N2) (2)

[0116] According to an embodiment of the present disclosure, when the grayscale values ​​of pixels in the target area are adjusted according to Curve 3, the first target value can be calculated according to Formula (3) corresponding to Curve 3.

[0117] Here, c represents a preset constant.

[0118] According to an embodiment of the present disclosure, when it is determined that the grayscale value of at least one target pixel is greater than a first threshold and less than or equal to a second threshold, the pixel grayscale value of at least one target pixel in the target area is adjusted. The specific adjustment formula can be configured according to actual business needs and is not limited here.

[0119] According to an embodiment of the present disclosure, the adjustment unit adjusts the pixel grayscale value of at least one target pixel in at least one target area, including: in response to determining that the grayscale value of the at least one target pixel is greater than or equal to a third threshold, adjusting the grayscale value of the at least one target pixel to the third threshold. In response to determining that the grayscale value of the at least one target pixel is less than the third threshold and greater than or equal to a fourth threshold, adjusting the grayscale value of the at least one target pixel to a second target value, the second target value being determined based on the third threshold and the fourth threshold. In response to determining that the grayscale value of the at least one target pixel is less than the fourth threshold, maintaining the grayscale value of the at least one target pixel unchanged. The third threshold and the fourth threshold are determined based on a preset mapping relationship.

[0120] According to an embodiment of the present disclosure, in response to determining that the grayscale value of at least one target pixel is greater than or equal to a third threshold, the grayscale value of at least one target pixel is adjusted to the third threshold, thereby reducing the contrast of the brightness at the same position of the disparity map by reducing the brightness of the higher grayscale, thereby reducing ghosting when the display device displays the disparity map.

[0121] In response to determining that the grayscale value of at least one target pixel is less than a third threshold and greater than or equal to a fourth threshold, the grayscale value of at least one target pixel is adjusted to a second target value, where the second target value is determined based on the third threshold and the fourth threshold, so that the grayscale value of at least one target pixel is adjusted by the second target value determined by the third threshold and the fourth threshold, so that the adjusted grayscale value that is less than the third threshold and greater than or equal to the fourth threshold can change slowly according to a certain rule, thereby achieving a slower reduction in the contrast of the brightness at the same position of the disparity map, thereby reducing ghosting when the display device displays the disparity map.

[0122] According to an embodiment of the present disclosure, when the third threshold and the fourth threshold are used to adjust the grayscale value of the pixel in the target area, the grayscale value of the pixel in the target area can be adjusted according to an adjustment method similar to the change rule in FIG. 2 .

[0123] According to an embodiment of the present disclosure, when it is determined that the grayscale value of at least one target pixel is less than the third threshold and greater than or equal to the fourth threshold, the grayscale value of the pixel in the target area is adjusted using the third threshold and the fourth threshold. The second target value can be calculated according to formula (4): Y2 = N3 + (X - N3) / (255 - N3) * (N4 - N3) (4)

[0124] According to an embodiment of the present disclosure, when the third threshold and the fourth threshold are used to adjust the grayscale value of the pixel in the target area, the second target value can also be calculated according to formula (5).

[0125] According to an embodiment of the present disclosure, when the third threshold and the fourth threshold are used to adjust the grayscale value of the pixel in the target area, the second target value can also be calculated according to formula (6).

[0126] According to an embodiment of the present disclosure, when it is determined that the grayscale value of at least one target pixel is less than a third threshold and greater than or equal to a fourth threshold, the third threshold and the fourth threshold are used to adjust the grayscale value of the pixel in the target area. The specific adjustment formula can be configured according to actual business needs and is not limited here.

[0127] According to an embodiment of the present disclosure, after adjusting the multi-view image using the first threshold and the second threshold, the multi-view image can be further adjusted using the third threshold and the fourth threshold, thereby achieving both increasing the brightness of low grayscales and reducing the brightness of high grayscales, thereby better reducing ghosting when the display device displays the disparity map.

[0128] According to the embodiments of the present disclosure, formulas (1) to (6) for adjusting multi-viewpoint images can be selected according to actual business conditions and are not limited here.

[0129] According to an embodiment of the present disclosure, the multi-viewpoint image includes a first viewpoint image and a second viewpoint image that are adjacent to each other. The first viewpoint image includes N pixels, and the second viewpoint image includes N pixels, where N is an integer greater than 1.

[0130] According to an embodiment of the present disclosure, the image processing apparatus 100 shown in FIG1 may further include a first determining unit. The first determining unit may be configured to determine, based on a difference between the grayscale values ​​of N pixels of the first viewpoint image and the grayscale values ​​of N pixels of the second viewpoint image, a first region in the first viewpoint image and a second region corresponding to the first region in the second viewpoint image, and use the first region and the second region as at least one target region.

[0131] According to an embodiment of the present disclosure, the first determining unit may determine, based on the difference between the grayscale values ​​of N pixels in the first viewpoint image and the grayscale values ​​of N pixels in the second viewpoint image, a first region in the first viewpoint image and a second region in the second viewpoint image corresponding to the first region, which may include: determining the difference between the grayscale values ​​of N pixels in the first viewpoint image and the grayscale values ​​of N pixels in the second viewpoint image to obtain N difference values. Then, based on the N difference values, determining the first region in the first viewpoint image and the second region in the second viewpoint image corresponding to the first region. The first region and the second region each include n adjacent pixels, the difference between the pixel values ​​of the n pixels in the first region and the pixel values ​​of the n pixels in the second region are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0132] According to an embodiment of the present disclosure, N difference values ​​are obtained by determining the difference between the grayscale values ​​of N pixels in a first viewpoint image and the grayscale values ​​of N pixels in a second viewpoint image. Based on the N difference values, a first region in the first viewpoint image and a second region corresponding to the first region in the second viewpoint image are determined. This allows for more precise determination of the locations of the first and second regions where ghosting occurs, allowing subsequent adjustments to be made only to the first and second regions where ghosting occurs, improving adjustment efficiency.

[0133] According to the embodiments of the present disclosure, since the ghosting area can only be observed by the human eye when it meets a certain area size, the first area and the second area both include n adjacent pixels, and the difference between the pixel values ​​of the n pixels in the first area and the pixel values ​​of the n pixels in the second area is greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N, which can ensure that the first area and the second area are ghosting areas that can be observed by the human eye, making the first area and the second area more accurate.

[0134] According to the embodiments of the present disclosure, both the predetermined difference threshold and the predetermined pixel count threshold can be configured based on actual business needs and are not limited here. For example, the predetermined pixel count threshold can be 5% to 10% of the total number of pixels in the multi-view image, and the predetermined difference threshold can be 10, 20, or 30, etc.

[0135] FIG. 3 illustrates a process of adjusting a multi-view image by an image processing apparatus when the multi-view image includes two adjacent view images according to an embodiment of the present disclosure.

[0136] As shown in FIG. 3 , the multi-viewpoint image includes adjacent first viewpoint image A1 and second viewpoint image A2 .

[0137] By traversing all pixels in the first and second viewpoint images A1 and A2, a matrix of absolute grayscale differences between pixels at the same locations in the second viewpoint image A2 and its left viewpoint image A1 is obtained. Locations with large values ​​in the absolute grayscale difference matrix (a threshold can be set) are then extracted. Furthermore, regions with large areas where the two matrices are connected (a threshold for the number of connected pixels can be set) are extracted separately, resulting in a first region 310 in the first viewpoint image A1 and a second region 320 in the second viewpoint image A2.

[0138] The highest grayscale value, the lowest grayscale value, and the average grayscale value of the first region 310 and the second region 320 can then be calculated. By looking up Table 1, N1, N2, N3, and N4 are obtained. Based on N1, N2, N3, and N4, the grayscale values ​​of the pixels in the first region 310 and the second region 320 can be first adjusted using Formulas (1) and (4), obtaining the adjusted first viewpoint image A1_1 and the adjusted second viewpoint image A2_1.

[0139] According to an embodiment of the present disclosure, the multi-viewpoint image may further include M viewpoint images, where M is an integer greater than 2. The M viewpoint images may each include N pixels.

[0140] According to an embodiment of the present disclosure, the image processing apparatus 100 shown in FIG1 may further include a second determining unit. The second determining unit may be configured to determine, based on the difference between the grayscale values ​​of N pixels in the m-th viewpoint image and the grayscale values ​​of N pixels in the m+1-th viewpoint image, an m-th region in the m-th viewpoint image and an m+1-th region corresponding to the m-th region in the m+1-th viewpoint image, and use the m-th region and the m+1-th region as at least one target region to obtain an adjusted m-th viewpoint image and an adjusted m+1-th viewpoint image. m is greater than or equal to 1 and less than or equal to M-2.

[0141] According to the difference between the grayscale values ​​of N pixels of the adjusted m+1th viewpoint image and the grayscale values ​​of N pixels of the m+2th viewpoint image, the adjusted m+1th region in the adjusted m+1th viewpoint image and the m+2th region corresponding to the adjusted m+1th region in the m+2th viewpoint image are determined, and the adjusted m+1th region and the m+2th region are used as at least one target region.

[0142] According to an embodiment of the present disclosure, the second determining unit determines the mth region in the mth viewpoint image and the m+1th region corresponding to the mth region in the m+1th viewpoint image based on the difference between the grayscale values ​​of N pixels in the mth viewpoint image and the grayscale values ​​of N pixels in the m+1th viewpoint image. This may include: determining the difference between the grayscale values ​​of N pixels in the mth viewpoint image and the grayscale values ​​of N pixels in the m+1th viewpoint image to obtain N difference values. Then, based on the N difference values, determining the mth region in the mth viewpoint image and the m+1th region corresponding to the mth region in the m+1th viewpoint image, wherein both the mth region and the m+1th region include n adjacent pixels, the difference between the pixel values ​​of n pixels in the mth region and the pixel values ​​of n pixels in the m+1th region is greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0143] According to the embodiments of the present disclosure, M can be configured according to actual business needs and is not limited here. For example, M can be 3, 6, or 9.

[0144] According to an embodiment of the present disclosure, N difference values ​​are obtained by determining the difference between the grayscale values ​​of N pixels in the m-th viewpoint image and the grayscale values ​​of N pixels in the m+1-th viewpoint image. Based on these N difference values, the m-th region in the m-th viewpoint image and the m+1-th region corresponding to the m-th region in the m+1-th viewpoint image are then determined. This allows for more precise determination of the locations of the m-th and m+1-th regions where ghosting occurs. Subsequently, adjustments are only made to the m-th and m+1-th regions where ghosting occurs, improving adjustment efficiency.

[0145] According to the embodiments of the present disclosure, since the ghosting area can only be sensed by the human eye when it meets a certain area size, the mth area and the m+1th area both include n adjacent pixels, and the difference between the pixel value of n pixels in the mth area and the pixel value of n pixels in the m+1th area is greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N, which can ensure that the mth area and the m+1th area are ghosting areas that can be observed by the human eye, making the mth area and the m+1th area more accurate.

[0146] FIG. 4 illustrates a process of adjusting a multi-view image by an image processing apparatus when the multi-view image includes at least three view images according to an embodiment of the present disclosure.

[0147] According to an embodiment of the present disclosure, the multi-viewpoint image shown in Fig. 4 may include 9 viewpoint images, including a 3rd viewpoint image A3, a 4th viewpoint image A4, and a 5th viewpoint image A5.

[0148] As shown in Figure 4, the steps of adjusting the 9 viewpoint images through the second determination unit are: traversing all pixels of the multi-viewpoint images A1-A9, obtaining a matrix of the absolute grayscale difference values ​​of pixels at the same position of the target viewpoint image, such as A2, relative to its left viewpoint image, such as A1 (if there is no left or right view, only one difference matrix is ​​obtained, for example, A1 has only one adjacent viewpoint image A2, and A9 has only one adjacent viewpoint image A8), and then extracting the positions with larger values ​​in the difference absolute value matrix (a threshold can be set), and then extracting the larger areas where the two matrices are concentrated and connected together (a threshold for the number of connected pixels can be set) to obtain area a1 in A1 and area a2 in A2.

[0149] At this point, the grayscale values ​​of the pixels in regions a1 and a2 are calculated as described above (i.e., grayscale values ​​that are too high are lowered and grayscale values ​​that are too low are raised), resulting in adjusted A1 and adjusted A2. Next, the pixel difference between adjusted A2 and the original A3 is calculated to obtain target region a2′ in A2 and target region a3 in A3. Note that target region a2′ is independent of target region a2. Next, the grayscale value adjustment operation is performed on target region a2′ and target region a3 in A3, resulting in further adjusted A2 and adjusted A3. The pixel difference between adjusted A3 and the original A4 is then calculated.

[0150] As shown in Figure 4, the adjusted A3 is "A3_1". The second determination unit calculates the pixel difference between A3_1 and the original A4 to obtain the target area 4301 in A3_1 and the target area 440 in A4. Then the pixel grayscale value of the target area 4301 and the target area 440 are first adjusted to obtain the re-adjusted A3 "A3_2" and the adjusted A4 "A4_1". Then the pixel difference between A4_1 and A5 is calculated to obtain the target area 450 in A4_1 and the target area 4401 in A4_1. The pixel grayscale value of the target area 450 and the target area 4401 are second adjusted to obtain the re-adjusted A4_1 "A4_2" and the adjusted A5 "A5_1". Then the pixel difference between A5_1 and the original A6 is calculated, and so on.

[0151] FIG. 5 is an image displayed by a display device according to an embodiment of the present disclosure.

[0152] First, calculate the highest grayscale value, lowest grayscale value, and average grayscale value for the adjacent viewpoint images corresponding to integrated image A6 in Figure 5. Then, based on the highest grayscale value, lowest grayscale value, and average grayscale value, look up Table 1 and obtain N1 as 30 and N2 as 127. Calculate the pixel difference between the adjacent viewpoint images corresponding to integrated image A6 to obtain target area 560. Use formula (1) to adjust the adjacent viewpoint images corresponding to integrated image A6 to obtain an adjusted viewpoint image, and then obtain integrated image A7. After adjusting target area 560, adjusted target area 570 is obtained.

[0153] As can be seen from FIG. 5 , the ghosting of the target area 570 is significantly smaller than that of the target area 560 , which proves that the image processing device of the present disclosure can accurately and quickly adjust the target area 560 and can effectively reduce the ghosting.

[0154] According to an embodiment of the present disclosure, the output unit obtains a processed image for displaying on a display device based on the adjusted multiple viewpoint images, including: splicing the adjusted multiple viewpoint images to obtain a processed image for displaying on a display device.

[0155] The display device provided by the embodiment of the present disclosure may include the image processing device and the display device provided by the embodiment of the present disclosure. The display device can be used to display the output image from the image processing device.

[0156] FIG6 is a flowchart of an image processing method according to an embodiment of the present disclosure.

[0157] As shown in FIG. 6 , the image processing method of this embodiment may include operations S610 to S630 .

[0158] In operation S610 , multi-viewpoint images are acquired.

[0159] In operation S620, the grayscale value of at least one target pixel in at least one target region of the multi-view image is adjusted according to a preset mapping relationship to obtain an adjusted multi-view image. The preset mapping relationship is obtained by measuring the ghosting sensitivity of the display device.

[0160] In operation S630, a processed image for display on a display device is obtained based on the adjusted multi-viewpoint image, and the processed image is output.

[0161] It should be noted that, unless it is explicitly stated that there is a sequence of execution between different operations shown in the flowchart in the embodiments of the present disclosure, or there is a sequence of execution between different operations in technical implementation, otherwise, the execution order between multiple operations may not be prioritized, and multiple operations may also be executed simultaneously.

[0162] It should also be noted that the image processing method in the embodiment of the present disclosure corresponds to the image processing device in the embodiment of the present disclosure, and will not be described in detail here.

[0163] According to an embodiment of the present disclosure, the multi-viewpoint image includes a first viewpoint image and a second viewpoint image that are adjacent to each other. The first viewpoint image includes N pixels, and the second viewpoint image includes N pixels, where N is an integer greater than 1.

[0164] The image processing method further includes determining, based on a difference between grayscale values ​​of N pixels in the first viewpoint image and grayscale values ​​of N pixels in the second viewpoint image, a first region in the first viewpoint image and a second region in the second viewpoint image corresponding to the first region, and using the first region and the second region as at least one target region.

[0165] According to an embodiment of the present disclosure, determining a first area in the first viewpoint image and a second area in the second viewpoint image corresponding to the first area based on the difference between the grayscale values ​​of N pixels of the first viewpoint image and the grayscale values ​​of N pixels of the second viewpoint image includes: determining the difference between the grayscale values ​​of N pixels of the first viewpoint image and the grayscale values ​​of N pixels of the second viewpoint image, and obtaining N difference values.

[0166] Based on N difference values, a first area in the first viewpoint image and a second area corresponding to the first area in the second viewpoint image are determined, wherein the first area and the second area both include n adjacent pixels, and the differences between the pixel values ​​of the n pixels in the first area and the pixel values ​​of the n pixels in the second area are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0167] According to an embodiment of the present disclosure, the multi-viewpoint image includes M viewpoint images, where M is an integer greater than 2; each of the M viewpoint images includes N pixels.

[0168] The image processing method also includes: determining the mth region in the mth viewpoint image and the m+1th region corresponding to the mth region in the m+1 viewpoint image based on the difference between the grayscale values ​​of N pixels of the mth viewpoint image and the grayscale values ​​of N pixels of the m+1th viewpoint image, and using the mth region and the m+1th region as at least one target region to obtain an adjusted mth viewpoint image and an adjusted m+1th viewpoint image, where m is greater than or equal to 1 and less than or equal to M-2.

[0169] According to the difference between the grayscale values ​​of N pixels of the adjusted m+1th viewpoint image and the grayscale values ​​of N pixels of the m+2th viewpoint image, the adjusted m+1th region in the adjusted m+1th viewpoint image and the m+2th region corresponding to the adjusted m+1th region in the m+2th viewpoint image are determined, and the adjusted m+1th region and the m+2th region are used as at least one target region.

[0170] According to an embodiment of the present disclosure, determining an mth region in an mth viewpoint image and an m+1th region corresponding to the mth region in an m+1th viewpoint image based on the difference between the grayscale values ​​of N pixels in an mth viewpoint image and the grayscale values ​​of N pixels in an m+1th viewpoint image includes: determining the difference between the grayscale values ​​of N pixels in the mth viewpoint image and the grayscale values ​​of N pixels in the m+1th viewpoint image to obtain N difference values. Based on the N difference values, determining the mth region in the mth viewpoint image and the m+1th region corresponding to the mth region in an m+1th viewpoint image. The mth region and the m+1th region each include n adjacent pixels, the difference between the pixel values ​​of n pixels in the mth region and the pixel values ​​of n pixels in the m+1th region are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

[0171] According to an embodiment of the present disclosure, adjusting the pixel grayscale value of at least one target pixel in at least one target area includes: in response to determining that the grayscale value of the at least one target pixel is less than or equal to a first threshold, adjusting the grayscale value of the at least one target pixel to the first threshold. In response to determining that the grayscale value of the at least one target pixel is greater than the first threshold and less than or equal to a second threshold, adjusting the grayscale value of the at least one target pixel to a first target value, where the first target value is determined based on the first threshold and the second threshold. In response to determining that the grayscale value of the at least one target pixel is greater than the second threshold, maintaining the grayscale value of the at least one target pixel unchanged. Wherein, the first threshold and the second threshold are determined based on a preset mapping relationship.

[0172] According to an embodiment of the present disclosure, adjusting the pixel grayscale value of at least one target pixel in at least one target area further includes: in response to determining that the grayscale value of the at least one target pixel is greater than or equal to a third threshold, adjusting the grayscale value of the at least one target pixel to the third threshold. In response to determining that the grayscale value of the at least one target pixel is less than the third threshold and greater than or equal to a fourth threshold, adjusting the grayscale value of the at least one target pixel to a second target value, the second target value being determined based on the third threshold and the fourth threshold. In response to determining that the grayscale value of the at least one target pixel is less than the fourth threshold, maintaining the grayscale value of the at least one target pixel unchanged. The third threshold and the fourth threshold are determined based on a preset mapping relationship.

[0173] According to an embodiment of the present disclosure, obtaining a processed image for display on a display device based on the adjusted multiple viewpoint images includes: splicing the adjusted multiple viewpoint images to obtain a processed image for display on the display device.

[0174] According to an embodiment of the present disclosure, the preset mapping relationship includes a mapping relationship between the grayscale values ​​of pixels in the target area and multiple thresholds, the grayscale values ​​of the pixels include the highest grayscale value, the lowest grayscale value and the average grayscale value of the pixels in the target area; the multiple thresholds include a first threshold, a second threshold, a third threshold and a fourth threshold.

[0175] FIG7 is a block diagram of an electronic device suitable for implementing an image processing method according to an embodiment of the present disclosure.

[0176] As shown in Figure 7, the electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. The processor 701 may, for example, include a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include an onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0177] Various programs and data required for the operation of the electronic device 700 are stored in the RAM 703. The processor 701, ROM 702, and RAM 703 are connected to each other via a bus 704. The processor 701 executes the various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 702 and / or RAM 703. It should be noted that the programs may also be stored in one or more memories other than the ROM 702 and RAM 703. The processor 701 may also execute the various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in one or more memories.

[0178] According to an embodiment of the present disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to the bus 704. The electronic device 700 may further include one or more of the following components connected to the I / O interface 705: an input portion 706 including a keyboard, a mouse, etc.; an output portion 707 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage portion 708 including a hard disk; and a communication portion 709 including a network interface card such as a LAN card or a modem. The communication portion 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed in the drive 710 as needed, so that a computer program read therefrom can be installed into the storage portion 708 as needed.

[0179] The present disclosure also provides a non-transitory computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0180] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 702 and / or RAM 703 described above and / or one or more memories other than ROM 702 and RAM 703.

[0181] The embodiments of the present disclosure also include a computer program product, which includes a computer program containing program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the image processing method provided by the embodiments of the present disclosure.

[0182] The computer program executes the above functions defined in the system / device of the embodiment of the present disclosure when the processor 701 executes the computer program. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0183] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 709, and / or installed from a removable medium 711. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0184] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709, and / or installed from a removable medium 711. When the computer program is executed by the processor 701, the above-described functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the systems, devices, means, modules, units, etc. described above can be implemented by computer program modules.

[0185] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0186] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0187] Those skilled in the art will appreciate that the features described in the various embodiments and / or claims of this disclosure may be combined and / or coupled in various ways, even if such combinations and / or couplings are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure may be combined and / or coupled in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or couplings are intended to fall within the scope of this disclosure.

[0188] The embodiments of the present disclosure are described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be used in combination to advantage. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. An image processing device, comprising: An acquisition unit, used for acquiring multi-viewpoint images; an adjusting unit, configured to adjust the pixel grayscale value of at least one target pixel in at least one target area in the multi-view image according to a preset mapping relationship to obtain an adjusted multi-view image, wherein the preset mapping relationship is obtained by measuring the ghosting sensitivity of the display device; as well as An output unit is used to obtain a processed image for display by the display device according to the adjusted multi-viewpoint image, and output the processed image.

2. The device according to claim 1, wherein: The multi-viewpoint image includes a first viewpoint image and a second viewpoint image that are adjacent to each other, the first viewpoint image includes N pixels, the second viewpoint image includes N pixels, and N is an integer greater than 1; The device also includes a first determination unit for determining a first area in the first viewpoint image and a second area in the second viewpoint image corresponding to the first area based on a difference between grayscale values ​​of N pixels in the first viewpoint image and grayscale values ​​of N pixels in the second viewpoint image, and using the first area and the second area as the at least one target area.

3. The device according to claim 2, wherein: The first determining unit determines, according to the difference between the grayscale values ​​of the N pixels of the first viewpoint image and the grayscale values ​​of the N pixels of the second viewpoint image, a first area in the first viewpoint image and a second area in the second viewpoint image corresponding to the first area, including: Determine the difference between the grayscale values ​​of N pixels of the first viewpoint image and the grayscale values ​​of N pixels of the second viewpoint image to obtain N difference values; and Based on the N difference values, determine a first area in the first viewpoint image and a second area in the second viewpoint image corresponding to the first area, wherein the first area and the second area both include n adjacent pixels, and the differences between the pixel values ​​of the n pixels in the first area and the pixel values ​​of the n pixels in the second area are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

4. The device according to claim 1, wherein: The multi-viewpoint image includes M viewpoint images, where M is an integer greater than 2; each of the M viewpoint images includes N pixels; The device also includes a second determining unit, which is used to Determine, according to a difference between grayscale values ​​of N pixels of an m-th viewpoint image and grayscale values ​​of N pixels of an m+1-th viewpoint image, an m-th region in the m-th viewpoint image and an m+1-th region corresponding to the m-th region in the m+1-th viewpoint image, and use the m-th region and the m+1-th region as the at least one target region, so as to obtain an adjusted m-th viewpoint image and an adjusted m+1-th viewpoint image, where m is greater than or equal to 1 and less than or equal to M-2; as well as According to the difference between the grayscale values ​​of N pixels of the adjusted m+1th viewpoint image and the grayscale values ​​of N pixels of the m+2th viewpoint image, the adjusted m+1th region in the adjusted m+1th viewpoint image and the m+2th region corresponding to the adjusted m+1th region in the m+2th viewpoint image are determined, and the adjusted m+1th region and the m+2th region are used as the at least one target region.

5. The device according to claim 4, wherein: The second determining unit determines an mth region in the mth viewpoint image and an m+1th region corresponding to the mth region in the m+1 viewpoint image according to a difference between grayscale values ​​of N pixels in the mth viewpoint image and grayscale values ​​of N pixels in the m+1th viewpoint image, including: Determine the difference between the grayscale values ​​of the N pixels of the m-th viewpoint image and the grayscale values ​​of the N pixels of the m+1-th viewpoint image to obtain N difference values; and Based on the N difference values, determine the mth region in the mth viewpoint image and the m+1th region corresponding to the mth region in the m+1th viewpoint image, wherein the mth region and the m+1th region both include n adjacent pixels, and the differences between the pixel values ​​of n pixels in the mth region and the pixel values ​​of n pixels in the m+1th region are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

6. The device according to any one of claims 1 to 5, wherein: The adjusting unit adjusting the pixel grayscale value of at least one target pixel in the at least one target area includes: In response to determining that the grayscale value of the at least one target pixel is less than or equal to a first threshold, adjusting the grayscale value of the at least one target pixel to the first threshold; In response to determining that the grayscale value of the at least one target pixel is greater than a first threshold and less than or equal to a second threshold, adjusting the grayscale value of the at least one target pixel to a first target value, wherein the first target value is determined according to the first threshold and the second threshold; and In response to determining that the grayscale value of the at least one target pixel is greater than the second threshold, maintaining the at least one target pixel The grayscale value of the target pixel remains unchanged; The first threshold and the second threshold are determined according to the preset mapping relationship.

7. The device according to any one of claims 1 to 6, wherein: The adjusting unit adjusting the pixel grayscale value of at least one target pixel in the at least one target area includes: In response to determining that the grayscale value of the at least one target pixel is greater than or equal to a third threshold, adjusting the grayscale value of the at least one target pixel to the third threshold; In response to determining that the grayscale value of the at least one target pixel is less than the third threshold and greater than or equal to a fourth threshold, adjusting the grayscale value of the at least one target pixel to a second target value, wherein the second target value is determined according to the third threshold and the fourth threshold; and In response to determining that the grayscale value of the at least one target pixel is less than the fourth threshold, maintaining the grayscale value of the at least one target pixel unchanged; The third threshold and the fourth threshold are determined according to the preset mapping relationship.

8. The device according to any one of claims 1 to 7, wherein: The output unit obtains a processed image for displaying on a display device according to the adjusted multiple viewpoint images, comprising: The adjusted multi-view images are stitched together to obtain a processed image for display on a display device.

9. The device according to any one of claims 1 to 8, wherein: The preset mapping relationship includes a mapping relationship between the grayscale values ​​of pixels in the target area and multiple thresholds, the grayscale values ​​of the pixels include the highest grayscale value, the lowest grayscale value and the average grayscale value of the pixels in the target area; the multiple thresholds include a first threshold, a second threshold, a third threshold and the fourth threshold.

10. A display device, comprising: The image processing device according to any one of claims 1 to 9; as well as A display device is used to display the output image from the image processing device.

11. An image processing method, comprising: Acquire multi-view images; According to the preset mapping relationship, at least one target in at least one target area in the multi-view image is adjusted. The pixel grayscale value of the pixel is obtained to obtain the adjusted multi-view image, wherein the preset mapping relationship is obtained by measuring the ghosting sensitivity of the display device; Obtaining a processed image for display by the display device according to the adjusted multi-viewpoint image; and The processed image is output.

12. The method according to claim 11, wherein: The multi-viewpoint image includes a first viewpoint image and a second viewpoint image that are adjacent to each other, the first viewpoint image includes N pixels, the second viewpoint image includes N pixels, and N is an integer greater than 1; The method further comprises: determining a first area in the first viewpoint image and a second area in the second viewpoint image corresponding to the first area according to a difference between grayscale values ​​of N pixels in the first viewpoint image and grayscale values ​​of N pixels in the second viewpoint image; and The first area and the second area are used as the at least one target area.

13. The method according to claim 12, wherein: The determining, according to the difference between the grayscale values ​​of the N pixels of the first viewpoint image and the grayscale values ​​of the N pixels of the second viewpoint image, a first area in the first viewpoint image and a second area in the second viewpoint image corresponding to the first area comprises: Determine the difference between the grayscale values ​​of N pixels of the first viewpoint image and the grayscale values ​​of N pixels of the second viewpoint image to obtain N difference values; and Based on the N difference values, determine a first area in the first viewpoint image and a second area in the second viewpoint image corresponding to the first area, wherein the first area and the second area both include n adjacent pixels, and the differences between the pixel values ​​of the n pixels in the first area and the pixel values ​​of the n pixels in the second area are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

14. The method according to claim 11, wherein: The multi-viewpoint image includes M viewpoint images, where M is an integer greater than 2; each of the M viewpoint images includes N pixels; The method further comprises: According to the difference between the grayscale values ​​of N pixels of the m-th viewpoint image and the grayscale values ​​of N pixels of the m+1-th viewpoint image, an m-th region in the m-th viewpoint image and an m+1-th region corresponding to the m-th region in the m+1-th viewpoint image are determined, and the m-th region and the m+1-th region are used as the at least one target areas, so as to obtain an adjusted m-th viewpoint image and an adjusted m+1-th viewpoint image, where m is greater than or equal to 1 and less than or equal to M-2; and According to the difference between the grayscale values ​​of N pixels of the adjusted m+1th viewpoint image and the grayscale values ​​of N pixels of the m+2th viewpoint image, the adjusted m+1th region in the adjusted m+1th viewpoint image and the m+2th region corresponding to the adjusted m+1th region in the m+2th viewpoint image are determined, and the adjusted m+1th region and the m+2th region are used as the at least one target region.

15. The method according to claim 14, wherein: The determining, according to the difference between the grayscale values ​​of N pixels of the m-th viewpoint image and the grayscale values ​​of N pixels of the m+1-th viewpoint image, the m-th region in the m-th viewpoint image and the m+1-th region corresponding to the m-th region in the m+1-th viewpoint image comprises: Determine the difference between the grayscale values ​​of the N pixels of the m-th viewpoint image and the grayscale values ​​of the N pixels of the m+1-th viewpoint image to obtain N difference values; and Based on the N difference values, determine the mth region in the mth viewpoint image and the m+1th region corresponding to the mth region in the m+1th viewpoint image, wherein the mth region and the m+1th region both include n adjacent pixels, and the differences between the pixel values ​​of n pixels in the mth region and the pixel values ​​of n pixels in the m+1th region are both greater than or equal to a predetermined difference threshold, and n is greater than or equal to a predetermined pixel number threshold and less than N.

16. The method according to any one of claims 11 to 15, wherein: The adjusting the pixel grayscale value of at least one target pixel in the at least one target area comprises: In response to determining that the grayscale value of the at least one target pixel is less than or equal to a first threshold, adjusting the grayscale value of the at least one target pixel to the first threshold; In response to determining that the grayscale value of the at least one target pixel is greater than a first threshold and less than or equal to a second threshold, adjusting the grayscale value of the at least one target pixel to a first target value, wherein the first target value is determined according to the first threshold and the second threshold; and In response to determining that the grayscale value of the at least one target pixel is greater than the second threshold, maintaining the grayscale value of the at least one target pixel unchanged; The first threshold and the second threshold are determined according to the preset mapping relationship.

17. The method according to claim 16, wherein: The step of adjusting the pixel grayscale value of at least one target pixel in the at least one target area further comprises: In response to determining that the grayscale value of the at least one target pixel is greater than or equal to a third threshold, adjusting the grayscale value of the at least one target pixel to the third threshold; In response to determining that the grayscale value of the at least one target pixel is less than the third threshold and greater than or equal to a fourth threshold, adjusting the grayscale value of the at least one target pixel to a second target value, wherein the second target value is determined according to the third threshold and the fourth threshold; and In response to determining that the grayscale value of the at least one target pixel is less than the fourth threshold, maintaining the grayscale value of the at least one target pixel unchanged; The third threshold and the fourth threshold are determined according to the preset mapping relationship.

18. The method according to any one of claims 11 to 17, wherein: The step of obtaining a processed image for displaying on a display device according to the adjusted multiple viewpoint images comprises: The adjusted multi-view images are stitched together to obtain a processed image for display on a display device.

19. The method according to any one of claims 11 to 18, wherein: The preset mapping relationship includes a mapping relationship between the grayscale values ​​of pixels in the target area and multiple thresholds, the grayscale values ​​of the pixels include the highest grayscale value, the lowest grayscale value and the average grayscale value of the pixels in the target area; the multiple thresholds include a first threshold, a second threshold, a third threshold and the fourth threshold.

20. An electronic device, comprising: at least one processor; as well as A memory storing instructions executable by the processor, wherein when the instructions are executed by the processor, the processor is caused to perform the method according to any one of claims 11 to 19.

21. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 11 to 19.

22. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 11 to 19.

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