Image crosstalk compensation method, device, electronic device and storage medium

Abstract

The embodiment of the present application provides an image crosstalk compensation method, device, electronic device and storage medium, the method comprising determining a central block and a plurality of peripheral blocks around the central block in the area to be processed according to each grid unit in the area to be processed, determining a crosstalk compensation value of the area to be processed according to the white channel value of the central block and each peripheral block, and determining a compensation threshold of the area to be processed according to the non-white channel value of the central block and each peripheral block; and selectively using the crosstalk compensation value to compensate for the white channel value of the central block according to the comparison result of the crosstalk compensation value and the compensation threshold. The present application can effectively improve the imaging quality by determining the crosstalk compensation value and the compensation threshold of the area to be processed to dynamically perform image crosstalk compensation.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of image crosstalk compensation, and in particular to an image crosstalk compensation method, device, electronic device and storage medium applicable to an RGBW filter array. Background Art

[0002] With consumers' increasing demand for photo-taking effects and the booming CMOS industry, RGBW filter arrays have gradually replaced Bayer filter arrays and become the mainstream choice in the market.

[0003] Specifically, compared with the traditional Bayer filter array, the RGBW filter array introduces a W brightness channel. Since this channel filter can transmit a wider spectrum, it has a stronger ability to retain image details and has a better signal-to-noise ratio, especially in low-light imaging environments.

[0004] However, since the RGBW filter array changes from the traditional Bayer array's RGB three-channel color to RGBW four-channel color, the crosstalk between channels will be more serious than that of the Bayer array. At present, there are many studies on the crosstalk phenomenon in the Bayer filter array at home and abroad, but there are fewer studies on the RGBW filter array, and there is a lack of effective methods to reduce the crosstalk effect in the RGBW filter array. Summary of the invention

[0005] In view of this, the embodiments of the present application provide an image crosstalk compensation method, device, electronic device and storage medium suitable for an RGBW filter array. By determining the crosstalk compensation value and compensation threshold of the area to be processed, image crosstalk compensation processing is dynamically performed, which can improve the imaging quality after crosstalk compensation.

[0006] According to a first aspect of an embodiment of the present application, a method for compensating for image crosstalk is provided, comprising: determining a central block and a plurality of peripheral blocks surrounding the central block in the area to be processed according to each grid unit in the area to be processed; determining a crosstalk compensation value of the area to be processed according to white channel values ​​of the central block and the peripheral blocks, and determining a compensation threshold of the area to be processed according to non-white channel values ​​of the central block and the peripheral blocks; and selectively using the crosstalk compensation value to compensate for the white channel value of the central block according to a comparison result of the crosstalk compensation value and the compensation threshold.

[0007] Optionally, the area to be processed is obtained in the following manner: identifying a minimum filter group of an image capture device used to obtain the image to be processed, and determining each grid unit in the image to be processed based on the minimum filter group; determining a second number of grid units covered by a sliding window and a sliding step of the sliding window based on a first number of grid units covered by the minimum filter group; using the sliding window, repeatedly performing sliding processing that satisfies the sliding step on each grid unit of the image to be processed, and obtaining each area to be processed corresponding to each sliding processing.

[0008] Optionally, the minimum filter group and the sliding window are respectively square arrays composed of multiple grid units; the number of the second units is 2.25 times the number of the first units; and the sliding step size of the sliding window is 1 / 3 of the side length of the sliding window.

[0009] Optionally, determining a central block in the area to be processed and a plurality of peripheral blocks surrounding the central block according to each grid unit in the area to be processed includes: performing a nine-equal division process on the area to be processed according to each grid unit in the area to be processed to obtain nine sub-blocks of the area to be processed; determining a sub-block located at a center position of each sub-block as the central block, and determining eight sub-blocks surrounding the central block as peripheral blocks.

[0010] Optionally, the method also includes: identifying the channel color of each grid unit covered by the central block; if it is identified that the central block is covered with red or blue grid units, executing the method of determining the crosstalk compensation value of the area to be processed based on the white channel value of the central block and each surrounding block, and determining the compensation threshold of the area to be processed based on the non-white channel value of the central block and each surrounding block.

[0011] Optionally, determining the crosstalk compensation value of the area to be processed based on the white channel values ​​of the central block and each peripheral block includes: determining the white channel mean of the central block and each peripheral block based on the white channel values ​​of the central block and each peripheral block; determining each adjacent edge block in each peripheral block that is adjacent to each side of the central block, and determining the similarity weight value of each adjacent edge block based on the white channel mean of the central block and each adjacent edge block; determining the gradient weight value of the area to be processed based on the white channel mean of each peripheral block; and determining the crosstalk compensation value of the area to be processed based on the similarity weight value of each adjacent edge block and the gradient weight value of the area to be processed.

[0012] Optionally, determining the similarity weight value of each adjacent edge block based on the white channel mean value of the central block and each adjacent edge block includes: determining the compensation reference value of each adjacent edge block based on the difference between the white channel mean value of the central block and the white channel mean value of each adjacent edge block; determining the similarity weight value of each adjacent edge block based on the compensation reference value of each adjacent edge block and a given similarity weight coefficient.

[0013] Optionally, determining the gradient weight value of the area to be processed based on the white channel mean value of each surrounding block includes: determining the horizontal gradient value and the vertical gradient value of the area to be processed based on the position distribution of each surrounding block in the area to be processed and the white channel mean value of each surrounding block; determining the gradient weight value of the area to be processed based on the larger of the horizontal gradient value and the vertical gradient value and a given gradient weight coefficient.

[0014] Optionally, determining the crosstalk compensation value of the area to be processed based on the similarity weight values ​​of each adjacent edge block and the gradient weight value of the area to be processed includes: determining a first weighted value based on the similarity weight values ​​of each adjacent edge block, the gradient weight value of the area to be processed, and the compensation reference value of each adjacent edge block; determining a second weighted value based on the similarity weight values ​​of each adjacent edge block and the gradient weight value of the area to be processed; and determining the crosstalk compensation value of the area to be processed based on the first weighted value and the second weighted value.

[0015] Optionally, determining the compensation threshold of the area to be processed based on the non-white channel values ​​of the central block and each peripheral block includes: determining the non-white channel mean of the central block and each peripheral block based on the non-white channel values ​​of the central block and each peripheral block, wherein the non-white channel value includes one of a red channel value, a green channel value, and a blue channel value; determining the red pixel mean, the green pixel mean, and the blue pixel mean of the area to be processed based on the non-white channel mean of the central block and each peripheral block; determining the saturation of the area to be processed based on the maximum and minimum values ​​among the red pixel mean, the green pixel mean, and the blue pixel mean of the area to be processed; determining the compensation threshold of the area to be processed based on the saturation of the area to be processed and a given crosstalk maximum intensity value.

[0016] Optionally, determining the red pixel mean, green pixel mean, and blue pixel mean of the area to be processed according to the non-white channel mean of the central block and each peripheral block includes: determining each adjacent edge block adjacent to each side of the central block in each peripheral block, and determining each vertex block adjacent to each vertex of the central block in each peripheral block; determining the channel color of each grid unit in the central block, and if the central block contains a red grid unit, determining the red pixel mean of the area to be processed according to the non-white channel mean of the central block. The mean value is determined according to the non-white channel mean value of each adjacent block, and the mean value of the blue pixels in the area to be processed is determined according to the non-white channel mean value of each corner block; or if the central block contains blue grid units, the mean value of the blue pixels in the area to be processed is determined according to the non-white channel mean value of the central block, the mean value of the green pixels in the area to be processed is determined according to the non-white channel mean value of each adjacent block, and the mean value of the red pixels in the area to be processed is determined according to the non-white channel mean value of each corner block.

[0017] Optionally, based on the comparison result of the crosstalk compensation value with the compensation threshold, the crosstalk compensation value is selectively used to compensate the white channel value of the central block, including: comparing the crosstalk compensation value and the compensation threshold, if the crosstalk compensation value is less than or equal to the compensation threshold, determining the adaptive weight value of each white channel value according to the crosstalk compensation value and each white channel value in the central block, and determining the compensated channel value of each white channel value in the central block according to each white channel value in the central block, the adaptive weight value of each white channel value, and the crosstalk compensation value; if the crosstalk compensation value is greater than the compensation threshold, not performing compensation processing for each white channel value in the central block.

[0018] According to a second aspect of an embodiment of the present application, there is provided an image crosstalk compensation device, comprising: a block determination module, for determining a central block and a plurality of peripheral blocks surrounding the central block in the area to be processed according to each grid unit in the area to be processed; a calculation module, for determining a crosstalk compensation value of the area to be processed according to white channel values ​​of the central block and each peripheral block, and determining a compensation threshold of the area to be processed according to non-white channel values ​​of the central block and each peripheral block; and a compensation module, for selectively using the crosstalk compensation value to compensate the white channel value of the central block according to a comparison result of the crosstalk compensation value and the compensation threshold.

[0019] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus; the memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the image crosstalk compensation method described in the first aspect above.

[0020] According to a fourth aspect of the embodiments of the present application, a computer storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the image crosstalk compensation method as described in the first aspect above can be implemented.

[0021] In summary, the image crosstalk compensation method, device, electronic device and storage medium provided in each embodiment of the present application divide the area to be processed into a central block and multiple peripheral blocks, and determine the crosstalk compensation value and compensation threshold of the area to be processed according to the white channel value and non-white channel value of the central block and each peripheral block, so as to dynamically perform image crosstalk compensation of the central block, thereby effectively improving the imaging quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Hereinafter, some specific embodiments of the present application will be described in detail in an exemplary and non-limiting manner with reference to the accompanying drawings. The same reference numerals in the accompanying drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the accompanying drawings:

[0023] Figure 1 The figure is a processing flow chart of an image crosstalk compensation method according to an exemplary embodiment of the present application.

[0024] Figure 2 This is a processing flow chart of an image crosstalk compensation method according to another exemplary embodiment of the present application.

[0025] FIG. 3A to FIG. 3B It is a schematic diagram of a minimum filter group and a region to be processed determined based on the minimum filter group according to an exemplary embodiment of the present application.

[0026] FIG. 4A to FIG. 4B It is a schematic diagram of a minimum filter group and a region to be processed determined based on the minimum filter group according to another exemplary embodiment of the present application.

[0027] Figure 5 This is a processing flow chart of an image crosstalk compensation method according to another exemplary embodiment of the present application.

[0028] Fig. 6A It is a schematic diagram of the distribution of the central block and the peripheral blocks in the area to be processed in an exemplary embodiment of the present application.

[0029] FIG. 6B to FIG. 6C Schematic diagram of the distribution of grid units in the central block of different embodiments of the present application.

[0030] Figure 7 This is a processing flow chart of an image crosstalk compensation method according to another exemplary embodiment of the present application.

[0031] Figure 8 This is a processing flow chart of an image crosstalk compensation method according to another exemplary embodiment of the present application.

[0032] Fig. 9 This is a processing flow chart of an image crosstalk compensation method according to another exemplary embodiment of the present application.

[0033] Fig.10 It is a structural block diagram of an image crosstalk compensation device according to an exemplary embodiment of the present application.

[0034] Fig.11 It is a structural block diagram of an electronic device according to an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0036] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0037] In the present application, directional terms such as "upper", "lower", "front" and "back" are defined relative to the orientation of the components in the drawings. It should be understood that these directional terms are relative concepts. They are used for relative description and clarification, and they may change accordingly according to the change of the orientation of the components in the drawings.

[0038] In addition, unless a specified order is clearly stated in the context of the present application, the processing steps described herein may be performed differently from the specified order, that is, each step may be performed in the specified order, each step may be performed substantially simultaneously, each step may be performed in the reverse order, or each step may be performed in a different order.

[0039] As consumers' requirements for image quality increase, RGBW filter array has gradually become the mainstream choice in the market. Although the W (white) channel filter in the RGBW filter array can transmit a wider spectrum and perform better in low-light imaging environments, the crosstalk between channels is more serious than that of the traditional RGB three-channel Bayer array.

[0040] In view of this, the present application proposes an image crosstalk compensation solution for the RGBW filter array. Specifically, since the imbalance caused by crosstalk mainly occurs in the white channel, the present application proposes an image crosstalk compensation solution specifically for compensating the white channel.

[0041] See also Figure 1 , which is a processing flow chart of the image crosstalk compensation method of the exemplary embodiment of the present application, which mainly includes the following steps:

[0042] Step S102 : determining a central block and a plurality of peripheral blocks surrounding the central block in the area to be processed according to each grid unit in the area to be processed.

[0043] Optionally, the area to be processed may be equally divided according to each grid unit in the area to be processed to obtain a plurality of sub-blocks of equal size.

[0044] In this embodiment, the sub-block located at the center of each sub-block may be determined as the central block, and each sub-block surrounding the central block may be determined as each peripheral block.

[0045] Step S104 , determining a crosstalk compensation value of the area to be processed according to the white channel values ​​of the central block and each peripheral block, and determining a compensation threshold of the area to be processed according to the non-white channel values ​​of the central block and each peripheral block.

[0046] Optionally, the white channel mean of the central block and each peripheral block can be determined based on the white channel values ​​of the central block and each peripheral block, the similarity weight value and the gradient weight value can be determined based on the white channel mean of the central block and each peripheral block, and the crosstalk compensation value of the area to be processed can be determined based on the similarity weight value and the gradient weight value.

[0047] Optionally, the non-white channel mean of the central block and each peripheral block can be determined based on the non-white channel values ​​of the central block and each peripheral block, the saturation of the area to be processed can be determined based on the non-white channel mean of the central block and each peripheral block, and the compensation threshold of the area to be processed can be determined based on the saturation and a given maximum crosstalk intensity value.

[0048] In this embodiment, the non-white channel value includes one of a red channel value (R value), a green channel value (G value), and a blue channel value (B value).

[0049] Step S106 , based on the comparison result between the crosstalk compensation value and the compensation threshold, selectively using the crosstalk compensation value to compensate the white channel value of the central block.

[0050] In this embodiment, if the crosstalk compensation value is greater than the compensation threshold, it means that the central block of the area to be processed is a texture detail, and no compensation processing is performed. If the crosstalk compensation value is less than or equal to the compensation threshold, the crosstalk compensation value is used to perform compensation processing on the white channel value of the central block.

[0051] In summary, the image crosstalk compensation method of this embodiment can perform compensation on the white channel value of the central block of the area to be processed, so as to effectively improve the problem in the prior art that the imbalance caused by crosstalk mainly occurs in the white channel, thereby improving the imaging quality.

[0052] Furthermore, the image crosstalk method of this embodiment can effectively retain the texture details in the image and avoid image degradation caused by crosstalk compensation by comparing the crosstalk compensation value and the compensation threshold to selectively perform compensation processing on the white channel.

[0053] Figure 2 This is a processing flow chart of an image crosstalk compensation method of another exemplary embodiment of the present application. This embodiment can be used as a pre-implementation of S102, which mainly includes the following steps:

[0054] Step S202, identifying a minimum filter group of an image capture device used to obtain the image to be processed, and determining each grid unit in the image to be processed according to the minimum filter group.

[0055] Optionally, the image capture device comprises a camera.

[0056] In this embodiment, the image to be processed includes a plurality of tiled minimal repeating units, and each minimal repeating unit includes a minimum filter group.

[0057] Optionally, the minimum filter group is a square array (also referred to as a square matrix) composed of a plurality of grid units.

[0058] Specifically, each grid unit in the minimum filter group is arranged in rows and columns, and the number of rows and columns of the grid units is the same to form a square filter array. Exemplarily, the minimum filter group may include but is not limited to a 6×6 filter group, an 8×8 filter group, etc.

[0059] In this embodiment, each minimum filter group includes four different light response filters, namely, a fully transparent filter (W), a red filter (R), a green filter (G), and a blue filter (B). Each light response filter corresponds to a grid unit in the image to be processed.

[0060] Specifically, when the minimum filter group is an 8×8 filter group, according to the minimum filter group, the channel color distribution of each grid unit in the image to be processed is determined as follows: Figure 3A As shown; when the minimum filter group is a 6×6 filter group, according to the minimum filter group, the channel color distribution of each grid unit in the image to be processed is determined as follows: Figure 4A shown.

[0061] Step S204: determining a second number of grid cells covered by the sliding window and a sliding step size of the sliding window according to a first number of grid cells covered by the minimum filter group.

[0062] In this embodiment, the sliding window determined based on the minimum filter group is also presented as a square array composed of a plurality of grid units. The grid units in the sliding window are arranged in rows and columns, and the number of rows and columns of the grid units are the same.

[0063] In this embodiment, the number of second units is 2.25 times the number of first units, that is, the number of rows or columns of grid units covered by the sliding window is 1.5 times the number of rows or columns of grid units covered by the minimum filter group. It can also be regarded that the side length of the sliding window is 1.5 times the side length of the minimum filter group (the size of each grid unit is the same).

[0064] Exemplarily, if the minimum filter group is an 8×8 filter group, that is, the minimum filter group covers 64 grid units of 8×8, the sliding window determined based on the minimum filter group can cover 144 grid units of 12×12; if the minimum filter group is a 6×6 filter group, that is, the minimum filter group covers 36 grid units of 6×6, the sliding window determined based on the minimum filter group can cover 81 grid units of 9×9.

[0065] In this embodiment, the number of rows and columns of grid units covered by the minimum filter group are both even numbers.

[0066] In this embodiment, the sliding step size of the sliding window is 1 / 3 of the side length of the sliding window.

[0067] Exemplarily, if the side length of the sliding window is 12 grid units in length, the sliding step length is 4 grid units in length; if the side length of the sliding window is 9 grid units in length, the sliding step length is 3 grid units in length.

[0068] Step S206, using a sliding window, repeatedly performing sliding processing that satisfies the sliding step length on each grid unit of the image to be processed, and obtaining each area to be processed corresponding to each sliding processing.

[0069] Specifically, a sliding window can be used to perform multiple sliding processes on each grid unit of the image to be processed, and the sliding distance of each sliding process performed is consistent with the sliding step size to obtain a processed area corresponding to each sliding process, wherein each processed area is covered with the second number of grid units.

[0070] For example, if the side length of the sliding window is 12 grid units and the sliding step length is 4 grid units, the following can be obtained: Figure 3B The area to be processed is shown, which is covered with 12×12 grid cells.

[0071] For example, if the side length of the sliding window is 9 grid units long and the sliding step length is 3 grid units long, the following can be obtained: Figure 4B The area to be processed is shown, which is covered with 9×9 grid cells.

[0072] To sum up, the image crosstalk compensation method of this embodiment determines the window size and sliding step of the sliding window according to the minimum filter group of the image capture device used to obtain the image to be processed, so that the grid cells covered in the area to be processed determined based on the sliding window can be adapted to the grid cells covered by the minimum filter group, which is beneficial to improving the effect of image crosstalk compensation processing.

[0073] Figure 5 This is a processing flow chart of an image crosstalk compensation method of another exemplary embodiment of the present application. This embodiment is a specific implementation of the above step S102, which mainly includes:

[0074] Step S502: Using a sliding window, based on the current position and the sliding step size, sliding processing is performed on each grid unit of the image to be processed to determine the area to be processed in the image to be processed.

[0075] For example, when the side length of the sliding window is 12 grid units and the sliding step length is 4 grid units, a processing area covered with 12×12 grid units (such as Figure 3B shown).

[0076] For example, when the side length of the sliding window is 9 grid units and the sliding step length is 3 grid units, a processing area covering 9×9 grid units (such as Figure 4B shown).

[0077] Step S504 , dividing the area to be processed into nine equal parts according to each grid unit in the area to be processed, and obtaining nine sub-blocks of the area to be processed.

[0078] In this embodiment, the area to be processed has nine sub-blocks of the same size, and each sub-block can be arranged in a nine-square grid (refer to Fig. 6A ).

[0079] For example, when the area to be processed covers 12×12 grid cells, each sub-block covers 4×4 grid cells (refer to Figure 6B ); When the area to be processed covers 9×9 grid cells, each sub-block covers 3×3 grid cells (refer to Figure 6C ).

[0080] At Figure 6B and Figure 6C In the illustrated embodiment, W corresponds to a fully transparent filter for characterizing white channel values, and C corresponds to a red (R), green (G) or blue (B) filter for characterizing non-white channel values ​​(i.e., any one of red, green, and blue).

[0081] Step S506 , determining a sub-block located at the center of each sub-block as a central block, and determining eight sub-blocks surrounding the central block as peripheral blocks.

[0082] Specifically, refer to Fig. 6A , the sub-block 22 located at the center position can be determined as the central block, and the eight sub-blocks 11, 21, 31, 12, 32, 13, 23, and 33 surrounding the central block 22 can be determined as peripheral blocks.

[0083] Step S508, identifying the channel color of each grid unit covered by the central block.

[0084] In this embodiment, in each sub-block as a central block or a peripheral block, the number of grid units of the white channel (W channel) and the number of grid units of non-white channels (R channel, G channel, B channel) included may be equal or unequal.

[0085] For example, in Figure 6B In the illustrated embodiment, each sub-block includes 8 grid units of white channels and 8 grid units of non-white channels; Figure 6B In the illustrated embodiment, each sub-block includes 9 grid units, wherein each sub-block may include 4 grid units of white channels and 5 grid units of non-white channels.

[0086] It should be noted that in a single sub-block, the channel colors of the grid cells of the non-white channels must be the same (refer to Figure 3B or Figure 4B ).

[0087] Specifically, the channel colors of the grid cells corresponding to the non-white channels in the central block may be identified.

[0088] Step S510, determining whether the central block includes a green grid unit, if so, returning to step S502, if not, executing step S104.

[0089] Specifically, if it is determined that the central block is covered with green grid cells, image crosstalk compensation processing is not performed on the current area to be processed, and the process returns to step S502 to obtain the next area to be processed in the image to be processed until each grid cell in the image to be processed is covered by the sliding window at least once; conversely, if it is determined that the central block is not covered with green grid cells, that is, the central block covers red or blue grid cells, step S104 is performed to perform image crosstalk compensation processing on the current area to be processed.

[0090] In summary, this embodiment can improve the effect of image crosstalk processing by determining the central block and peripheral blocks of the area to be processed and selectively performing image crosstalk compensation processing on the area to be processed by identifying the channel colors of the grid units covered by the central block.

[0091] Figure 7 A processing flow chart of an image crosstalk compensation method of another exemplary embodiment of the present application is shown. This embodiment shows a specific implementation scheme of determining the crosstalk compensation value of the area to be processed in the above step S104, which mainly includes:

[0092] Step S702 , determining the white channel average values ​​of the central block and each peripheral block according to the white channel values ​​of the central block and each peripheral block.

[0093] Optionally, for any sub-block in the central block and each peripheral block, a white channel mean value of the sub-block is determined according to each white channel value in the sub-block.

[0094] Optionally, the white channel mean of the sub-block may be calculated using the following formula 1:

[0095]

[0096] In the above formula 1, represents the mean value of the white channel of the sub-block in the i-th row and j-th column of the area to be processed, W z is the zth white channel value in the sub-block, and M is the number of white channel values ​​contained in the sub-block.

[0097] For example, in Figure 6B In the embodiment shown, each sub-block includes 8 white channel values ​​(ie, W1 to W8), and the value of M is 8; Figure 6CIn the illustrated embodiment, each sub-block includes four white channel values ​​(ie, W1 to W4), and the value of M is 4.

[0098] Step S704 , determining each adjacent edge block in each peripheral block that is adjacent to each side edge of the central block, and determining a similarity weight value of each adjacent edge block according to the white channel average value of the central block and each adjacent edge block.

[0099] refer to Fig. 6A In this embodiment, four peripheral blocks 12, 21, 23, and 32 adjacent to four sides of the central block 22 can be determined as adjacent edge blocks.

[0100] Optionally, the compensation reference value of each adjacent edge block can be determined based on the difference between the white channel mean value of the central block and the white channel mean value of each adjacent edge block, and the similarity weight value of each adjacent edge block can be determined based on the compensation reference value of each adjacent edge block and a given similarity weight coefficient.

[0101] In this embodiment, the following formulas 2 to 5 may be used to determine the compensation reference value of each adjacent block according to the difference between the white channel average value of the central block and the white channel average value of each adjacent block:

[0102]

[0103]

[0104]

[0105]

[0106] In the above formulas 2 to 5, δ1 represents the compensation reference value of the adjacent block 12; δ2 represents the compensation reference value of the adjacent block 21; δ3 represents the compensation reference value of the adjacent block 23; δ4 represents the compensation reference value of the adjacent block 32 (reference Fig. 6A ).

[0107] In this embodiment, the similarity weight value of each adjacent block can be determined according to the compensation reference value of each adjacent block and a given similarity weight coefficient using the following formula 6:

[0108]

[0109] In the above formula 6, weight1 i represents the similarity weight value of the i-th neighboring block, δ i represents the compensation reference value of the i-th adjacent block (ie, δ1, δ2, δ3, δ4 mentioned above), and σ1 is an adjustable similarity weight coefficient.

[0110] Step S706, determining the gradient weight value of the area to be processed according to the white channel mean value of each surrounding block.

[0111] Optionally, the horizontal gradient value and vertical gradient value of the area to be processed can be determined based on the position distribution of each surrounding block in the area to be processed and the mean value of the white channel of each surrounding block, and the gradient weight value of the area to be processed can be determined based on the larger of the horizontal gradient value and the vertical gradient value and a given gradient weight coefficient.

[0112] In this embodiment, the horizontal gradient value of the area to be processed can be determined according to the white channel average value of each peripheral block in the left column and the right column of the area to be processed using the following formula 7:

[0113]

[0114] In the above formula 7, grad hor Represents the horizontal gradient value of the area to be processed, is the mean value of the white channel of each peripheral block in the left column of the area to be processed, is the mean value of the white channel of each peripheral block in the right column of the area to be processed (reference Fig. 6A ).

[0115] In this embodiment, the vertical gradient value of the area to be processed can be determined according to the white channel average value of each peripheral block in the top row and the bottom row of the area to be processed using the following formula 8:

[0116]

[0117] In the above formula 8, grad ver Indicates the vertical gradient value of the area to be processed, is the mean value of the white channel of each peripheral block in the top row of the area to be processed, is the mean value of the white channel of each peripheral block in the bottom row of the area to be processed (reference Fig. 6A ).

[0118] In this embodiment, the following formula 9 can be used to determine the gradient weight value of the area to be processed according to the larger of the horizontal gradient value and the vertical gradient value and a given gradient weight coefficient:

[0119]

[0120] In the above formula 9, weight2 represents the gradient weight value of the area to be processed, and grad represents the larger of the horizontal gradient value and the vertical gradient value, that is, grad = max (grad hor ,grad ver ), σ2 represents the adjustable gradient weight coefficient.

[0121] Step S708: Determine the crosstalk compensation value of the area to be processed according to the similarity weight value of each adjacent edge block and the gradient weight value of the area to be processed.

[0122] Optionally, a first weighted value can be determined based on the similarity weight values ​​of each adjacent edge block, the gradient weight value of the area to be processed, and the compensation reference value of each adjacent edge block; a second weighted value can be determined based on the similarity weight value of each adjacent edge block and the gradient weight value of the area to be processed; and a crosstalk compensation value of the area to be processed can be determined based on the first weighted value and the second weighted value.

[0123] In this embodiment, the following formula 10 can be used to determine the crosstalk compensation value of the area to be processed according to the similarity weight value of each adjacent block, the gradient weight value of the area to be processed, and the compensation reference value of each adjacent block:

[0124]

[0125] In the above formula 10, δ represents the crosstalk compensation value of the area to be processed, weight1 i represents the similarity weight value of the i-th adjacent block, weight2 represents the gradient weight value of the area to be processed, and δ i represents the compensation reference value of the i-th adjacent edge block.

[0126] To sum up, the image crosstalk compensation method of this embodiment adopts the weighted average method of similarity weight value and gradient weight value to determine the crosstalk compensation value of the area to be processed, which can avoid the texture details in the image from being miscompensated, effectively retain the rich texture details in the image, and avoid the problem of image degradation.

[0127] Figure 8 The processing flow chart of the image crosstalk compensation method of another exemplary embodiment of the present application is shown. This embodiment shows a specific implementation scheme of determining the compensation threshold of the area to be processed in the above step S104, which mainly includes the following steps:

[0128] Step S802 , determining the non-white channel averages of the central block and each peripheral block according to the non-white channel values ​​of the central block and each peripheral block.

[0129] In this embodiment, the non-white channel values ​​of the central block and each peripheral block include any one of a red channel value, a green channel value, and a blue channel value.

[0130] Optionally, for any sub-block in the central block and each peripheral block, the non-white channel mean value of the sub-block is determined according to each non-white channel value in the sub-block.

[0131] Optionally, the non-white channel mean of the sub-block may be calculated using the following formula 11:

[0132]

[0133] In the above formula 11, represents the mean value of the non-white channel of the sub-block in the i-th row and j-th column of the area to be processed, C z is the zth non-white channel value in the sub-block, and N is the number of non-white channel values ​​contained in the sub-block.

[0134] For example, in Figure 6B In the embodiment shown, each sub-block includes 8 non-white channel values ​​(ie, C1 to C8), and the value of N is 8; Figure 6C In the illustrated embodiment, each sub-block includes five non-white channel values ​​(ie, C1 to C5), and the value of N is 5.

[0135] Step S804 , determining the red pixel mean, green pixel mean, and blue pixel mean of the area to be processed according to the non-white channel mean of the central block and each peripheral block.

[0136] Optionally, each adjacent edge block adjacent to each side edge of the central block may be determined in each peripheral block, and each corner block adjacent to each corner of the central block may be determined in each peripheral block.

[0137] refer to Fig. 6A In this embodiment, the four peripheral blocks 12, 21, 23, and 32 adjacent to the four sides of the central block 22 can be determined as adjacent edge blocks, and the four peripheral blocks 11, 13, 31, and 33 adjacent to the four corners of the central block 22 can be determined as corner blocks.

[0138] Optionally, the channel color of each grid unit in the central block may be determined to dynamically determine the mean value of red pixels, the mean value of green pixels, and the mean value of blue pixels in the area to be processed.

[0139] In this embodiment, if the central block contains red grid units, the red pixel mean of the area to be processed can be determined based on the non-white channel mean of the central block, the green pixel mean of the area to be processed can be determined based on the non-white channel mean of each adjacent block, and the blue pixel mean of the area to be processed can be determined based on the non-white channel mean of each corner block.

[0140] Specifically, if the central block contains red grid cells, the mean value of red pixels in the area to be processed can be determined according to the following formula 12, the mean value of green pixels in the area to be processed can be determined according to the following formula 13, and the mean value of blue pixels in the area to be processed can be determined according to the following formula 14:

[0141]

[0142]

[0143]

[0144] In the above formula 12, Represents the mean value of red pixels in the area to be processed, Represents the mean value of the non-white channels in the center block.

[0145] In the above formula 13, represents the mean value of green pixels in the area to be processed, Represents the average value of the non-white channel of each adjacent block.

[0146] In the above formula 14, Represents the mean value of blue pixels in the area to be processed, Represents the mean value of the non-white channel of each corner block.

[0147] In this embodiment, if the central block contains blue grid units, the blue pixel mean of the area to be processed is determined according to the non-white channel mean of the central block, the green pixel mean of the area to be processed is determined according to the non-white channel mean of each adjacent block, and the red pixel mean of the area to be processed is determined according to the non-white channel mean of each corner block.

[0148] Specifically, if the central block contains blue grid cells, the mean value of blue pixels in the area to be processed can be determined according to the following formula 15, the mean value of green pixels in the area to be processed can be determined according to the following formula 16, and the mean value of red pixels in the area to be processed can be determined according to the following formula 17:

[0149]

[0150]

[0151]

[0152] In the above formula 15, Represents the mean value of blue pixels in the area to be processed, Represents the mean value of the non-white channels in the center block.

[0153] In the above formula 16, represents the mean value of green pixels in the area to be processed, Represents the average value of the non-white channel of each adjacent block.

[0154] In the above formula 17, Represents the mean value of red pixels in the area to be processed, Represents the mean value of the non-white channel of each corner block.

[0155] Step S806, determining the saturation of the area to be processed according to the maximum and minimum values ​​of the red pixel mean, the green pixel mean, and the blue pixel mean in the area to be processed.

[0156] Specifically, the saturation of the area to be processed can be calculated using the following formula 18 according to the maximum and minimum values ​​of the red pixel mean, green pixel mean, and blue pixel mean in the area to be processed:

[0157]

[0158] In the above formula 18, sat represents the saturation of the area to be processed, Indicates the minimum value among the mean values ​​of red pixels, green pixels, and blue pixels in the area to be processed. Indicates the maximum value among the mean values ​​of red pixels, green pixels, and blue pixels in the area to be processed.

[0159] Step S808: determining a compensation threshold of the area to be processed according to the saturation of the area to be processed and a given maximum crosstalk intensity value.

[0160] In this embodiment, the compensation threshold of the area to be processed can be determined according to the saturation of the area to be processed and a given maximum crosstalk intensity value using the following formula 19:

[0161] Thre=sat*stren (Formula 19)

[0162] In the above formula 19, Thre represents the compensation threshold of the area to be processed, sat represents the saturation of the area to be processed, and stren represents the maximum crosstalk intensity value, which can be determined by calibration, that is, the maximum crosstalk intensity value can be adjusted according to the actually set crosstalk standard.

[0163] In summary, the image crosstalk compensation method of this embodiment dynamically determines the compensation threshold of the area to be processed according to the non-white channel values ​​of the central block and each peripheral block, and uses this color-related dynamic threshold rather than a fixed threshold to determine whether compensation processing needs to be performed. This can retain more color details in the image to improve the processing effect of image crosstalk compensation.

[0164] Fig. 9 The processing flow chart of the image crosstalk compensation method of another exemplary embodiment of this embodiment is shown. This embodiment shows a specific implementation scheme of the above step S106, which mainly includes the following steps:

[0165] Step S902: compare the crosstalk compensation value and the compensation threshold.

[0166] Specifically, a size comparison may be performed on the crosstalk compensation value and the compensation threshold.

[0167] Step S904, determining whether the crosstalk compensation value is greater than the compensation threshold, if so, ending the process, if not, proceeding to step S906.

[0168] Specifically, if the crosstalk compensation value is greater than the compensation threshold (δ>Thre), it means that the current area to be processed is a texture detail, and there is no need to perform image crosstalk compensation processing, and the process ends; otherwise, if the crosstalk compensation value is less than or equal to the compensation threshold (δ≤Thre), step S906 is executed.

[0169] Step S906 , determining an adaptive weight value of each white channel value according to the crosstalk compensation value and each white channel value in the central block.

[0170] In this embodiment, the adaptive weight value of each white channel value can be calculated according to the crosstalk compensation value and each white channel value in the central block using Formula 20:

[0171]

[0172] In the above formula 20, weight3 i represents the adaptive weight value of the i-th white channel value, δ represents the crosstalk compensation value, W i Represents the i-th white channel value.

[0173] Step S908 , determining the compensation channel value of each white channel value in the central block according to each white channel value in the central block, the adaptive weight value of each white channel value, and the crosstalk compensation value.

[0174] In this embodiment, the compensation channel value of each white channel value in the central block can be determined according to each white channel value in the central block, the adaptive weight value of each white channel value, and the crosstalk compensation value using the following formula 21:

[0175] W i corr =W i +weight3 i ×δ (Formula 21)

[0176] In the above formula 21, W i corr Represents the compensation channel value of the i-th white channel value, W i Indicates the i-th white channel value, weight3 i represents the adaptive weight value of the i-th white channel value, and δ represents the crosstalk compensation value.

[0177] To summarize, the image crosstalk compensation method of the present embodiment calculates the adaptive weight value of each white pixel in the central block, and compensates for the white channel value of each white pixel accordingly. By adopting an adaptive method to respectively calculate the compensation value of each white channel value, rather than uniformly performing the compensation of each white channel value in a fixed compensation method, the influence of noise on the compensation value can be effectively avoided, thereby improving the imaging quality.

[0178] Fig.10 1 is a structural block diagram of an image crosstalk compensation device according to an exemplary embodiment of the present application. As shown in the figure, the image crosstalk compensation device 1000 according to the present embodiment includes a block determination module 1002 , a calculation module 1004 , and a compensation module 1006 .

[0179] The block determination module 1002 is used to determine a central block and a plurality of peripheral blocks surrounding the central block in the area to be processed according to each grid unit in the area to be processed.

[0180] The calculation module 1004 is used to determine the crosstalk compensation value of the area to be processed according to the white channel values ​​of the central block and each peripheral block, and to determine the compensation threshold of the area to be processed according to the non-white channel values ​​of the central block and each peripheral block.

[0181] The compensation module 1006 is configured to selectively use the crosstalk compensation value to compensate the white channel value of the central block according to a comparison result between the crosstalk compensation value and the compensation threshold.

[0182] Optionally, the block determination module 1002 is further used to: identify a minimum filter group of an image capture device used to obtain an image to be processed, and determine each grid unit in the image to be processed based on the minimum filter group; determine a second number of grid units covered by a sliding window and a sliding step of the sliding window based on a first number of grid units covered by the minimum filter group; and use the sliding window to repeatedly perform sliding processing that satisfies the sliding step on each grid unit of the image to be processed, to obtain each area to be processed corresponding to each sliding processing.

[0183] Optionally, the minimum filter group and the sliding window are respectively square arrays composed of multiple grid units; the number of the second units is 2.25 times the number of the first units; and the sliding step size of the sliding window is 1 / 3 of the side length of the sliding window.

[0184] Optionally, the block determination module 1002 is also used to: perform nine-equal division processing on the area to be processed according to each grid unit in the area to be processed to obtain nine sub-blocks of the area to be processed; determine a sub-block located at the center position of each sub-block as the central block, and determine eight sub-blocks surrounding the central block as peripheral blocks.

[0185] Optionally, the calculation module 1004 is also used to: identify the channel color of each grid unit covered by the central block; if it is identified that the central block is covered with red or blue grid units, determine the crosstalk compensation value of the area to be processed according to the white channel value of the central block and each surrounding block, and determine the compensation threshold of the area to be processed according to the non-white channel value of the central block and each surrounding block.

[0186] Optionally, the calculation module 1004 is also used to: determine the white channel mean of the central block and each peripheral block according to the white channel values ​​of the central block and each peripheral block; determine each adjacent edge block in each peripheral block that is adjacent to each side of the central block, and determine the similarity weight value of each adjacent edge block according to the white channel mean of the central block and each adjacent edge block; determine the gradient weight value of the area to be processed according to the white channel mean of each peripheral block; determine the crosstalk compensation value of the area to be processed according to the similarity weight value of each adjacent edge block and the gradient weight value of the area to be processed.

[0187] Optionally, the calculation module 1004 is also used to: determine the compensation reference value of each adjacent edge block according to the difference between the white channel mean value of the central block and the white channel mean value of each adjacent edge block; determine the similarity weight value of each adjacent edge block according to the compensation reference value of each adjacent edge block and a given similarity weight coefficient.

[0188] Optionally, the calculation module 1004 is also used to: determine the horizontal gradient value and the vertical gradient value of the area to be processed according to the position distribution of each surrounding block in the area to be processed and the white channel mean of each surrounding block; determine the gradient weight value of the area to be processed according to the larger of the horizontal gradient value and the vertical gradient value and a given gradient weight coefficient.

[0189] Optionally, the calculation module 1004 is also used to: determine a first weighted value based on the similarity weight value of each adjacent edge block, the gradient weight value of the area to be processed, and the compensation reference value of each adjacent edge block; determine a second weighted value based on the similarity weight value of each adjacent edge block and the gradient weight value of the area to be processed; determine the crosstalk compensation value of the area to be processed based on the first weighted value and the second weighted value.

[0190] Optionally, the calculation module 1004 is also used to: determine the non-white channel mean of the central block and each peripheral block according to the non-white channel values ​​of the central block and each peripheral block, wherein the non-white channel value includes one of the red channel value, the green channel value, and the blue channel value; determine the red pixel mean, the green pixel mean, and the blue pixel mean of the area to be processed according to the non-white channel mean of the central block and each peripheral block; determine the saturation of the area to be processed according to the maximum and minimum values ​​of the red pixel mean, the green pixel mean, and the blue pixel mean of the area to be processed; determine the compensation threshold of the area to be processed according to the saturation of the area to be processed and a given crosstalk maximum intensity value.

[0191] Optionally, the calculation module 1004 is also used to: determine each adjacent side block adjacent to each side of the central block in each peripheral block, and determine each vertex block adjacent to each vertex of the central block in each peripheral block; determine the channel color of each grid unit in the central block, if the central block contains red grid units, determine the red pixel mean of the area to be processed according to the non-white channel mean of the central block, determine the green pixel mean of the area to be processed according to the non-white channel mean of each adjacent side block, and determine the blue pixel mean of the area to be processed according to the non-white channel mean of each vertex block; or if the central block contains blue grid units, determine the blue pixel mean of the area to be processed according to the non-white channel mean of the central block, determine the green pixel mean of the area to be processed according to the non-white channel mean of each adjacent side block, and determine the red pixel mean of the area to be processed according to the non-white channel mean of each vertex block.

[0192] Optionally, the compensation module 1006 is also used to: compare the crosstalk compensation value and the compensation threshold; if the crosstalk compensation value is less than or equal to the compensation threshold, determine the adaptive weight value of each white channel value according to the crosstalk compensation value and each white channel value in the central block; and determine the compensation channel value of each white channel value in the central block according to each white channel value in the central block, the adaptive weight value of each white channel value, and the crosstalk compensation value; if the crosstalk compensation value is greater than the compensation threshold, compensation processing for each white channel value in the central block is not performed.

[0193] The image crosstalk compensation device provided in the embodiment of the present invention corresponds to the image crosstalk compensation method provided in each embodiment of the present invention. Other descriptions may refer to the description of the image crosstalk compensation method provided in each embodiment of the present invention, which will not be repeated here.

[0194] Another embodiment of the present invention provides an electronic device, including: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus.

[0195] Fig.11 This is a structural block diagram of an electronic device according to an exemplary embodiment of the present invention. As shown in the figure, the electronic device 1100 of this embodiment may include a processor 1102 , a communication interface 1104 , and a memory 1106 .

[0196] The processor 1102 , the communication interface 1104 , and the memory 1106 may communicate with each other via a communication bus 1108 .

[0197] The communication interface 1104 is used to communicate with other electronic devices such as terminal devices or servers.

[0198] The processor 1102 is used to execute the computer program 1110, and specifically can execute the relevant steps in the above-mentioned method embodiments, that is, execute the steps in the image crosstalk compensation method as described in the above-mentioned embodiments.

[0199] Specifically, the computer program 1110 may include program codes, which include computer operation instructions.

[0200] The processor 1102 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the electronic device may be processors of the same type, such as one or more CPUs, or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0201] The memory 1106 is used to store the computer program 1110. The memory 1106 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0202] Another embodiment of the present invention provides a computer storage medium on which a computer program is stored. When the program is executed by a processor, the image crosstalk compensation method described in the above embodiments can be implemented.

[0203] It should be pointed out that, according to the needs of implementation, the various components / steps described in the embodiments of the present invention can be split into more components / steps, or two or more components / steps or partial operations of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of the present invention.

[0204] The method according to the embodiment of the present invention described above may be implemented in hardware, firmware, or as software or computer code that can be stored in a recording medium (such as a CD ROM, RAM, floppy disk, hard disk or magneto-optical disk), or as computer code that is originally stored in a remote recording medium or a non-temporary machine-readable medium downloaded through a network and will be stored in a local recording medium, so that the method described herein can be stored in such software processing on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code, and when the software or computer code is accessed and executed by a computer, a processor, or hardware, the image crosstalk compensation method described herein is implemented. In addition, when a general-purpose computer accesses code for implementing the image crosstalk compensation method shown herein, the execution of the code converts the general-purpose computer into a dedicated computer for executing the image crosstalk compensation method shown herein.

[0205] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present invention.

[0206] Thus far, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired results. Additionally, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing may be advantageous.

[0207] It should be noted that, under the premise of no conflict, the various embodiments and / or technical features in the various embodiments described in this application can be arbitrarily combined with each other, and the technical solutions obtained after the combination should also fall within the protection scope of this application. The various embodiments in this specification are described in a progressive manner, and the same and similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments.

[0208] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for compensating image crosstalk, characterized in that: include: Determine, according to each grid unit in the area to be processed, a central block in the area to be processed and a plurality of peripheral blocks surrounding the central block; Determine the crosstalk compensation value of the area to be processed according to the white channel values ​​of the central block and each peripheral block, and determine the compensation threshold of the area to be processed according to the non-white channel values ​​of the central block and each peripheral block; According to a comparison result between the crosstalk compensation value and the compensation threshold, selectively using the crosstalk compensation value to compensate the white channel value of the central block; Determining the crosstalk compensation value of the area to be processed according to the white channel values ​​of the central block and each peripheral block includes: Determine the white channel average value of the central block and each peripheral block according to the white channel values ​​of the central block and each peripheral block; Determine each adjacent edge block in each peripheral block that is adjacent to each side edge of the central block, and determine a similarity weight value of each adjacent edge block according to a white channel average value of the central block and each adjacent edge block; Determine the gradient weight value of the area to be processed according to the white channel mean value of each surrounding block; The crosstalk compensation value of the area to be processed is determined according to the similarity weight values ​​of each adjacent edge block and the gradient weight value of the area to be processed.

2. The method according to claim 1, characterized in that The area to be processed is obtained by: Identifying a minimum filter group of an image capture device used to obtain an image to be processed, and determining each grid cell in the image to be processed based on the minimum filter group; Determining a second number of grid cells covered by a sliding window and a sliding step length of the sliding window according to a first number of grid cells covered by the minimum filter group; The sliding window is used to repeatedly perform sliding processing that satisfies the sliding step length on each grid unit of the image to be processed, and each area to be processed corresponding to each sliding processing is obtained.

3. The method according to claim 2, characterized in that The minimum filter group and the sliding window are respectively square arrays consisting of a plurality of grid units; The number of the second units is 2.25 times the number of the first units; The sliding step size of the sliding window is 1 / 3 of the side length of the sliding window.

4. The method according to any one of claims 1 to 3, characterized in that The step of determining a central block and a plurality of peripheral blocks surrounding the central block in the area to be processed according to each grid unit in the area to be processed includes: According to each grid unit in the area to be processed, the area to be processed is divided into nine equal parts to obtain nine sub-blocks of the area to be processed; A sub-block located at a central position among the sub-blocks is determined as the central block, and eight sub-blocks surrounding the central block are determined as peripheral blocks.

5. The method according to claim 4, characterized in that The method further comprises: Identify the channel color of each grid cell covered by the central block; If it is identified that the central block is covered with red or blue grid cells, the crosstalk compensation value of the area to be processed is determined based on the white channel values ​​of the central block and each peripheral block, and the compensation threshold of the area to be processed is determined based on the non-white channel values ​​of the central block and each peripheral block.

6. The method according to claim 1, characterized in that Determining the similarity weight value of each adjacent edge block according to the white channel average value of the central block and each adjacent edge block includes: Determine a compensation reference value for each adjacent edge block according to a difference between a white channel mean value of the central block and a white channel mean value of each adjacent edge block; The similarity weight value of each adjacent edge block is determined according to the compensation reference value of each adjacent edge block and a given similarity weight coefficient.

7. The method according to claim 6, characterized in that Determining the gradient weight value of the area to be processed according to the white channel mean value of each surrounding block includes: Determine the horizontal gradient value and the vertical gradient value of the area to be processed according to the position distribution of each peripheral block in the area to be processed and the white channel average value of each peripheral block; The gradient weight value of the area to be processed is determined according to the larger one of the horizontal gradient value and the vertical gradient value and a given gradient weight coefficient.

8. The method according to claim 7, characterized in that The step of determining the crosstalk compensation value of the area to be processed according to the similarity weight values ​​of each adjacent edge block and the gradient weight value of the area to be processed includes: Determine a first weighted value according to the similarity weight value of each adjacent edge block, the gradient weight value of the to-be-processed area, and the compensation reference value of each adjacent edge block; Determine a second weighted value according to the similarity weight values ​​of each adjacent edge block and the gradient weight value of the area to be processed; A crosstalk compensation value of the area to be processed is determined according to the first weighted value and the second weighted value.

9. The method according to claim 1 or 5, characterized in that: The step of determining the compensation threshold of the area to be processed according to the non-white channel values ​​of the central block and each peripheral block includes: Determine the non-white channel averages of the central block and the peripheral blocks according to the non-white channel values ​​of the central block and the peripheral blocks, wherein the non-white channel value includes one of a red channel value, a green channel value, and a blue channel value; Determine the red pixel mean, green pixel mean, and blue pixel mean of the area to be processed according to the non-white channel mean of the central block and each peripheral block; Determine the saturation of the area to be processed according to the maximum and minimum values ​​of the red pixel mean, the green pixel mean, and the blue pixel mean of the area to be processed; A compensation threshold of the area to be processed is determined according to the saturation of the area to be processed and a given maximum crosstalk intensity value.

10. The method according to claim 9, characterized in that Determining the red pixel mean, the green pixel mean, and the blue pixel mean of the area to be processed according to the non-white channel mean of the central block and each peripheral block includes: Determine each adjacent edge block in each peripheral block that is adjacent to each side edge of the central block, and determine each corner block in each peripheral block that is adjacent to each corner of the central block; Determine the channel color of each grid cell in the central block, If the central block contains red grid cells, the mean value of red pixels in the area to be processed is determined according to the mean value of the non-white channel of the central block, the mean value of green pixels in the area to be processed is determined according to the mean value of the non-white channel of each adjacent block, and the mean value of blue pixels in the area to be processed is determined according to the mean value of the non-white channel of each corner block; or If the central block contains blue grid units, the mean value of blue pixels in the area to be processed is determined according to the mean value of the non-white channel of the central block, the mean value of green pixels in the area to be processed is determined according to the mean value of the non-white channel of each adjacent block, and the mean value of red pixels in the area to be processed is determined according to the mean value of the non-white channel of each corner block.

11. The method according to claim 1 or 5, characterized in that: The selectively using the crosstalk compensation value to compensate the white channel value of the central block according to the comparison result of the crosstalk compensation value and the compensation threshold value includes: comparing the crosstalk compensation value with the compensation threshold, If the crosstalk compensation value is less than or equal to the compensation threshold, determining an adaptive weight value of each white channel value according to the crosstalk compensation value and each white channel value in the central block, and determining a compensation channel value of each white channel value in the central block according to each white channel value in the central block, the adaptive weight value of each white channel value, and the crosstalk compensation value; If the crosstalk compensation value is greater than the compensation threshold, the compensation process of each white channel value in the central block is not performed.

12. An image crosstalk compensation device, characterized in that: include: A block determination module, used for determining a central block and a plurality of peripheral blocks surrounding the central block in the area to be processed according to each grid unit in the area to be processed; A calculation module, used to determine the crosstalk compensation value of the area to be processed according to the white channel values ​​of the central block and each peripheral block, and to determine the compensation threshold of the area to be processed according to the non-white channel values ​​of the central block and each peripheral block; A compensation module, configured to selectively use the crosstalk compensation value to compensate the white channel value of the central block according to a comparison result between the crosstalk compensation value and the compensation threshold; The calculation module is specifically used to: determine the white channel mean of the central block and each peripheral block according to the white channel value of the central block and each peripheral block; determine each adjacent block adjacent to each side of the central block in each peripheral block, and determine the similarity weight value of each adjacent block according to the white channel mean of the central block and each adjacent block; determine the gradient weight value of the area to be processed according to the white channel mean of each peripheral block; The crosstalk compensation value of the area to be processed is determined according to the similarity weight values ​​of each adjacent edge block and the gradient weight value of the area to be processed.

13. An electronic device, characterized in that: include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the image crosstalk compensation method according to any one of claims 1 to 11.

14. A computer storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the image crosstalk compensation method as claimed in any one of claims 1 to 11 can be implemented.

Images