Image processing method and device, equipment and medium
By calculating the average value of the acquired image and sub-image in the image acquisition area and determining the pixel compensation value, the problem of split screen phenomenon during image stitching is solved, and the image is balanced grayscale and high-quality visual effect is achieved.
Patent Information
- Application Number
- CN202411784578.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-02
- Publication Date
- 2025-03-28
Smart Images
Figure CN119722484A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of image processing technology, and in particular to an image processing method, device, equipment and medium. Background Art
[0002] When designing fingerprint collection under large-area display screens, fixed-size rectangular blocks are usually used as collection units. During use, when a fingerprint is detected, the images of several collection units covered by the fingerprint are collected in sequence, and then stitched together into a complete fingerprint image. Due to the differences in the electrical characteristics of the collection units themselves and the influence of environmental factors, the brightness of the images collected by each collection unit is different, resulting in obvious boundaries in the stitched image, resulting in a split screen phenomenon, affecting the visual effect and subsequent image processing. Summary of the invention
[0003] The present application discloses an image processing method, device, equipment and medium to solve the problem of split screen phenomenon caused by splicing images of different brightness.
[0004] In a first aspect, the present application discloses an image processing method, the image processing method comprising:
[0005] Acquire a captured image in an image acquisition area, wherein the image acquisition area includes a plurality of acquisition units, and the captured image is formed by splicing sub-images acquired by at least some of the acquisition units;
[0006] Selecting a partial image of each sub-image adjacent to a junction, and obtaining a plurality of selected area images corresponding to each sub-image, wherein the junction corresponds to a common boundary of two adjacent acquisition units;
[0007] Calculating a first pixel mean value of the acquired image and a second pixel mean value of a plurality of selected area images corresponding to each sub-image;
[0008] A pixel compensation value corresponding to each sub-image is determined based on the first pixel mean value and the second pixel mean value to compensate the collected image.
[0009] In some exemplary embodiments, calculating the first pixel mean of the acquired image includes:
[0010] Determining an image width, an image height, and a pixel value of each pixel of the acquired image;
[0011] A calculation is performed based on the image width, the image height and the pixel value of each pixel to obtain a pixel average value of the collected image as a first pixel average value.
[0012] In some exemplary embodiments, selecting a partial image of each sub-image adjacent to a boundary to obtain a plurality of selected area images corresponding to each sub-image comprises:
[0013] Selecting an area of the acquisition unit corresponding to each sub-image that is a preset width away from the junction as a selected area, and obtaining a plurality of selected areas corresponding to each acquisition unit;
[0014] Acquire a partial image corresponding to each selected area of each acquisition unit as a plurality of selected area images corresponding to each sub-image;
[0015] Optionally, the junction includes a first junction and a second junction adjacent to each other, the first junction is a common boundary of two adjacent collection units in a first direction, and the second junction is a common boundary of two adjacent collection units in a second direction;
[0016] Optionally, the first junction is perpendicular to the second junction.
[0017] In some exemplary embodiments, selecting an area of the acquisition unit corresponding to each sub-image that is a preset width away from the junction as the selected area includes:
[0018] The selected area is distributed in the same area in two adjacent collection units, and the two adjacent collection units are located on both sides of the junction;
[0019] Optionally, the preset width of the selected area is between 1 pixel and 20 pixels.
[0020] In some exemplary embodiments, calculating the second pixel mean of the plurality of selected area images corresponding to each sub-image comprises:
[0021] Calculating the pixel average value of each of the partial sub-images corresponding to each sub-image respectively to obtain a plurality of third pixel average values;
[0022] determining a total number of the selected areas;
[0023] The pixel average value of the images of the plurality of selected regions is obtained as the second pixel average value by performing calculation based on the total number of the selected regions and the plurality of third pixel average values.
[0024] In some exemplary embodiments, determining a pixel compensation value corresponding to each sub-image based on the first pixel mean value and the second pixel mean value to compensate the acquired image includes:
[0025] Calculating according to the first pixel mean value and the second pixel mean value to obtain a pixel compensation value corresponding to each sub-image;
[0026] Get the initial pixel value of each sub-image pixel;
[0027] Based on the pixel compensation value, the pixels of each sub-image are compensated.
[0028] In some exemplary embodiments, when the acquisition unit is composed of sub-images acquired by some of the acquisition units, the image processing method further includes:
[0029] Compensation is performed on sub-images other than the acquired image in the image acquisition area.
[0030] In a second aspect, the present application discloses an image processing device, the image processing device comprising:
[0031] An acquisition unit, used for acquiring an acquired image in an image acquisition area, wherein the image acquisition area includes a plurality of acquisition units, and the acquired image is formed by splicing sub-images acquired by at least some of the acquisition units;
[0032] A selection unit, used for selecting a partial image of each sub-image adjacent to a junction, and obtaining a selected area image corresponding to each sub-image, wherein the junction is a common boundary of two adjacent acquisition units;
[0033] A calculation unit, used for calculating a first pixel mean of the collected image and a second pixel mean of a plurality of selected area images corresponding to each sub-image;
[0034] A compensation unit is used to determine a pixel compensation value corresponding to each sub-image based on the first pixel mean value and the second pixel mean value, so as to compensate the collected image.
[0035] In a third aspect, the present application discloses an image processing device, comprising a processor, a memory, and a computer program stored in the memory, wherein the processor implements the steps of the image processing method described in the first aspect when executing the computer program.
[0036] In a fourth aspect, the present application discloses a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed, the steps of the image processing method described in the first aspect are implemented.
[0037] The image processing method, device, equipment and medium provided by the present application can solve the split screen phenomenon caused by the splicing of images of different brightness, with fast speed and good effect. Specifically, by obtaining the captured image of the image acquisition area, selecting the partial image of each sub-image near the junction, and obtaining multiple selected area images corresponding to each sub-image respectively, calculating the first pixel mean of the captured image and the second pixel mean of the multiple selected area images corresponding to each sub-image, so as to determine the pixel compensation value corresponding to each sub-image based on the first pixel mean and the second pixel mean, so as to compensate the captured image, realize the grayscale compensation at each splicing position of the captured image, thereby realizing the compensation of the entire captured image, and achieving the effect of balancing the image grayscale and removing the split screen phenomenon for the captured image. BRIEF DESCRIPTION OF THE DRAWINGS
[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.
[0039] Figure 1 A schematic diagram of an image acquisition area in a display screen is provided for related technology.
[0040] Figure 2 Schematic diagram of fingerprint image provided for related art.
[0041] Figure 3 A flowchart of an image processing method provided for an exemplary embodiment of the present application.
[0042] Figure 4 This is a schematic diagram of a fingerprint image processed by an image processing method according to an exemplary embodiment of the present application.
[0043] Figure 5 A flowchart of an image processing method provided by another exemplary embodiment of the present application.
[0044] Figure 6 A schematic diagram of the positional relationship between the image acquisition area and the acquired image provided in an exemplary embodiment of the present application.
[0045] Figure 7 for Figure 6 Schematic diagram of the acquisition unit provided in.
[0046] Figure 8 A schematic diagram of the positional relationship between an image acquisition area and a captured image provided by another exemplary embodiment of the present application.
[0047] Fig. 9 A schematic diagram of the positional relationship between an image acquisition area and a captured image provided by another exemplary embodiment of the present application.
[0048] Fig.10 for Fig. 9Schematic diagram of the acquisition unit provided in.
[0049] Fig.11 A block diagram of an image processing apparatus provided by an exemplary embodiment of the present application.
[0050] Fig.12 A block diagram of an image processing device provided for an exemplary embodiment of the present application. DETAILED DESCRIPTION
[0051] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0052] like Figure 1 As shown, taking the acquisition of fingerprint images under a large area screen as an example, when designing the image acquisition area, a rectangular block of a fixed size is usually used as the acquisition unit. The entire screen or part of the screen can be used as the effective acquisition area, i.e., the image acquisition area. The effective acquisition area is an array of several acquisition units. For fingerprint acquisition, for example, during use, when the fingerprint is detected, the images of several units covered by the fingerprint in the image acquisition area are collected in sequence, and then spliced into a complete fingerprint image. Due to differences in the electrical characteristics of the acquisition unit itself and environmental factors, the brightness of the image collected by each acquisition unit is different, resulting in a split screen phenomenon in the spliced fingerprint image. As shown Figure 2 As shown, the fingerprint image has obvious boundaries, resulting in a split screen phenomenon, which affects the visual effect and subsequent image processing.
[0053] As an optional implementation of the content disclosed in this application, the embodiment of this application discloses an image processing method, which is applicable to, but not limited to, the processing of fingerprint images under the screen and inside the screen, and is applicable to other technical fields and the situation of uneven image chromaticity caused by the block acquisition unit. Figure 3 As shown, Figure 3 This is a flowchart of an image processing method disclosed in an embodiment of the present application, the image processing method comprising:
[0054] Step S110: Acquire a captured image in an image capture area, where the image capture area includes a plurality of capture units, and the captured image is formed by splicing sub-images captured by at least some of the capture units.
[0055] like Figure 6 As shown, Figure 6The schematic diagram of the image acquisition area 100 is shown as an example. The image acquisition area 100 includes a plurality of acquisition units 200 distributed in an array. The plurality of acquisition units may be adjacent to each other to form an array structure. For example, the image acquisition area 100 may be an under-screen fingerprint acquisition array. Exemplarily, the image acquisition area 100 is rectangular in shape. The area of the image acquisition area 100 may be the same as the area of the display screen, or may be smaller than the area of the display screen. The image acquisition area 100 is an area for acquiring images on the display screen.
[0056] like Figure 6 As shown, the captured image includes an image to be identified located in the image capture area, such as a fingerprint image, a facial image, a head portrait, etc. The captured image can be spliced from sub-images captured by some of the capture units 200, or spliced from sub-images captured by all the capture units 200. In other words, the number of capture units 200 corresponding to the captured image is less than or equal to the number of all the capture units 200 in the image capture area. In this step, when capturing an image, the sub-images of several capture units 200 covered by the captured image can be captured in sequence, and then spliced in position order to obtain a complete captured image.
[0057] Step S120: Select a portion of each sub-image near the junction to obtain a plurality of selected area images corresponding to each sub-image. The junction corresponds to the common boundary of two adjacent acquisition units.
[0058] refer to Figure 6 When the sub-images collected by each collection unit 200 corresponding to the collection image are spliced, the common boundary of two adjacent collection units 200 is the junction of adjacent sub-images. Figure 6 As shown, taking the acquisition unit 200 at the upper left corner of the acquisition image as an example, the acquisition unit 200 has at least two boundaries connected to other acquisition units respectively. Therefore, there are at least two intersections between the acquisition unit 200 and other acquisition units, that is, there are at least two intersections between the sub-image acquired by the acquisition unit 200 and the sub-image acquired by the adjacent acquisition unit. Therefore, there are at least two intersections between the sub-image acquired by each acquisition unit. By selecting the partial image of each sub-image adjacent to the intersection, multiple selected area images corresponding to each sub-image can be obtained respectively.
[0059] Step S130: Calculate a first pixel mean value of the acquired image and a second pixel mean value of a plurality of selected area images corresponding to each sub-image.
[0060] In this step, the collected image is regarded as a complete image, and the pixel mean of the collected image can be determined based on all the pixels of the collected image, which is the first pixel mean. The pixel mean of the collected image refers to the average of the color values (such as grayscale value or RGB value) of all pixels in the collected image. Calculating the pixel mean of the collected image can help understand the overall brightness or color distribution of the entire image. In this step, the pixel mean of multiple selected area images corresponding to each sub-image is also calculated, which is the second pixel mean, so as to obtain the mean of the area image near the junction of each sub-image.
[0061] Step S140: Determine a pixel compensation value corresponding to each sub-image based on the first pixel mean value and the second pixel mean value to compensate the collected image.
[0062] In this step, after obtaining the first pixel mean and the second pixel mean, the pixel compensation value corresponding to each sub-image can be determined based on the first pixel mean and the second pixel mean, so as to compensate each sub-image using the corresponding pixel compensation value of each sub-image, thereby achieving grayscale compensation at each stitching position of the acquired image, thereby achieving compensation for the entire acquired image.
[0063] In this step, the pixel compensation value of each sub-image is determined based on the first pixel mean and the second pixel mean, so that the brightness of the entire collected image does not change significantly after compensation. When compensating each sub-image, the pixel compensation value corresponding to each sub-image is used to eliminate the split screen phenomenon between sub-images. Figure 4 The captured image shown in the figure will not cause image blur, and the grayscale of the captured image can be balanced and the split screen phenomenon can be removed to improve the quality of the output image.
[0064] The image processing method provided in the embodiment of the present application can solve the split-screen phenomenon caused by the splicing of images of different brightness, with fast speed and good effect. Specifically, by acquiring a captured image of the image acquisition area, a partial image of each sub-image near the junction is selected, and multiple selected area images corresponding to each sub-image are obtained respectively, and the first pixel mean of the captured image and the second pixel mean of the multiple selected area images corresponding to each sub-image are calculated, so as to determine the pixel compensation value corresponding to each sub-image based on the first pixel mean and the second pixel mean, so as to compensate the captured image and realize grayscale compensation at each splicing position of the captured image, thereby realizing compensation for the entire captured image, and achieving the effect of balancing the image grayscale and removing the split-screen phenomenon for the captured image.
[0065] As an optional implementation of the content disclosed in this application, the embodiment of this application discloses an image processing method, such as Figure 5 As shown, Figure 5This is a flow chart of an image processing method disclosed in an embodiment of the present application. In this embodiment, the number of acquisition units corresponding to the acquired image is consistent with the number of all acquisition units in the image acquisition area. The image processing method includes:
[0066] Step S210: Acquire a captured image in an image capture area, where the image capture area includes a plurality of capture units, and the captured image is formed by splicing sub-images captured by each capture unit.
[0067] like Figure 6 As shown, the image acquisition area 100 is taken as an example of the area of a portion of the display screen, wherein the number of acquisition units 200 corresponding to the acquired image is consistent with the number of acquisition units 200 corresponding to the image acquisition area 100, that is, the acquired image is the splicing of the sub-images acquired by all the acquisition units 200. In this embodiment, the acquired image includes a fingerprint image, Figure 6 As shown, each sub-image contains a partial fingerprint image.
[0068] Step S220: Select an area with a preset width from the boundary in the acquisition unit corresponding to each sub-image as a selected area, and obtain multiple selected areas corresponding to each acquisition unit.
[0069] refer to Figure 6 As shown, the captured image is composed of sub-images captured by 2*2 capture units 200, and each sub-image corresponds to one capture unit 200. In the process of capturing image splicing, there is a splicing boundary between two adjacent sub-images, and the splicing boundary is the junction between adjacent capture units 200, that is, the position where the two sub-images produce a split screen phenomenon. Therefore, in order to eliminate the problem of the split screen phenomenon, the area of the capture unit 200 corresponding to each sub-image with a preset width from the junction is used as the selected area to obtain multiple selected areas corresponding to each capture unit 200. The multiple selected areas can be regarded as the position where the capture unit 200 is prone to produce a split screen phenomenon, so as to determine the area with obvious difference in image brightness based on the multiple selected areas. .
[0070] refer to Figure 6 As shown, optionally, the junction includes a first junction 210 and a second junction 220 adjacent to each other, the first junction 210 is the common boundary of two adjacent collection units 200 in the first direction; the second junction 220 is the common boundary of two adjacent collection units 200 in the second direction. In this embodiment, the first direction may be a horizontal direction, and the first junction 210 may be regarded as a horizontal junction; the second direction may be a vertical direction, and the second junction 220 may be regarded as a vertical junction, that is, the first junction 210 is perpendicular to the second junction 220.
[0071] like Figure 7 As shown, for Figure 6 For the acquisition unit 200 in the upper left corner of the captured image, assuming that the width of the sub-image captured by the acquisition unit 200 is W pixels and the height is H pixels, the acquisition unit has a horizontal junction and a vertical junction, and the preset width is set for the acquisition unit, for example, L, in pixels, at the horizontal junction, for the horizontal junction, a rectangular area of L*H size can be taken as the selected area S11. For the vertical junction, a rectangular area of L*W size can be taken as the selected area S12, and the selected areas S11 and S12 are multiple selected areas corresponding to the acquisition unit 200.
[0072] Optionally, the preset width L of the selected area should not be too large. In order to better eliminate the split screen phenomenon, the preset width L can be set between 1 pixel and 20 pixels. The preset width L is set to 5 pixels, 10 pixels, 20 pixels, etc., and no specific limitation is made here.
[0073] It can be understood that the number of the multiple selected areas corresponding to any acquisition unit is at least greater than two. Figure 8 As shown, when the acquired image is formed by stitching together sub-images acquired by 3*3 acquisition units 200, for the acquisition unit located at the center position, the acquisition unit has adjacent acquisition units on both sides of the horizontal direction and on both sides of the vertical direction. Therefore, the acquisition unit located in the middle position has 2 horizontal junctions and 2 vertical junctions. The number of selected areas of the acquisition unit at the horizontal junctions is 2, and the number of selected areas of the acquisition unit at the vertical junctions is also 2. The number of selected areas corresponding to the acquisition unit can be 4, and the 4 selected areas can all be used as the selected areas of the acquisition unit.
[0074] refer to Figure 6 As shown, the areas of the selected regions on both sides of the first junction 210 can be the same or different. In order to better eliminate the split screen phenomenon at the junction, for example, for multiple acquisition units corresponding to the acquired image, the junction of adjacent acquisition units is taken as the center, and regions of the same area on both sides of the junction are selected as the selected regions. Figure 6 As shown, the areas of the selected areas on both sides of the first junction 210 are the same, such as the areas of the selected areas S11 and S21, and the selected area S21 is one of the selected areas of the collection unit adjacent to the collection unit located at the upper left corner in the horizontal direction. The areas of the selected areas on both sides of the second junction 220 may be the same, such as the areas of the selected areas S12 and S32, and the selected area S32 is one of the selected areas of the collection unit adjacent to the collection unit located at the upper left corner in the vertical direction.
[0075] Step S230: acquiring a partial sub-image corresponding to each selected area of each acquisition unit as a plurality of selected area images corresponding to each sub-image.
[0076] refer to Figure 6 and Figure 7 As shown, continuing to take the acquisition unit 200 located in the upper left corner as an example, the image acquired for the selected area of the acquisition unit 200 is a partial image of each sub-image, therefore, the partial sub-image of each selected area corresponding to the acquisition unit 200 is obtained, that is, the partial sub-image corresponding to the selected area S11 and the partial sub-image corresponding to the selected area S12 are determined, respectively as multiple selected area images corresponding to the acquisition unit 200. According to the above method, multiple selected area images of other acquisition units corresponding to the acquired images can be determined respectively.
[0077] Step S240: Calculate the first pixel mean of the acquired image.
[0078] After obtaining the acquired image, the pixel mean of the acquired image may be calculated based on all pixels of the acquired image as the first pixel mean. Exemplarily, calculating the first pixel mean of the acquired image may specifically include the following steps:
[0079] Step S241, determining the image width, image height and each pixel value of the collected image;
[0080] Step S241: Calculate based on the image width, the image height and each pixel value to obtain a pixel average value of the collected image as a first pixel average value.
[0081] refer to Figure 6 As shown, the captured image is spliced from the images captured by the corresponding multiple acquisition units, so the image width W0, image height H0 formed by the corresponding multiple acquisition units, and the pixel value of each pixel of the captured image can be determined. For example, the pixel average value M of the captured image can be calculated by the following calculation formula:
[0082]
[0083] Where W0 is the image width, H0 is the image height, and f(x, y) is the pixel value at the coordinate (x, y).
[0084] Step S250: Calculate the second pixel mean of the plurality of selected area images corresponding to each sub-image.
[0085] After determining the multiple selected area images corresponding to each sub-image, the pixel mean of the multiple selected area images corresponding to each sub-image may be determined in sequence for each sub-image as the second pixel mean. Exemplarily, calculating the pixel mean of the multiple selected area images corresponding to each sub-image may specifically include the following steps:
[0086] Step S251, respectively calculating the pixel average values of each partial sub-image corresponding to each sub-image to obtain a plurality of third pixel average values;
[0087] Step S252, determining the total number of selected areas;
[0088] Step S253: Calculate based on the total number of selected areas and multiple third pixel means to obtain the pixel average value of the multiple selected area images as the second pixel average value.
[0089] refer to Figure 7 As shown, for the acquisition unit 200, after determining the partial sub-images corresponding to the selected area S11 and the selected area S12, respectively, the pixel mean D1 corresponding to the selected area S11 is calculated according to the partial sub-image corresponding to the selected area S11, and the pixel mean D2 corresponding to the selected area S12 is calculated according to the partial sub-image corresponding to the selected area S12. For each selected area, the total number of pixels of the partial sub-image corresponding to the selected area and the pixel index of the partial sub-image corresponding to the selected area can be determined, so as to calculate the pixel mean value of the selected area using the following formula:
[0090]
[0091] Wherein, S is the total number of pixels of the partial sub-image corresponding to the selected area, and f(i) is the pixel index of the partial sub-image corresponding to the selected area.
[0092] refer to Figure 7 As shown, the number of selected areas corresponding to the acquisition unit is 2, therefore, the pixel average m of multiple selected area images can be calculated according to the pixel average D1 of the selected area S11, the pixel average D2 corresponding to the selected area S12, and the number of selected areas, for example, m = (D1 + D2) / 2, and the pixel average m is used as the second pixel average. According to the above calculation process, the second pixel average of multiple selected area images corresponding to each sub-image can be calculated.
[0093] Step S260: Determine a pixel compensation value corresponding to each sub-image based on the first pixel mean value and the second pixel mean value to compensate the collected image.
[0094] Exemplarily, the implementation process of this step may include the following steps:
[0095] Step S261, performing calculation according to the first pixel mean and the second pixel mean to obtain a pixel compensation value corresponding to each sub-image may include:
[0096] Step S262: Obtain the initial pixel value of each pixel of the sub-image.
[0097] Step S263: Compensate the pixels of each sub-image based on the pixel compensation value.
[0098] In this embodiment, the difference between the first pixel mean M and the second pixel mean m can be used as the pixel compensation value corresponding to each sub-image, and then the initial pixel value f(j) of each pixel of the acquisition unit corresponding to each sub-image is obtained, and then all pixels of each acquisition unit of the acquired image are traversed, and a unified pixel compensation value is used to compensate the pixel g(j) of each acquisition unit, thereby eliminating the split screen phenomenon and not causing image blur. Wherein, g(j)=f(j)+M―m,j∈[0...W*H], where f(j) is the initial pixel value of the pixel of the acquisition unit, and g(j) is the pixel value of the pixel of the acquisition unit after compensation.
[0099] Step S270: output the captured image.
[0100] As an optional implementation of the content disclosed in the present application, an embodiment of the present application discloses an image processing method. The image processing method provided by this embodiment is basically the same as the image processing method provided by the above embodiment, and the main difference is that in this embodiment, the number of acquisition units corresponding to the acquired image is inconsistent with the number of all acquisition units in the image acquisition area. In this embodiment, when the acquisition unit is composed of sub-images acquired by some acquisition units, that is, when the number of acquisition units corresponding to the acquired image is less than the number of all acquisition units, the image processing method Figure 1 The image processing method shown in the figure also includes:
[0101] The sub-images other than the captured image in the image capture area are compensated, and the captured image in the image capture area is output.
[0102] In this embodiment, the image captured in the image acquisition area includes the captured image and sub-images other than the captured image. The sub-images other than the captured image can be regarded as the background image of the image captured by the image acquisition area. In order to ensure that the image output by the entire image acquisition area does not have a split screen phenomenon, the image captured by the image acquisition area is taken as a complete image. The complete image includes the captured image and the background image other than the captured image. Therefore, in this embodiment, the entire image captured by the image acquisition area is processed, for example, the captured image and the background image can be compensated at the same time. Among them, the method of compensating the captured image is the same as the implementation method of the above embodiment, which will not be repeated here.
[0103] In this embodiment, the implementation method of compensating the sub-images other than the captured image in the image capture area is basically the same as the implementation method of compensating the captured image in the image capture area. Fig. 9 and Fig.10As shown, the image captured by the image acquisition area includes a captured image and a plurality of sub-images other than the captured image. For ease of expression, the captured image area in the image acquisition area is denoted as 300, and each sub-image other than the captured image can be denoted as a second sub-image, and one second sub-image corresponds to one acquisition unit 400.
[0104] Specifically, a partial image of each second sub-image near the junction is selected to obtain a plurality of selected area images corresponding to each sub-image, and the junction corresponds to the common boundary of two adjacent acquisition units. Fig. 9 As shown, for the acquisition unit 400 located in the upper left corner, assuming that the width of the second sub-image acquired by the acquisition unit 400 is W pixels and the height is H pixels, the acquisition unit 400 has a horizontal junction and a vertical junction. For the acquisition unit 400, in pixels, for the horizontal junction, a rectangular area of size P*H can be taken as the selected area AA11. For the vertical junction, a rectangular area of size P*W can be taken as the selected area AA12, and the selected areas AA11 and AA12 are multiple selected areas corresponding to the acquisition unit 400.
[0105] Then, the fourth pixel mean of the image collected by the image collection area and the fifth pixel mean of the plurality of selected area images corresponding to each second sub-image are calculated. Fig. 9 and Fig.10 The entire image of the image acquisition area is spliced together by the images acquired by the corresponding multiple acquisition units. Therefore, the image width W1 and image height H1 of the image formed by all acquisition units, as well as the pixel value of each pixel of the image acquired by the entire image acquisition area can be determined. According to the above image width W1, image height H1, and the pixel value of each pixel of the image acquired by the entire image acquisition area, the pixel average value of the image acquired by the image acquisition area is calculated as the fourth pixel average value.
[0106] Then, after determining the multiple selected area images corresponding to each second sub-image, the pixel mean of the multiple selected area images corresponding to each second sub-image can be determined in turn as the fifth pixel mean for each second sub-image. Finally, the pixel compensation value corresponding to each second sub-image can be determined based on the fourth pixel mean and the fifth pixel mean to compensate for the multiple second sub-images respectively.
[0107] In this embodiment, the image captured in the image acquisition area includes the captured image and sub-images other than the captured image. By acquiring the image captured by the image acquisition area, a partial image of each sub-image in the image acquisition area near the junction is selected to obtain a plurality of selected area images corresponding to each sub-image, respectively. The pixel mean of the entire image and the pixel mean of the plurality of selected area images corresponding to each sub-image are calculated to determine the pixel compensation value corresponding to each sub-image, so as to compensate the captured image and the sub-images other than the captured image, thereby achieving compensation for the entire image, and achieving grayscale compensation for each splicing position of the image captured in the image acquisition area, so as to achieve the effect of balancing the image grayscale and removing the split screen phenomenon.
[0108] As an optional implementation of the content disclosed in this application, the embodiment of this application discloses an image processing device, such as Fig.11 As shown, Fig.11 This is a block diagram of an image processing device disclosed in an embodiment of the present application, and the image processing device includes:
[0109] An acquisition unit 10 is used to acquire an acquired image in an image acquisition area, wherein the image acquisition area includes a plurality of acquisition units, and the acquired image is formed by splicing sub-images acquired by at least some of the acquisition units;
[0110] A selection unit 20 is used to select a partial image of each sub-image near a junction, and obtain a selected area image corresponding to each sub-image, wherein the junction is a common boundary of two adjacent acquisition units;
[0111] A calculation unit 30, configured to calculate a first pixel mean of the collected image and a second pixel mean of a plurality of selected area images corresponding to each sub-image;
[0112] The compensation unit 40 is used to determine a pixel compensation value corresponding to each sub-image based on the first pixel mean value and the second pixel mean value, so as to compensate the collected image.
[0113] Fig.12 is a block diagram of an image processing device 700 according to an exemplary embodiment. For example, the image processing device 700 may be provided as a terminal device. Fig.12 The image processing device 700 includes a processor 701, and the number of processors can be set to one or more as needed. The image processing device 700 also includes a memory 702, which is used to store instructions that can be executed by the processor 701, such as application programs. The number of memories can be set to one or more as needed. The application programs stored therein can be one or more. The processor 701 is configured to execute instructions to perform the above-mentioned image processing method.
[0114] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, devices (equipment), or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media in which a computer-usable program code is included. Computer storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data), including but not limited to RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device, or any other medium that can be used to store desired information and can be accessed by a computer, etc. In addition, it is well known to those skilled in the art that communication media generally include computer-readable instructions, data structures, program modules or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.
[0115] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is provided, such as a memory 702 including instructions, and the instructions can be executed by a processor 701 of an image processing device 700 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.
[0116] A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of an image processing device, enables the image processing device to perform the above-mentioned image processing method.
[0117] The present application is described with reference to the flowcharts and / or block diagrams of the methods, apparatuses (devices) and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable image processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable image processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0118] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0120] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0121] The above embodiments only express several implementation methods of this specification, and the descriptions are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent application. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of this specification, which all belong to the protection scope of this specification. Therefore, the protection scope of the patent of this specification shall be based on the attached claims.
Claims
1. An image processing method, characterized in that: The image processing method comprises: Acquire a captured image in an image acquisition area, wherein the image acquisition area includes a plurality of acquisition units, and the captured image is formed by splicing sub-images acquired by at least some of the acquisition units; Selecting a partial image of each sub-image adjacent to a junction, and obtaining a plurality of selected area images corresponding to each sub-image, wherein the junction corresponds to a common boundary of two adjacent acquisition units; Calculating a first pixel mean value of the acquired image and a second pixel mean value of a plurality of selected area images corresponding to each sub-image; A pixel compensation value corresponding to each sub-image is determined based on the first pixel mean value and the second pixel mean value to compensate the collected image.
2. The image processing method according to claim 1, characterized in that: Calculating the first pixel mean of the acquired image includes: Determining an image width, an image height, and a pixel value of each pixel of the acquired image; A calculation is performed based on the image width, the image height and the pixel value of each pixel to obtain a pixel average value of the collected image as a first pixel average value.
3. The image processing method according to claim 1 or 2, characterized in that: Selecting a partial image of each sub-image adjacent to the boundary to obtain a plurality of selected area images corresponding to each sub-image comprises: Selecting an area of the acquisition unit corresponding to each sub-image that is a preset width away from the junction as a selected area, and obtaining a plurality of selected areas corresponding to each acquisition unit; Acquire a partial image corresponding to each selected area of each acquisition unit as a plurality of selected area images corresponding to each sub-image; Optionally, the junction includes a first junction and a second junction adjacent to each other, the first junction is a common boundary of two adjacent collection units in a first direction, and the second junction is a common boundary of two adjacent collection units in a second direction; Optionally, the first junction is perpendicular to the second junction.
4. The image processing method according to claim 3, characterized in that: Selecting an area of the acquisition unit corresponding to each sub-image with a preset width from the junction as the selected area includes: The selected area is distributed in the same area in two adjacent collection units, and the two adjacent collection units are located on both sides of the junction; Optionally, the preset width of the selected area is between 1 pixel and 20 pixels.
5. The image processing method according to claim 3, characterized in that: Calculating the second pixel mean of the plurality of selected area images corresponding to each sub-image comprises: Calculating the pixel average value of each of the partial sub-images corresponding to each sub-image respectively to obtain a plurality of third pixel average values; determining a total number of the selected areas; The pixel average value of the images of the plurality of selected regions is obtained as the second pixel average value by performing calculation based on the total number of the selected regions and the plurality of third pixel average values.
6. The image processing method according to claim 5, characterized in that: Determining a pixel compensation value corresponding to each sub-image based on the first pixel mean value and the second pixel mean value to compensate the acquired image includes: Calculating according to the first pixel mean value and the second pixel mean value to obtain a pixel compensation value corresponding to each sub-image; Get the initial pixel value of each sub-image pixel; Based on the pixel compensation value, the pixels of each sub-image are compensated.
7. The image processing method according to claim 1, characterized in that: When the acquisition unit is composed of sub-images acquired by some of the acquisition units, the image processing method further includes: Compensation is performed on sub-images other than the acquired image in the image acquisition area.
8. An image processing device, characterized in that: The image processing device comprises: An acquisition unit, used for acquiring an acquired image in an image acquisition area, wherein the image acquisition area includes a plurality of acquisition units, and the acquired image is formed by splicing sub-images acquired by at least some of the acquisition units; A selection unit, used for selecting a partial image of each sub-image adjacent to a junction, and obtaining a selected area image corresponding to each sub-image, wherein the junction is a common boundary of two adjacent acquisition units; A calculation unit, used for calculating a first pixel mean of the collected image and a second pixel mean of a plurality of selected area images corresponding to each sub-image; A compensation unit is used to determine a pixel compensation value corresponding to each sub-image based on the first pixel mean value and the second pixel mean value, so as to compensate the collected image.
9. An image processing device, comprising a processor, a memory and a computer program stored in the memory, characterized in that: When the processor executes the computer program, the steps of the image processing method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the steps of the image processing method according to any one of claims 1 to 7 are implemented.