Image processing device and method, chip and electronic equipment

Abstract

The invention discloses an image processing device and method, a chip and electronic equipment, and belongs to the technical field of display. The device comprises a receiving interface and an image signal processor. The receiving interface is used for acquiring a first image, and the first image comprises a plurality of pixel points; the image signal processor is used for determining a pixel window with any pixel point in the multiple pixel points as the center based on the first image and determining effective pixel points in the pixel window, and the pixel difference value between the effective pixel points and any pixel point is not larger than a target threshold value. And the image signal processor is also used for determining a processing result of any pixel point according to the effective pixel points in the pixel window. And the image signal processor is also used for determining a second image according to the processing result of each pixel point. The method can enable the second image to keep the brightness relation of the first image, and improves the image quality of the second image.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of display technology, and in particular to an image processing device, method, chip and electronic device. Background Art

[0002] In the field of display technology, electronic devices can acquire images and display them on a display screen. The image acquisition process can be understood as follows: light from the external scene is projected onto the sensor through the lens, and the sensor converts the light signal into an electrical signal. The electrical signal is converted into a digital signal after analog-to-digital conversion, and the image is determined based on the digital signal. In the image acquisition process, due to the influence of factors such as the sensor, lighting, and atmosphere, noise will inevitably be introduced into the image. This noise not only affects the visual effect of the image, but also interferes with subsequent image analysis and processing. Based on this, image processing is a very important task. Summary of the invention

[0003] The present application provides an image processing device, method, chip and electronic device, which can be used to solve the problems in the related technology. The technical solution includes the following contents.

[0004] In one aspect, an image processing device is provided, the device comprising a receiving interface and an image signal processor;

[0005] The receiving interface is used to acquire a first image, where the first image includes a plurality of pixels;

[0006] The image signal processor is used to determine a pixel window centered on any one of the multiple pixel points based on the first image, determine a valid pixel point in the pixel window, and a pixel difference between the valid pixel point and any one of the pixel points is not greater than a target threshold;

[0007] The image signal processor is further used to determine the processing result of any pixel point according to the valid pixel points in the pixel window;

[0008] The image signal processor is further used to determine the second image according to the processing results of each pixel point.

[0009] In a possible implementation manner, before determining the valid pixel points in the pixel window, the method further includes:

[0010] Determining a dispersion parameter of the first image, where the dispersion parameter represents a dispersion degree of pixel values ​​of each pixel point;

[0011] The target threshold is determined according to the dispersion parameter.

[0012] In a possible implementation manner, before determining the valid pixel points in the pixel window, the method further includes:

[0013] Acquire a first exposure of the first image and a plurality of reference data sets, wherein the reference data sets include reference exposures and reference thresholds;

[0014] Determining weights of the reference data sets according to the first exposure and reference exposures in the reference data sets;

[0015] The target threshold is determined according to the weights of the respective reference data sets and the reference thresholds in the respective reference data sets.

[0016] In a possible implementation, the pixel window includes a plurality of valid pixel points; and determining the processing result of any one pixel point according to the valid pixel points in the pixel window includes:

[0017] Dividing the multiple valid pixel points to obtain multiple pixel sub-windows, each pixel sub-window including at least one valid pixel point;

[0018] Determine an updated pixel value of any pixel point through any pixel sub-window among the multiple pixel sub-windows;

[0019] Based on each updated pixel value of the any pixel point, a processing result of the any pixel point is determined.

[0020] In a possible implementation, dividing the multiple valid pixel points to obtain multiple pixel sub-windows includes:

[0021] Valid pixel points belonging to a pixel sub-window are screened out from the multiple valid pixel points, wherein the valid pixel points belonging to the pixel sub-window are located on a reference line or on one side of the reference line, and the reference line is a straight line passing through any pixel point in the pixel window.

[0022] In a possible implementation, determining the processing result of any pixel point based on each updated pixel value of any pixel point includes:

[0023] Determine, from the updated pixel values ​​of any one of the pixels, a target pixel value having a minimum pixel difference with the pixel value of any one of the pixels;

[0024] Based on the target pixel value, a processing result of any one pixel is determined.

[0025] In a possible implementation, the processing result of any pixel point includes a denoising result of the any pixel point; and determining the processing result of any pixel point based on the target pixel value includes:

[0026] Determine the difference between the pixel value of any one pixel and the target pixel value;

[0027] The denoising result of any one pixel is determined according to the denoising coefficient, the difference and the target pixel value.

[0028] In a possible implementation, the processing result of any pixel point includes a brightness balance result of the any pixel point; and determining the processing result of any pixel point based on the target pixel value includes:

[0029] Determine the difference between the pixel value of any one pixel and the target pixel value;

[0030] A brightness balance result of any pixel point is determined according to the brightness balance coefficient, the difference and the pixel value of any pixel point.

[0031] In a possible implementation manner, the first image corresponds to multiple channels, one pixel in the first image corresponds to one channel, and any pixel and the valid pixel correspond to the same channel.

[0032] In another aspect, an image processing method is provided, the method comprising:

[0033] Acquire a first image, where the first image includes a plurality of pixels;

[0034] Determine, based on a pixel window centered on any one of the multiple pixel points in the first image, a valid pixel point in the pixel window, wherein a pixel difference between the valid pixel point and any one of the pixel points is not greater than a target threshold;

[0035] Determine a processing result of any one pixel point according to valid pixel points in the pixel window;

[0036] A second image is determined according to the processing results of each pixel point.

[0037] In a possible implementation manner, before determining the valid pixel points in the pixel window, the method further includes:

[0038] Determining a dispersion parameter of the first image, where the dispersion parameter represents a dispersion degree of pixel values ​​of each pixel point;

[0039] The target threshold is determined according to the dispersion parameter.

[0040] In a possible implementation manner, before determining the valid pixel points in the pixel window, the method further includes:

[0041] Acquire a first exposure of the first image and a plurality of reference data sets, wherein the reference data sets include reference exposures and reference thresholds;

[0042] Determining weights of the reference data sets according to the first exposure and reference exposures in the reference data sets;

[0043] The target threshold is determined according to the weights of the respective reference data sets and the reference thresholds in the respective reference data sets.

[0044] In a possible implementation, the pixel window includes a plurality of valid pixel points; and determining the processing result of any one pixel point according to the valid pixel points in the pixel window includes:

[0045] Dividing the multiple valid pixel points to obtain multiple pixel sub-windows, each pixel sub-window including at least one valid pixel point;

[0046] Determine an updated pixel value of any pixel point through any pixel sub-window among the multiple pixel sub-windows;

[0047] Based on each updated pixel value of the any pixel point, a processing result of the any pixel point is determined.

[0048] In a possible implementation, dividing the multiple valid pixel points to obtain multiple pixel sub-windows includes:

[0049] Valid pixel points belonging to a pixel sub-window are screened out from the multiple valid pixel points, wherein the valid pixel points belonging to the pixel sub-window are located on a reference line or on one side of the reference line, and the reference line is a straight line passing through any pixel point in the pixel window.

[0050] In a possible implementation, determining the processing result of any pixel point based on each updated pixel value of any pixel point includes:

[0051] Determine, from the updated pixel values ​​of any one of the pixels, a target pixel value having a minimum pixel difference with the pixel value of any one of the pixels;

[0052] Based on the target pixel value, a processing result of any one pixel is determined.

[0053] In a possible implementation, the processing result of any pixel point includes a denoising result of the any pixel point; and determining the processing result of any pixel point based on the target pixel value includes:

[0054] Determine the difference between the pixel value of any one pixel and the target pixel value;

[0055] The denoising result of any one pixel is determined according to the denoising coefficient, the difference and the target pixel value.

[0056] In a possible implementation, the processing result of any pixel point includes a brightness balance result of the any pixel point; and determining the processing result of any pixel point based on the target pixel value includes:

[0057] Determine the difference between the pixel value of any one pixel and the target pixel value;

[0058] A brightness balance result of any pixel point is determined according to the brightness balance coefficient, the difference and the pixel value of any pixel point.

[0059] In a possible implementation manner, the first image corresponds to multiple channels, one pixel in the first image corresponds to one channel, and any pixel and the valid pixel correspond to the same channel.

[0060] On the other hand, a chip is provided, wherein the chip includes the above-mentioned image processing device.

[0061] On the other hand, an electronic device is provided, comprising the above chip.

[0062] The technical solution provided by this application brings at least the following beneficial effects:

[0063] The image processing device provided by the present application determines a pixel window centered on a pixel point in the first image, and determines the processing result of the center pixel point through the effective pixel points in the pixel window, thereby eliminating invalid pixels in the pixel window that are greatly different from the center pixel point, and avoiding the diffusion of the pixel values ​​of the invalid pixels to the center pixel point in the subsequent processing process, so that the light and dark relationship between the processed center pixel point and the surrounding pixels is consistent with the original light and dark relationship in the first image, thereby improving the accuracy of the processing result of the center pixel point. Moreover, the processing result of the center pixel point is determined through the effective pixel points in the pixel window of the center pixel point, thereby optimizing the pixel value of the center pixel point. Subsequently, the second image is determined according to the processing results of each pixel point. On the one hand, the second image can retain the light and dark relationship of the first image, and on the other hand, the first image can be optimized to obtain the second image, thereby improving the image quality of the second image. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0065] Figure 1 is a structural schematic diagram of an image processing device provided in an embodiment of the present application;

[0066] Figure 2 is a schematic diagram of a pixel window provided in an embodiment of the present application;

[0067] Figure 3 is a schematic diagram of another pixel window provided in an embodiment of the present application;

[0068] Figure 4 is a schematic diagram of a pixel sub-window provided in an embodiment of the present application;

[0069] Figure 5 is a schematic diagram of an image processing result provided in an embodiment of the present application;

[0070] Figure 6 is a schematic diagram of another image processing result provided in an embodiment of the present application;

[0071] Figure 7 is a flow chart of an image processing method provided by an embodiment of the present application;

[0072] Figure 8 It is a schematic diagram of the structure of a chip provided in an embodiment of the present application;

[0073] Fig. 9 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0074] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0075] It should be noted that the terms "first", "second", etc. in this application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0076] The present application embodiment provides an image processing device, such as Figure 1 As shown, the device includes a receiving interface 10 and an image signal processor (ISP) 20. The black circle in the structural figure is used to mark the input end, and the white circle is used to mark the output end. Figure 1 As shown, the output end of the receiving interface 10 is connected to the input end of the image signal processor 20 .

[0077] The receiving interface 10 is used to obtain a first image, and the first image includes a plurality of pixels.

[0078] The user may input the first image into the electronic device, or the electronic device may obtain the first image through the Internet, or the electronic device may obtain the first image through an image acquisition device, etc. The electronic device includes an image processing device, and the image processing device includes a receiving interface 10. After the electronic device obtains the first image, when the first image needs to be processed, the first image is obtained through the receiving interface 10.

[0079] The embodiment of the present application does not limit the type of the first image. For example, the first image may include at least one of an RGB image, a YUV image, and a RAW image. Among them, the RGB image uses three color channels of red (Red, R), green (Green, G), and blue (Blue, B) to express the color, brightness and other information of the image. Among them, each pixel in the RGB image corresponds to the pixel value of the three color channels of R, G, and B. The YUV image uses two channels of luminance (Luminance, Luma) and chrominance (Chrominance, Chroma) to express the brightness, hue, saturation and other information of the image. Among them, Y represents brightness, and U and V represent chrominance. Moreover, each pixel in the YUV image corresponds to the pixel value of the three channels of Y, U, and V. The RAW image uses three color channels of R, G, and B to express the color, brightness and other information of the image. Among them, each pixel in the RAW image corresponds to a single channel. That is to say, the RAW image corresponds to the three color channels of R, G, and B, but one pixel in the RAW image corresponds to the R channel, the G channel, or the B channel, and there are multiple pixels in the RAW image corresponding to the same channel.

[0080] like Figure 2 As shown, Figure 2 (1) in the figure shows a local area of ​​a RAW image. For ease of description, in the following, the pixels of the R channel are referred to as R pixels, the pixels of the B channel are referred to as B pixels, and the pixels of the G channel are referred to as G pixels. Among them, the G pixels located in the same row of the RAW image and adjacent to the R pixels are recorded as Gr pixels, and the G pixels located in the same row of the RAW image and adjacent to the B pixels are recorded as Gb pixels. In other words, the Gr pixels and the Gb pixels are actually both G pixels. Based on this, Figure 2 As can be seen from (1) in FIG. 1 , the RAW image includes R pixels, G pixels and B pixels, and the G pixels are adjacent to the R pixels or the B pixels. There are multiple G pixels, R pixels and B pixels.

[0081] The image signal processor 20 is used to determine a pixel window centered on any one of the multiple pixel points based on the first image, determine a valid pixel point in the pixel window, and the pixel difference between the valid pixel point and any pixel point is not greater than a target threshold.

[0082] For each pixel of the first image, if the pixel is located in the edge area of ​​the first image, the image can be expanded by mirror flipping the first image, so as to determine the pixel window in the expanded image with the pixel as the center; if the pixel is not located in the edge area of ​​the first image, the pixel window is directly determined in the first image with the pixel as the center. The size of the pixel window can be flexibly changed according to the situation, as long as the size of the pixel window is smaller than the size of the first image. For example, the size of the pixel window can be 5×5 or 3×3, etc. Figure 2 As shown in (1) in FIG. 1 , a pixel window with a size of 5×5 and centered at the Gr pixel point in the second row and second column (ie, the Gr pixel point in the black frame) can be determined from the RAW image.

[0083] In this example, the pixel point at the center of the pixel window is referred to as the central pixel point, that is, the image signal processor 20 determines the pixel window of the central pixel point based on the first image. The pixel window includes a plurality of pixel points, and these pixel points include the central pixel point. Figure 2 As shown in (1), the 5×5 pixel window includes a central pixel, and the central pixel is the Gr pixel in the second row and second column (ie, the Gr pixel in the black frame).

[0084] For any pixel in the pixel window, if the pixel difference between the pixel and the central pixel is not greater than the target threshold, the pixel is a valid pixel; if the pixel difference between the pixel and the central pixel is greater than the target threshold, the pixel is an invalid pixel. In this way, at least one valid pixel can be determined from the pixel window, and these valid pixels include the central pixel.

[0085] Optionally, the first image corresponds to multiple channels, one pixel in the first image corresponds to one channel, and any pixel and effective pixel correspond to the same channel. Taking the first image as a RAW image as an example, the central pixel and the effective pixel are both R pixels, or are both G pixels, or are both B pixels. In practical applications, in addition to corresponding to the same channel and the pixel difference being no greater than the target threshold, the central pixel and the effective pixel may also meet other conditions. For example, the channel distribution around the central pixel and the effective pixel is consistent, or the central pixel and the effective pixel are adjacent to each other, and so on.

[0086] For example, Figure 2 As shown, it can be obtained from Figure 2 Determine in the pixel window shown in (1) Figure 2In this example, the effective pixel and the central pixel are both Gr pixels, and they correspond to the same channel. The pixels above and below are B pixels, and the pixels on the left and right are R pixels. In other words, the channel distribution around the two pixels is consistent.

[0087] Another example Figure 3 As shown, you can start with Figure 3 Determine in the pixel window shown in (1) Figure 3 The area shown in (2) in the figure, then, from Figure 3 Determine in the area shown in (2) Figure 3 In this example, the central pixel is the Gr pixel, and the valid pixel includes the Gr pixel and the Gb pixel. Since the Gb pixel and the Gr pixel both correspond to the G channel, the central pixel and the valid pixel also correspond to the same channel, and the central pixel and the valid pixel are adjacent to each other.

[0088] The embodiment of the present application does not limit the method for determining the target threshold. That is, in practical applications, there may be multiple methods for determining the target threshold. Two possible implementation methods are shown below.

[0089] In implementation mode A, before determining the valid pixel points in the pixel window, the method further includes: determining a dispersion parameter of the first image, where the dispersion parameter represents the dispersion degree of the pixel values ​​of each pixel point; and determining a target threshold value according to the dispersion parameter.

[0090] The embodiments of the present application do not limit the dispersion parameter. For example, the dispersion parameter may be a standard deviation or a variance. Variance is a statistic that measures the degree of dispersion of a set of data, and is defined as the average of the squares of the differences between each data and the mean. The standard deviation is another statistic that measures the degree of dispersion of a set of data, and is defined as the arithmetic square root of the variance. Based on this, the pixel values ​​of each pixel in the first image are regarded as a set of data, and the standard deviation or variance can be calculated based on the first image. Afterwards, the target threshold is determined based on the standard deviation or variance. For example, the target threshold N th It is N times the standard deviation σ (N is a positive number). The accuracy of the target threshold can be improved by determining the target threshold through the dispersion parameter of the first image.

[0091] Taking the denoising of a first image as an example, the first image includes noise. According to the implementation method of the embodiment of the present application, the first image can be denoised to obtain a second image. In general, most of the noise in an image is additive noise, which is generally considered to be spatially uncorrelated and has a constant power spectrum. Due to these characteristics, the noise on the image presents a Gaussian distribution N(0,σ 2 ), where σ represents the standard deviation. Based on this, the first image satisfies: p = pnf +N(0,σ 2 ), where p represents the distribution satisfied by the first image, and p nf Characterize the distribution satisfied by the second image, N(0,σ 2 ) characterizes the distribution of noise satisfaction.

[0092] Based on the 2σ theory of Gaussian distribution, the probability of the value being distributed between (μ-2σ, μ+2σ) is 0.9544, that is, about 95.5% of the data will be distributed within two standard deviations around the mean. Based on this, the standard deviation of the first image can be multiplied by 2 to obtain the target threshold N th .

[0093] In implementation method B, before determining the valid pixel points in the pixel window, it also includes: acquiring a first exposure of the first image and multiple reference data sets, the reference data sets including a reference exposure and a reference threshold; determining the weight of each reference data set based on the first exposure and the reference exposure in each reference data set; determining the target threshold based on the weight of each reference data set and the reference threshold in each reference data set.

[0094] In an embodiment of the present application, the image signal processor 20 can obtain a reference data set corresponding to multiple reference images, and the reference data set includes a reference exposure and a reference threshold. The reference exposure represents the exposure of the reference image, and the exposure refers to the degree to which the camera's photosensitive element is exposed to light, that is, the amount of light received by the photosensitive element. The level of exposure directly affects the brightness of the image. The higher the exposure, the brighter the image, and the lower the exposure, the darker the image. The reference threshold is the threshold used when screening valid pixels in the reference image, and the method for determining the reference threshold is not limited here. By way of example, the reference threshold corresponding to the reference image can be determined based on manual experience, or the reference threshold corresponding to the reference image can be determined according to the principle of implementation method A.

[0095] In this example, the image signal processor 20 can obtain the first exposure of the first image, and the method for obtaining the first exposure is not limited here. Then, the image signal processor 20 calculates the difference between each reference exposure and the first exposure, and determines the weight according to the difference, and the difference is negatively correlated with the weight, that is, the larger the difference, the lower the weight.

[0096] Multiply the weight and reference threshold in each reference data set, and add the multiplication results of each reference data set to obtain the target threshold. For example, there are two reference data sets, the weight of each reference data set is 0.5, and the reference thresholds in each reference data set are N1 and N2 respectively, then the target threshold N th=0.5×(N1+N2). By determining the target threshold corresponding to the first exposure level through the reference thresholds corresponding to the reference exposure levels, the target threshold is quickly interpolated, the efficiency of determining the target threshold is improved, and thus the image processing efficiency is improved.

[0097] After determining the target threshold N th Afterwards, we can calculate the target threshold N based on th Determine the pixel value range (pN) to which the effective pixel point of the central pixel belongs th ,p+N th ), p represents the pixel value of the central pixel. For each pixel in the pixel window, according to Determine the label of each pixel. ij Represents the pixel point at the i-th row and j-th column in the pixel window, flag ij Characterize pixel point p ij Among them, flag ij =1, representing pixel p ij For valid pixels, if flag ij =0, representing pixel p ij Invalid pixel.

[0098] In this way, the label of each pixel in the pixel window can be determined, so that invalid pixels can be excluded according to the label and valid pixels can be retained.

[0099] The image signal processor 20 is further configured to determine a processing result of any pixel point according to valid pixel points in the pixel window.

[0100] The present application embodiment does not limit the processing method. For example, Determine the processing result of the center pixel I i ′ , where Ω i The pixel window representing the central pixel, q j Represents the pixel value of the jth valid pixel in the pixel window, w ij represents the weight of the jth valid pixel. Optionally, w ij Negatively correlated with the distance between the jth effective pixel and the center pixel in the pixel window. In other words, the closer the jth effective pixel is to the center pixel, the greater the weight of the jth effective pixel.

[0101] It can be seen from the above processing method that the processing result of the central pixel point is the weighted calculation result of the pixel values ​​of each valid pixel point in the pixel window. In practical applications, the processing result of the central pixel point can also be determined in other ways.

[0102] In an exemplary embodiment, the pixel window includes a plurality of valid pixel points. According to the valid pixel points in the pixel window, determining the processing result of any pixel point includes the following steps S1 to S3.

[0103] Step S1, dividing a plurality of valid pixel points to obtain a plurality of pixel sub-windows, each pixel sub-window including at least one valid pixel point.

[0104] The present application embodiment does not limit the division method of effective pixels. Figure 4 As shown in (a), the valid pixel point located in the upper left corner of the pixel window is divided into a pixel sub-window, and the Figure 4 Similarly, the valid pixel point located at the upper right corner of the pixel window is divided into a pixel sub-window, and the obtained Figure 4 The pixel sub-window shown in (2) of (a) in FIG. Divide the valid pixel point located at the lower left corner of the pixel window into a pixel sub-window, and obtain Figure 4 The pixel sub-window shown in (3) of (a) in FIG. Divide the valid pixel point located at the lower right corner of the pixel window into a pixel sub-window, and obtain Figure 4 The effective pixel points located above the pixel window are divided into a pixel sub-window to obtain Figure 4 The effective pixel points located at the bottom of the pixel window are divided into a pixel sub-window to obtain Figure 4 The effective pixel points on the left side of the pixel window are divided into a pixel sub-window to obtain Figure 4 The effective pixel points on the right side of the pixel window are divided into a pixel sub-window to obtain Figure 4 The pixel sub-window shown in (8) of (a) in FIG. 8 , wherein the white square represents the valid pixel points belonging to the pixel sub-window, and the black square represents the valid pixel points not belonging to the pixel sub-window.

[0105] Optionally, step S1 includes: screening out valid pixel points belonging to a pixel sub-window from multiple valid pixel points, the valid pixel points belonging to a pixel sub-window are located on a reference line or on one side of the reference line, and the reference line is a straight line passing through any pixel point in the pixel window.

[0106] Since any pixel is the center pixel, the straight line passing through the center pixel in the pixel window is the reference line, which can be a symmetry line, a fold line, a diagonal line, etc. Figure 4 As shown in (b), the straight line passing through the center pixel point in the pixel window is a diagonal line.

[0107] The image signal processor 20 may determine each valid pixel point located on the straight line and on one side of the straight line in the pixel window as a pixel sub-window. Figure 4 As shown in (b) of FIG. 1 , in this example, the image signal processor 20 can determine the diagonal line from the lower left to the upper right based on the pixel window, and determine the valid pixel points on the diagonal line and the valid pixel points above the diagonal line as a pixel sub-window. Figure 4 From the pixel sub-window shown in (1) in (a), it can be seen that this pixel sub-window adds valid pixel points in the upper right corner and the lower left corner of the pixel window. Similarly, the valid pixel points on the diagonal line and the valid pixel points below the diagonal line are determined as another pixel sub-window. Compare this pixel sub-window with Figure 4 From the pixel sub-window shown in (4) in (a), it can be seen that this pixel sub-window also adds valid pixel points in the upper right corner and the lower left corner of the pixel window.

[0108] Optionally, the straight line passing through the central pixel point includes the horizontal fold line, the vertical fold line, the first diagonal line from the lower left to the upper right, and the second diagonal line from the lower right to the upper left of the pixel window. Figure 4 As shown in (c) in FIG. 1 , the valid pixel points on the first diagonal line in the pixel window and the valid pixel points above the first diagonal line are divided into a pixel sub-window, and the Figure 4 Similarly, the valid pixel points on the second diagonal line in the pixel window and the valid pixel points above the second diagonal line are divided into one pixel sub-window, and the obtained pixel sub-window is Figure 4 The effective pixel points on the second diagonal line in the pixel window and the effective pixel points below the second diagonal line are divided into one pixel sub-window, and the pixel sub-window is obtained. Figure 4 The effective pixel points on the first diagonal line in the pixel window and the effective pixel points below the first diagonal line are divided into one pixel sub-window, and the Figure 4 The effective pixel points located on the horizontal fold line in the pixel window and the effective pixel points above the horizontal fold line are divided into a pixel sub-window to obtain Figure 4 The effective pixel points located on the horizontal fold line in the pixel window and the effective pixel points below the horizontal fold line are divided into a pixel sub-window to obtain Figure 4The effective pixel points on the vertical fold line in the pixel window and the effective pixel points on the left side of the vertical fold line are divided into a pixel sub-window to obtain Figure 4 The effective pixel points on the vertical fold line in the pixel window and the effective pixel points on the right side of the vertical fold line are divided into a pixel sub-window to obtain Figure 4 The pixel sub-window shown in (8) in (c) of FIG. 8 , wherein the white square represents the valid pixel points belonging to the pixel sub-window, and the black square represents the valid pixel points not belonging to the pixel sub-window.

[0109] contrast Figure 4 As can be seen from (a) and (c) in FIG. 1 , the pixel sub-window of this example can cover the valid pixel points on the fold line and the diagonal line, that is, the shape of the pixel sub-window has changed.

[0110] Step S2, determining an updated pixel value of any pixel point through any pixel sub-window among the plurality of pixel sub-windows.

[0111] The pixel value after the central pixel is updated can be regarded as a processing sub-result of the central pixel. Based on this, the method of determining the processing sub-result of the central pixel according to the pixel sub-window, that is, the implementation method of step S2, is similar to the implementation method of the image signal processor 20 determining the processing result of the central pixel according to the pixel window, and will not be repeated here.

[0112] Optionally, for Figure 2 The pixel window shown in (2) in the figure can be represented by the Gr pixel in the i-th row and j-th column as G ij , using flag ij Characterization G ij Whether it is a valid pixel. ij When it is a valid pixel, flag ij =1. G ij When it is not a valid pixel, flag ij =0.

[0113] Based on this, you can use Figure 4 The pixel sub-window shown in (5) in (c) is as follows Determine the updated pixel value dst of the center pixel U .

[0114] Similarly, you can use Figure 4 The pixel sub-window shown in (6) in (c) is as follows Determine the updated pixel value dst of the center pixelD .

[0115] Can be used Figure 4 The pixel sub-window shown in (7) in (c) is as follows Determine the updated pixel value dst of the center pixel L .

[0116] Can be used Figure 4 The pixel sub-window shown in (8) in (c) is as follows Determine the updated pixel value dst of the center pixel R .

[0117] Can be used Figure 4 The pixel sub-window shown in (1) in (c) is as follows Determine the updated pixel value dst of the center pixel NW .

[0118] Can be used Figure 4 The pixel sub-window shown in (2) in (c) is as follows Determine the updated pixel value dst of the center pixel NE .

[0119] Can be used Figure 4 The pixel sub-window shown in (3) of (c) is as follows Determine the updated pixel value dst of the center pixel SW .

[0120] Can be used Figure 4 The pixel sub-window shown in (4) in (c) is as follows Determine the updated pixel value dst of the center pixel SE .

[0121] Step S3, determining a processing result of any pixel point based on each updated pixel value of any pixel point.

[0122] The implementation method of step S3 is not limited in the embodiment of the present application. For example, the pixel values ​​after the central pixel is updated are averaged or weighted summed to obtain the processing result of the central pixel. In this way, the processing results of each pixel in the first image can be determined, the first image is processed, and the second image is obtained.

[0123] Optionally, step S3 includes: determining a target pixel value having the smallest pixel difference with the pixel value of any pixel point from each pixel value after update of any pixel point; and determining a processing result of any pixel point based on the target pixel value.

[0124] In this example, the pixel difference between each updated pixel value of the central pixel and the original pixel value of the central pixel can be calculated. Since there are multiple updated pixel values ​​of the central pixel, there are also multiple pixel differences. The smallest pixel difference can be selected from these pixel differences to determine the updated pixel value of the central pixel corresponding to the smallest pixel difference (i.e., the target pixel value).

[0125] In practical applications, the target pixel value can be determined directly using the pixel difference value, or the pixel difference value can be further calculated and the target pixel value can be determined using the calculation result. Determine the target pixel value dst. Among them, S represents the set of pixel sub-windows of the central pixel point, G 22 Represents the original pixel value of the center pixel, dst i Represents the updated i-th pixel value of the central pixel point determined by the i-th pixel sub-window. 22 -dst i The pixel difference between the original pixel value of the center pixel and the i-th pixel value after the center pixel is updated. represents the square of the two-norm. argmin represents the value of The minimum dst i .

[0126] After determining the target pixel value, the processing result of the central pixel point can be determined based on the target pixel value, for example, the target pixel value is used as the processing result of the central pixel point. In practical applications, the first image can be subjected to at least one processing such as denoising and brightness balancing. Different processing methods have different ways of determining the processing result of the central pixel point based on the target pixel value. Two possible implementation methods are shown below.

[0127] In implementation C, the processing result of any pixel point includes the denoising result of any pixel point. Based on the target pixel value, determining the processing result of any pixel point includes: determining the difference between the pixel value of any pixel point and the target pixel value; and determining the denoising result of any pixel point according to the denoising coefficient, the difference and the target pixel value.

[0128] If the first image is subjected to denoising, the difference between the pixel value of the central pixel and the target pixel value can be calculated for the central pixel. The difference is multiplied by the denoising coefficient and added to the target pixel value to obtain the denoising result of the central pixel. The embodiment of the present application does not limit the method for determining the denoising coefficient.

[0129] For example, according to dst ′ =dst+str×(G 22 -dst) determines the denoising result dst of the central pixel ′ Among them, G 22 represents the pixel value of the central pixel, dst represents the target pixel value, and str represents the denoising coefficient. Optionally, str∈[0,1] is used to control the intensity of denoising the first image.

[0130] In implementation method D, the processing result of any pixel point includes the brightness balance result of any pixel point; based on the target pixel value, the processing result of any pixel point is determined, including: determining the difference between the pixel value of any pixel point and the target pixel value; determining the brightness balance result of any pixel point based on the brightness balance coefficient, the difference and the pixel value of any pixel point.

[0131] If brightness balance is performed on the first image, for the central pixel, the difference between the pixel value of the central pixel and the target pixel value can be calculated. The difference is multiplied by the brightness balance coefficient and added to the pixel value of the central pixel to obtain the brightness balance result of the central pixel. The embodiment of the present application does not limit the method for determining the brightness balance coefficient.

[0132] Optionally, for a RAW image, since each R pixel is adjacent to a G pixel, and each B pixel is adjacent to a G pixel, generally, the number of G pixels in a RAW image is twice that of B pixels, and twice that of R pixels. Based on this, when the central pixel is a G pixel, Determine the brightness balance result dst of the center pixel ge . Wherein, center represents the pixel value of the center pixel, dst represents the target pixel value, and str represents the brightness balance coefficient. Optionally, str∈[0,1] is used to control the intensity of brightness balance for the first image.

[0133] The brightness balance of the G pixel is also called green balance processing. In an exemplary embodiment, if the RAW image is subjected to green balance processing, valid pixels that meet the following conditions can be selected: corresponding to the same channel as the central pixel, the pixel difference between the G pixel and the central pixel is not greater than the target threshold, and the G pixel is adjacent to the central pixel. For example, the valid pixels of the central pixel are as follows: Figure 3 As shown in (3) in . The pixel value of the central pixel point is updated by the pixel value of the effective pixel point, so that the pixel value of the current green channel is compensated by the pixel value of the adjacent green channel, so that each green channel within a certain range has a relatively balanced pixel value. Since the green channel is the main source of brightness, when the RAW image is processed for green balance according to the implementation method of the embodiment of the present application, the brightness of each part of the RAW image can be balanced, eliminating the maze phenomenon (a brightness difference phenomenon caused by the difference between the pixel value of the Gr channel and the pixel value of the Gb channel).

[0134] The image signal processor 20 is further configured to determine a second image according to the processing result of each pixel point.

[0135] The second image is an image processed by the first image, and the second image includes the processing results of each pixel. Optionally, if the second image is an image processed by denoising the first image, the second image includes the denoising results of each pixel; if the second image is an image processed by brightness balancing the first image, the second image includes the brightness balancing results of each pixel.

[0136] In an embodiment of the present application, on the one hand, a pixel window centered on a pixel point is determined in the first image, and the processing result of the center pixel point is determined by the valid pixel points in the pixel window, so as to avoid diffusing the pixel values ​​of invalid pixels to the center pixel point, thereby making the light and dark relationship between the processed center pixel point and the surrounding pixels consistent with the original light and dark relationship in the first image.

[0137] like Figure 5 As shown, on the one hand, Figure 5 A pixel window centered on a pixel point is determined in the first image shown in (1) in FIG. 1 , and a processing result of determining the central pixel point through the pixel window is obtained as follows: Figure 5 The processing result shown in (2) in . On the other hand, Figure 5 In the first image shown in (1), a pixel window centered on a pixel point is determined, valid pixels are determined in the pixel window, and the processing result of determining the central pixel point by the valid pixels is obtained as follows: Figure 5 The processing result shown in (3) in .

[0138] contrast Figure 5From (2) and (3) in , we can see that when the processing result of the central pixel is determined directly through the pixel window, the pixel value of the bright pixel will spread to the area where the dark pixel is located, resulting in a gray line appearing in the area where the dark pixel is located. Figure 5 The processing result shown in (2) is the same as Figure 5 The first image shown in (1) has different light and dark relationships, which reduces the image processing quality. When the processing result of the central pixel is determined by the valid pixels in the pixel window, if the central pixel is a dark pixel, the invalid bright pixel can be eliminated, and only the pixel value of the dark pixel is used to determine the processing result of the dark pixel, so that Figure 5 The processing result shown in (3) is the same as Figure 5 The first image shown in (1) has the same light and dark relationship, which improves the image processing quality.

[0139] On the other hand, the pixel sub-window includes: each valid pixel point located on the reference line in the pixel window and each valid pixel point located on one side of the reference line. Based on this, the pixel sub-window can effectively cover various edges such as horizontal edges, vertical edges and oblique edges, such as Figure 4 As shown in (c) in the figure, these pixel sub-windows can cover the horizontal edge, the vertical edge and the 45-degree oblique edge. Based on this, the pixel sub-window has an edge-preserving effect, so that when the first image is processed based on the pixel sub-window, the possibility of the pixel value diffusing along the normal direction of the edge can be reduced, and the processed second image can be ensured to have a clear edge, thereby reducing the phenomenon of aliasing artifacts in the second image and improving the quality of the second image.

[0140] like Figure 6 As shown in (a) of Figure 6 In the first image shown in (a) of (1), determine Figure 4 The pixel sub-windows shown in (a) are used to determine the processing result of the central pixel point, and the following is obtained: Figure 6 The processing result shown in (a) and (2) in FIG. Figure 6 In the first image shown in (a) of (1), determine Figure 4 The pixel sub-windows shown in (c) in FIG. 1 and the processing results of the central pixel point are determined by these pixel sub-windows, and the following is obtained: Figure 6 The processing result shown in (3) in (a).

[0141] contrast Figure 6 From (a), (2) and (3) in the above, we can see that based on Figure 4 When each pixel sub-window shown in (a) determines the processing result of the central pixel point, the pixel value can be diffused along the normal direction of the edge, resulting in Figure 6 The processing result shown in (2) of (a) in FIG. 1 shows aliasing artifacts, which affects the image quality. Figure 4 When each pixel sub-window shown in (c) determines the processing result of the central pixel point, the diffusion of the pixel value along the normal direction of the edge can be reduced. Based on this, Figure 6 The processing result shown in (3) in (a) will not have jagged artifacts, which can improve the image quality.

[0142] Furthermore, if Figure 6 As shown in (b) in Figure 6 In the first image shown in (1) of (b), determine Figure 4 The pixel sub-windows shown in (a) are used to determine the processing result of the central pixel point, and the following is obtained: Figure 6 The processing result shown in (2) in (b) is shown in FIG. Figure 6 In the first image shown in (1) of (b), determine Figure 4 The pixel sub-windows shown in (c) in FIG. 1 and the processing results of the central pixel point are determined by these pixel sub-windows, and the following is obtained: Figure 6 The processing result shown in (3) in (b).

[0143] contrast Figure 6 From (2) and (3) in (b), we can see that based on Figure 4 When each pixel sub-window shown in (a) determines the processing result of the central pixel point, the pixel value can be diffused along the normal direction of the edge, resulting in Figure 6 The processing result shown in (2) of (b) in FIG. 1 shows aliasing artifacts, which affects the image quality. Figure 4 When each pixel sub-window shown in (c) determines the processing result of the central pixel point, the diffusion of the pixel value along the normal direction of the edge can be reduced. Based on this, Figure 6 The processing result shown in (3) in (b) will not have jagged artifacts, which can improve the image quality.

[0144] The above-mentioned image processing device, by determining a pixel window centered on a pixel point in the first image, and determining the processing result of the central pixel point through the effective pixel points in the pixel window, realizes the elimination of invalid pixels in the pixel window that are greatly different from the central pixel point, and avoids the diffusion of the pixel values ​​of the invalid pixels to the central pixel point in the subsequent processing process, so that the light and dark relationship between the processed central pixel point and the surrounding pixels is consistent with the original light and dark relationship in the first image, thereby improving the accuracy of the processing result of the central pixel point. Moreover, the processing result of the central pixel point is determined through the effective pixel points in the pixel window of the central pixel point, and the pixel value of the central pixel point is optimized. Subsequently, the second image is determined according to the processing results of each pixel point. On the one hand, the second image can retain the light and dark relationship of the first image, and on the other hand, the first image can be optimized to obtain the second image, thereby improving the image quality of the second image.

[0145] The present application embodiment provides an image processing method, which is performed by the above-mentioned image processing device. Figure 7 As shown, the method includes the following steps.

[0146] Step 701, acquiring a first image, where the first image includes a plurality of pixels;

[0147] Step 702, determining a pixel window centered on any one of the plurality of pixels based on the first image, determining a valid pixel in the pixel window, wherein a pixel difference between the valid pixel and any one of the pixels is not greater than a target threshold;

[0148] Step 703, determining the processing result of any pixel point according to the valid pixel points in the pixel window;

[0149] Step 704: determine a second image according to the processing results of each pixel point.

[0150] In a possible implementation manner, before determining the valid pixel points in the pixel window, the method further includes:

[0151] Determine a dispersion parameter of the first image, where the dispersion parameter represents a dispersion degree of pixel values ​​of each pixel point;

[0152] The target threshold is determined based on the dispersion parameter.

[0153] In a possible implementation manner, before determining the valid pixel points in the pixel window, the method further includes:

[0154] Acquire a first exposure of a first image and a plurality of reference data sets, wherein the reference data sets include reference exposures and reference thresholds;

[0155] Determining a weight of each reference data set according to the first exposure and the reference exposure in each reference data set;

[0156] The target threshold is determined according to the weight of each reference data set and the reference threshold in each reference data set.

[0157] In a possible implementation, the pixel window includes a plurality of valid pixel points; and determining a processing result of any pixel point according to the valid pixel points in the pixel window includes:

[0158] Dividing a plurality of valid pixel points to obtain a plurality of pixel sub-windows, each pixel sub-window including at least one valid pixel point;

[0159] Determine an updated pixel value of any pixel point through any pixel sub-window among the plurality of pixel sub-windows;

[0160] Based on each updated pixel value of any pixel, a processing result of any pixel is determined.

[0161] In a possible implementation, multiple valid pixel points are divided to obtain multiple pixel sub-windows, including:

[0162] Valid pixel points belonging to a pixel sub-window are screened out from multiple valid pixel points, where the valid pixel points belonging to a pixel sub-window are located on a reference line or on one side of the reference line, and the reference line is a straight line passing through any pixel point in the pixel window.

[0163] In a possible implementation, determining a processing result of any pixel point based on each pixel value after update of any pixel point includes:

[0164] From the updated pixel values ​​of any pixel point, determine the target pixel value having the smallest pixel difference with the pixel value of any pixel point;

[0165] Based on the target pixel value, determine the processing result of any pixel.

[0166] In a possible implementation, the processing result of any pixel point includes a denoising result of any pixel point; and based on the target pixel value, determining the processing result of any pixel point includes:

[0167] Determine the difference between the pixel value of any pixel and the target pixel value;

[0168] The denoising result of any pixel is determined based on the denoising coefficient, difference and target pixel value.

[0169] In a possible implementation, any pixel is a pixel of a specified channel, and a processing result of any pixel includes a brightness balance result of any pixel; based on a target pixel value, determining the processing result of any pixel includes:

[0170] Determine the difference between the pixel value of any pixel and the target pixel value;

[0171] The brightness balance result of any pixel point is determined according to the brightness balance coefficient, the difference and the pixel value of any pixel point.

[0172] In a possible implementation manner, the first image corresponds to multiple channels, a pixel point in the first image corresponds to a channel, and any pixel point and a valid pixel point correspond to the same channel.

[0173] It should be understood that the above method embodiment and the device embodiment belong to the same concept, and the specific implementation process is detailed in the device embodiment, which will not be repeated here.

[0174] The above-mentioned image processing method, by determining a pixel window centered on a pixel point in the first image, and determining the processing result of the central pixel point through the effective pixel points in the pixel window, realizes the elimination of invalid pixels in the pixel window that are greatly different from the central pixel point, and avoids the diffusion of the pixel values ​​of the invalid pixels to the central pixel point in the subsequent processing process, so that the light and dark relationship between the processed central pixel point and the surrounding pixels is consistent with the original light and dark relationship in the first image, thereby improving the accuracy of the processing result of the central pixel point. Moreover, the processing result of the central pixel point is determined through the effective pixel points in the pixel window of the central pixel point, and the pixel value of the central pixel point is optimized. Subsequently, the second image is determined according to the processing results of each pixel point. On the one hand, the second image can retain the light and dark relationship of the first image, and on the other hand, the first image can be optimized to obtain the second image, thereby improving the image quality of the second image.

[0175] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards in the relevant regions. For example, the first image involved in this application was obtained with full authorization.

[0176] In an exemplary embodiment, if Figure 8 As shown, a chip is provided, and the chip includes the above-mentioned image processing device. Since the image processing device includes an ISP, the chip is a chip including an ISP.

[0177] In an exemplary embodiment, if Fig. 9 As shown, an electronic device is provided, and the electronic device includes the above chip.

[0178] It should be understood that the "plurality" mentioned in this article refers to two or more. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0179] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0180] The above description is only an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. An image processing device, characterized in that: The device includes a receiving interface and an image signal processor; The receiving interface is used to acquire a first image, where the first image includes a plurality of pixels; The image signal processor is used to determine a pixel window centered on any one of the multiple pixel points based on the first image, determine a valid pixel point in the pixel window, and a pixel difference between the valid pixel point and any one of the pixel points is not greater than a target threshold; The image signal processor is further used to determine the processing result of any pixel point according to the valid pixel points in the pixel window; The image signal processor is further used to determine the second image according to the processing results of each pixel point.

2. The device according to claim 1, characterized in that Before determining the valid pixel points in the pixel window, the method further includes: Determining a dispersion parameter of the first image, where the dispersion parameter represents a dispersion degree of pixel values ​​of each pixel point; The target threshold is determined according to the dispersion parameter.

3. The device according to claim 1, characterized in that Before determining the valid pixel points in the pixel window, the method further includes: Acquire a first exposure of the first image and a plurality of reference data sets, wherein the reference data sets include reference exposures and reference thresholds; Determining weights of the reference data sets according to the first exposure and reference exposures in the reference data sets; The target threshold is determined according to the weights of the respective reference data sets and the reference thresholds in the respective reference data sets.

4. The device according to any one of claims 1 to 3, characterized in that The pixel window includes a plurality of valid pixel points; and determining the processing result of any pixel point according to the valid pixel points in the pixel window includes: Dividing the multiple valid pixel points to obtain multiple pixel sub-windows, each pixel sub-window including at least one valid pixel point; Determine an updated pixel value of any pixel point through any pixel sub-window among the multiple pixel sub-windows; Based on each updated pixel value of the any pixel point, a processing result of the any pixel point is determined.

5. The device according to claim 4, characterized in that The dividing the multiple valid pixel points to obtain multiple pixel sub-windows includes: Valid pixel points belonging to a pixel sub-window are screened out from the multiple valid pixel points, wherein the valid pixel points belonging to the pixel sub-window are located on a reference line or on one side of the reference line, and the reference line is a straight line passing through any pixel point in the pixel window.

6. The device according to claim 4, characterized in that The determining the processing result of any pixel point based on each pixel value after the update of any pixel point includes: Determine, from the updated pixel values ​​of any one of the pixels, a target pixel value having a minimum pixel difference with the pixel value of any one of the pixels; Based on the target pixel value, a processing result of any one pixel is determined.

7. The device according to claim 6, characterized in that The processing result of any one pixel point includes a denoising result of the any one pixel point; and determining the processing result of any one pixel point based on the target pixel value includes: Determine the difference between the pixel value of any one pixel and the target pixel value; The denoising result of any one pixel is determined according to the denoising coefficient, the difference and the target pixel value.

8. The device according to claim 6, characterized in that The processing result of any pixel point includes a brightness balance result of any pixel point; The determining, based on the target pixel value, a processing result of any one pixel point includes: Determine the difference between the pixel value of any one pixel and the target pixel value; A brightness balance result of any pixel point is determined according to the brightness balance coefficient, the difference and the pixel value of any pixel point.

9. An image processing method, characterized in that: The method comprises: Acquire a first image, where the first image includes a plurality of pixels; Determine a pixel window centered on any one of the multiple pixel points based on the first image, determine a valid pixel point in the pixel window, and a pixel difference between the valid pixel point and any one of the pixel points is not greater than a target threshold; Determine a processing result of any one pixel point according to valid pixel points in the pixel window; A second image is determined according to the processing results of each pixel point.

10. The method according to claim 9, characterized in that Before determining the valid pixel points in the pixel window, the method further includes: Determining a dispersion parameter of the first image, where the dispersion parameter represents a dispersion degree of pixel values ​​of each pixel point; The target threshold is determined according to the dispersion parameter.

11. The method according to claim 9, characterized in that Before determining the valid pixel points in the pixel window, the method further includes: Acquire a first exposure of the first image and a plurality of reference data sets, wherein the reference data sets include reference exposures and reference thresholds; Determining weights of the reference data sets according to the first exposure and reference exposures in the reference data sets; The target threshold is determined according to the weights of the respective reference data sets and the reference thresholds in the respective reference data sets.

12. The method according to any one of claims 9 to 11, characterized in that The pixel window includes a plurality of valid pixel points; and determining the processing result of any pixel point according to the valid pixel points in the pixel window includes: Dividing the multiple valid pixel points to obtain multiple pixel sub-windows, each pixel sub-window including at least one valid pixel point; Determine an updated pixel value of any pixel point through any pixel sub-window among the multiple pixel sub-windows; Based on each updated pixel value of the any pixel point, a processing result of the any pixel point is determined.

13. The method according to claim 12, characterized in that The dividing the multiple valid pixel points to obtain multiple pixel sub-windows includes: Valid pixel points belonging to a pixel sub-window are screened out from the multiple valid pixel points, wherein the valid pixel points belonging to the pixel sub-window are located on a reference line or on one side of the reference line, and the reference line is a straight line passing through any pixel point in the pixel window.

14. The method according to claim 12, characterized in that The determining the processing result of any pixel point based on each pixel value after the update of any pixel point includes: Determine, from the updated pixel values ​​of any one of the pixels, a target pixel value having a minimum pixel difference with the pixel value of any one of the pixels; Based on the target pixel value, a processing result of any one pixel is determined.

15. The method according to claim 14, characterized in that The processing result of any one pixel point includes a denoising result of the any one pixel point; and determining the processing result of any one pixel point based on the target pixel value includes: Determine the difference between the pixel value of any one pixel and the target pixel value; The denoising result of any one pixel is determined according to the denoising coefficient, the difference and the target pixel value.

16. The method according to claim 14, characterized in that The processing result of any pixel point includes a brightness balance result of any pixel point; The determining, based on the target pixel value, a processing result of any one pixel point includes: Determine the difference between the pixel value of any one pixel and the target pixel value; A brightness balance result of any pixel point is determined according to the brightness balance coefficient, the difference and the pixel value of any pixel point.

17. A chip, characterized in that: The chip includes the image processing device as described in any one of claims 1 to 8.

18. An electronic device, characterized in that: The electronic device comprises the chip as claimed in claim 17.

Images