Image processing method, electronic equipment and computer readable medium
By determining the local brightness average value and brightness resolution threshold in image processing, image detail enhancement is selectively performed, and the problems of computational complexity and noise amplification in the prior art are solved, thereby achieving improvement of image details and effective suppression of noise.
Patent Information
- Application Number
- CN202311036549.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-08-16
- Publication Date
- 2025-02-28
AI Technical Summary
The existing image detail enhancement technology has defects such as complex algorithm calculations, limited effect improvement, and synchronous noise amplification, making it difficult to effectively improve image details and suppress noise.
By determining the local brightness average value and brightness resolution threshold of the local area corresponding to the pixels in the image to be processed, the detail enhancement process is selectively performed to improve image details and suppress noise according to the local brightness average value, brightness resolution threshold, and initial brightness values of the pixels.
It achieves improvement in image details, and effectively suppresses the degradation of the effect caused by synchronous noise amplification, making the logic and calculation process simple and easy to implement.
Smart Images
Figure CN119540112A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of image processing, and in particular to an image processing method, an electronic device, and a computer-readable medium. Background Art
[0002] With the continuous development of display technology, the resolution and color rendering performance of display terminal hardware are constantly improving. At the same time, due to the influence of factors such as display content shooting hardware, signal compression transmission, and network conditions, a large number of displayed images still have blurred edge details, which seriously affects people's viewing experience.
[0003] Deep learning convolutional neural networks, separate processing and re-fusion of high and low frequency information of images, and color space conversion and enhancement processing are commonly used detail enhancement technologies that can reduce the degradation of visual quality caused by image blur, thereby improving display quality. However, the above detail enhancement technologies have defects such as complex algorithm calculations, limited effect improvement, and synchronous noise amplification. There is still a lot of room for optimization of image detail enhancement technologies. Summary of the invention
[0004] The embodiments of the present disclosure provide an image processing method, an electronic device, and a computer-readable medium.
[0005] In a first aspect, an embodiment of the present disclosure provides an image processing method, comprising: determining a local brightness average value of a local area corresponding to a current pixel in an image to be processed; determining a brightness resolution threshold of a human eye corresponding to the local area based on the local brightness average value; and determining a target brightness value corresponding to the current pixel based on the local brightness average value, the brightness resolution threshold, and an initial brightness value of the current pixel.
[0006] In a second aspect, an embodiment of the present disclosure provides an electronic device, comprising: one or more processors; a memory on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the image processing method described in the first aspect of the embodiment of the present disclosure.
[0007] In a third aspect, an embodiment of the present disclosure provides a computer-readable medium having a computer program stored thereon, and when the program is executed by a processor, the image processing method described in the first aspect of the embodiment of the present disclosure is implemented.
[0008] In the embodiments of the present disclosure, by determining the local brightness average value and brightness resolution threshold of the local area corresponding to the pixels in the image to be processed, the physiological characteristics of the human eye that can distinguish different brightness resolution thresholds at different brightnesses can be utilized, and the pixels in the image to be processed are selectively enhanced in detail according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the pixel, thereby improving the image details and effectively suppressing the effect degradation caused by the synchronous amplification of noise; and the image processing method provided by the embodiments of the present disclosure has simple implementation logic and calculation process, and is easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS
[0009] Figure 1 is a flow chart of an image processing method in an embodiment of the present disclosure;
[0010] Figure 2 is a flowchart of some steps in another image processing method in an embodiment of the present disclosure;
[0011] Figure 3 is a schematic diagram of calculating the average local brightness in an embodiment of the present disclosure;
[0012] Figure 4 is a schematic diagram of the relationship between the brightness discrimination threshold of the human eye and the local brightness average value in an embodiment of the present disclosure;
[0013] Figure 5 is a flowchart of some steps in another image processing method in an embodiment of the present disclosure;
[0014] Figure 6 is a schematic diagram of the composition of an electronic device in an embodiment of the present disclosure;
[0015] Figure 7 is a schematic diagram of the composition of a computer-readable medium in an embodiment of the present disclosure;
[0016] Figure 8 It is a schematic diagram of the effect of image processing in an embodiment of the present disclosure. DETAILED DESCRIPTION
[0017] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, the image processing method, electronic device, and computer-readable medium provided by the present disclosure are described in detail below in conjunction with the accompanying drawings.
[0018] Example embodiments will be described more fully below with reference to the accompanying drawings, but the example embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. On the contrary, the purpose of providing these embodiments is to make the present disclosure thorough and complete and to enable those skilled in the art to fully understand the scope of the present disclosure.
[0019] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.
[0020] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.
[0021] The terms used herein are only used to describe specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and / or "made of" are used in this specification, the presence of the features, wholes, steps, operations, elements and / or components is specified, but the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof is not excluded.
[0022] First, refer to Figure 1 , the present disclosure provides an image processing method, including:
[0023] S1, determining the local brightness average value of the local area corresponding to the current pixel in the image to be processed;
[0024] S2. Determine a brightness discrimination threshold of a human eye corresponding to the local area according to the local brightness average value;
[0025] S3. Determine a target brightness value corresponding to the current pixel according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the current pixel.
[0026] In the embodiment of the present disclosure, the image to be processed may be an image in an RGB color space, an image in a YUV color space, or an image in another color space such as HSV, etc. The embodiment of the present disclosure does not specifically limit this.
[0027] In the embodiment of the present disclosure, multiple channels of the image to be processed may be processed, a specific channel of the image to be processed may be processed, or a single channel of the image to be processed may be processed. The embodiment of the present disclosure does not specifically limit this.
[0028] In the embodiment of the present disclosure, steps S1 to S3 are performed for any pixel to be processed, thereby achieving detail enhancement processing of the image to be processed.
[0029] In the embodiments of the present disclosure, the local area corresponding to the current pixel is the area in the image to be processed including the current pixel. In some embodiments, the local area is the area centered on the current pixel. For example, the local area corresponding to the current pixel is the area centered on the current pixel and having a size of (2m+1)×(2n+1).
[0030] In the disclosed embodiment, the brightness discrimination threshold of the human eye represents the minimum value of the pixel brightness that the human eye can distinguish and the local brightness average value under the local brightness average value of the local area. Pixels in the local area whose difference in brightness value relative to the local brightness average value is greater than or equal to the brightness discrimination threshold value will cause sensory stimulation to the human eye; pixels in the local area whose difference in brightness value relative to the local brightness average value is less than the brightness discrimination threshold value will not cause sensory stimulation to the human eye. According to the physiological characteristics of the human eye, the minimum value of brightness that the human eye can distinguish is different under different brightnesses, that is, local areas with different local brightness average values have different corresponding brightness discrimination thresholds.
[0031] In the embodiments of the present disclosure, by determining the local brightness average value and brightness resolution threshold of the local area corresponding to the pixels in the image to be processed, the physiological characteristics of the human eye that can distinguish different brightness resolution thresholds at different brightnesses can be utilized, and the pixels in the image to be processed are selectively enhanced in detail according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the pixel, thereby improving the image details and effectively suppressing the effect degradation caused by the synchronous amplification of noise; and the image processing method provided by the embodiments of the present disclosure has simple implementation logic and calculation process, and is easy to implement.
[0032] The disclosed embodiment does not specifically limit how to determine the target brightness value corresponding to the current pixel based on the local brightness average value, the brightness resolution threshold, and the initial brightness value of the current pixel.
[0033] In some embodiments, based on the physiological characteristics of the human eye that can distinguish different brightness resolution thresholds at different brightnesses, if the difference between the brightness value of the current pixel and the local brightness average value is greater than or equal to the brightness resolution threshold corresponding to the local area, it will cause sensory stimulation to the human eye, and the current pixel is considered to be a prominent pixel that requires detail enhancement processing; if the difference between the brightness value of the current pixel and the local brightness average value is less than the brightness resolution threshold corresponding to the local area, it will not cause sensory stimulation to the human eye, and the current pixel is considered to be a non-prominent pixel that does not require detail enhancement processing.
[0034] Accordingly, in some embodiments, reference Figure 2 , determining a target brightness value corresponding to the current pixel according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the current pixel, including:
[0035] S31, calculating the brightness difference between the initial brightness value and the local brightness average value;
[0036] S32: When the brightness difference is greater than or equal to the brightness resolution threshold, perform detail enhancement processing on the current pixel to obtain the target brightness value.
[0037] In the embodiment of the present disclosure, detail enhancement processing is performed on pixels whose brightness difference is greater than or equal to the brightness resolution threshold, so as to improve the clarity of the image to be processed.
[0038] The disclosed embodiment does not specifically limit how to perform detail enhancement processing on the current pixel.
[0039] In some embodiments, performing detail enhancement processing on the current pixel to obtain the target brightness value includes:
[0040] Performing local filtering on the current pixel to obtain a filtered pixel value;
[0041] Normalizing the filtered pixel value and the initial brightness value, and determining a pixel value to be output according to the filtered pixel value and the initial brightness value;
[0042] The pixel value to be output is quantized to obtain the target brightness value.
[0043] The disclosed embodiment does not specifically limit how to perform local filtering on the current pixel. For example, filtering methods such as mean filtering, median filtering, Gaussian filtering, bilateral filtering, guided filtering, etc. may be used to perform local filtering on the current pixel.
[0044] The embodiment of the present disclosure does not specifically limit how to perform the quantization process. For example, the pixel value to be output is quantized to a value between 0 and 255.
[0045] The embodiment of the present disclosure does not specifically limit how to determine the pixel value to be output according to the filtered pixel value and the initial brightness value.
[0046] In some embodiments, the pixel value to be output is determined according to the filtered pixel value and the initial brightness value based on the following formula (1):
[0047]
[0048] Wherein, D(i,j) represents the pixel value to be output, S(i,j) represents the initial brightness value, B(i,j) represents the filtered pixel value, i and j are integers, and (i,j) is the coordinate of the current pixel.
[0049] In some embodiments, at least one channel of the image to be processed is calculated according to formula (1). For example, if the image to be processed is an image in RGB color space, the three channels R, G, and B of the image to be processed are calculated according to formula (1).
[0050] In some embodiments, reference Figure 2, determining a target brightness value corresponding to the current pixel according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the current pixel, further comprising:
[0051] S33: When the brightness difference value is smaller than the brightness resolution threshold, use the initial brightness value as the target brightness value.
[0052] In the embodiment of the present disclosure, detail enhancement processing is not performed on pixels whose brightness difference value is less than the brightness resolution threshold, but the original brightness value is output as the target brightness value, which can reduce the influence of noise.
[0053] The embodiment of the present disclosure does not specifically limit how to determine the local brightness average value of the local area corresponding to the current pixel in the image to be processed.
[0054] In some embodiments, determining the local brightness average value of the local area corresponding to the current pixel in the image to be processed includes:
[0055] A weighted average of brightness values of multiple pixels in the local area is calculated to obtain the local brightness average value.
[0056] For example, the weighted average of the brightness values of multiple pixels in the local area is calculated to obtain the local brightness average value, which can be expressed as formula (2):
[0057]
[0058] Wherein, Y_block represents the local brightness average value, the local area is the area with a size of (2m+1)×(2n+1) centered on the current pixel, m, n are integers, i, j are integers, and W i,j Represents the weight value, Y i,j Represents the pixel brightness value.
[0059] Taking the local area as a 3×3 area centered on the current pixel as an example, the weighted average of the brightness values of multiple pixels in the local area is calculated to obtain the local brightness average value as follows: Figure 3 shown.
[0060] In some embodiments, the weight values corresponding to the pixels in the local area are equal, and the weighted average of the brightness values of the multiple pixels in the local area is the average of the brightness values of the multiple pixels in the local area. Formula (2) can be converted into the form of formula (3):
[0061]
[0062] The embodiments of the present disclosure do not specifically limit how to determine the brightness discrimination threshold of the human eye corresponding to the local area based on the local brightness average value.
[0063] According to the physiological characteristics of the human eye, as the brightness of the local area increases, the brightness resolution threshold of the human eye shows a trend of first decreasing and then increasing. The brightness resolution threshold determined in the embodiment of the present disclosure conforms to the above physiological characteristics of the human eye.
[0064] Accordingly, in some embodiments, determining the brightness discrimination threshold of the human eye corresponding to the local area according to the local brightness average value includes:
[0065] The brightness resolution threshold is determined based on the local brightness average value and the brightness reference value, wherein when the local brightness average value is less than the brightness reference value, the brightness resolution threshold is negatively correlated with the local brightness average value; when the local brightness average value is greater than the brightness reference value, the brightness resolution threshold is positively correlated with the local brightness average value.
[0066] In the embodiment of the present disclosure, the brightness reference value corresponds to the lower limit of the brightness resolution threshold, that is, when the local brightness average value is equal to the brightness reference value, the corresponding brightness resolution threshold is minimum. The embodiment of the present disclosure does not specifically limit the brightness reference value, and it can be set according to the physiological characteristics of the human eye.
[0067] In some embodiments, the brightness resolution threshold is determined based on the following formula (4) according to the local brightness average value and the brightness reference value:
[0068]
[0069] Wherein, T(i, j) represents the brightness resolution threshold, Y_block represents the local brightness average value, k represents the brightness reference value, i and j are integers, and (i, j) is the coordinate of the current pixel.
[0070] In some embodiments, the brightness reference value k is 127, and the brightness discrimination threshold of the human eye under different local brightness average values is as follows: Figure 4 shown.
[0071] In the embodiment of the present disclosure, multiple channels of the image to be processed may be processed, a specific channel of the image to be processed may be processed, or a single channel of the image to be processed may be processed. The embodiment of the present disclosure does not specifically limit this.
[0072] Accordingly, in some embodiments, determining the local brightness average value of the local area corresponding to the current pixel in the image to be processed includes:
[0073] Determine the local brightness average of at least one channel of the local area corresponding to the current pixel in the image to be processed.
[0074] The image processing method provided in the embodiment of the present disclosure can be applied to the overall detail enhancement of the image to be processed, and can also be applied to the detail enhancement of a specific area in the image to be processed. In the embodiment of the present disclosure, the specific area can be an area corresponding to subtitles, text, etc., or an area with specific features (such as a face, sky, etc.), and the embodiment of the present disclosure does not specifically limit this.
[0075] Accordingly, in some embodiments, reference Figure 5 Before determining the local brightness average value of the local area corresponding to the current pixel in the image to be processed, the image processing method further includes:
[0076] S4. Perform image recognition on the image to be processed to determine a region to be processed, wherein the current pixel is a pixel in the region to be processed.
[0077] Second, refer to Figure 6 , an embodiment of the present disclosure provides an electronic device, comprising:
[0078] One or more processors 101;
[0079] A memory 102 storing one or more programs, which, when executed by one or more processors, enables the one or more processors to implement the image processing method according to the first aspect of the embodiment of the present disclosure;
[0080] One or more I / O interfaces 103 are connected between the processor and the memory and are configured to implement information exchange between the processor and the memory.
[0081] Among them, the processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU) and the like; the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory (FLASH); the I / O interface (read-write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus) and the like.
[0082] In some embodiments, the processor 101 , the memory 102 , and the I / O interface 103 are connected to each other via a bus 104 , and further connected to other components of the computing device.
[0083] The embodiments of the present disclosure do not specifically limit the electronic devices, for example, electronic devices include but are not limited to mobile phones, vehicle-mounted displays, televisions, commercial displays, computers, etc.
[0084] Thirdly, refer to Figure 7 The embodiment of the present disclosure provides a computer-readable medium on which a computer program is stored. When the program is executed by a processor, the image processing method described in the first aspect of the embodiment of the present disclosure is implemented.
[0085] In order to enable those skilled in the art to more clearly understand the technical solutions provided by the embodiments of the present disclosure, the technical solutions provided by the embodiments of the present disclosure are described in detail below through specific embodiments:
[0086] Example
[0087] This embodiment can be applied to RGB color space, YUV color space, HSV color space, etc.
[0088] This embodiment supports processing multiple channels of an image, supports processing a specific channel of an image, and supports processing a single-channel image (black and white image).
[0089] This embodiment can be applied to the overall detail enhancement of the processed image, or to a specific region in the processed image. The specific region can be a region corresponding to subtitles, text, etc., or a region with specific features (such as a face, sky, etc.).
[0090] This embodiment can be applied to application scenarios that support image display detail enhancement, for example, display application scenarios based on terminals such as mobile phones, vehicle-mounted displays, televisions, commercial displays, and computers.
[0091] This embodiment selectively enhances the details of pixels based on the physiological characteristics of different brightness discrimination thresholds of the human eye at different brightnesses. The specific implementation process is as follows:
[0092] Calculate the local brightness average of the local area corresponding to the current pixel.
[0093] In this embodiment, the weighted average value of the brightness values of multiple pixels in the local area can be calculated according to formula (5):
[0094]
[0095] Wherein, Y_block represents the local brightness average value, the local area is the area with a size of (2m+1)×(2n+1) centered on the current pixel, m, n are integers, i, j are integers, and W i,j Represents the weight value, Y i,j Represents the pixel brightness value.
[0096] In this embodiment, the average value of brightness values of multiple pixels in the local area can also be calculated according to formula (6):
[0097]
[0098] In this embodiment, the pixel brightness value is calculated according to formula (7):
[0099] Y=R×r_y+G×g_y+B×b_y (7)
[0100] Among them, Y represents the pixel brightness value, R, G, and B represent the channel values of the three channels of the RGB image respectively, and r_y, g_y, and b_y represent the brightness calculation coefficients of the three channels of the corresponding RGB image respectively.
[0101] Calculate the brightness discrimination threshold of the human eye corresponding to the local area.
[0102] Taking the brightness reference value as 127 as an example, the brightness resolution threshold is calculated according to formula (8):
[0103]
[0104] Wherein, T(i, j) represents the brightness resolution threshold, Y_block represents the local brightness average value, i and j are integers, and (i, j) is the coordinate of the current pixel.
[0105] The brightness difference between the initial brightness value of the current pixel and the local brightness average is calculated to determine the pixel to be enhanced.
[0106] According to formula (9), the brightness difference between the initial brightness value of the current pixel and the local brightness average value is calculated:
[0107] Y_diff=abs(Y-Y_block) (9)
[0108] Wherein, Y_diff represents the brightness difference, Y represents the pixel brightness, Y_block represents the local brightness average, and abs(·) is the absolute value operation.
[0109] Compare the brightness difference of the current pixel with the brightness resolution threshold T(i,j). If the brightness difference Y_diff of the current pixel is less than the brightness resolution threshold T(i,j), it is considered that this pixel will not cause sensory stimulation to the human eye in the local area and is not a prominent pixel. In order to reduce the influence of noise, no detail enhancement is performed on this pixel and the original value is output; if the brightness difference Y_diff of the current pixel is greater than or equal to the brightness resolution threshold T(i,j), it is considered that this pixel will cause sensory stimulation to the human eye in the local range and is a prominent pixel. It needs to be enhanced to improve the overall clarity of the image, thereby determining the pixel to be enhanced.
[0110] Perform detailed enhancement processing on the pixels to be enhanced.
[0111] Perform local filtering on the pixels to be enhanced to obtain filtered pixel values. The filtering method can be a mean filter, a median filter, a Gaussian filter, a bilateral filter, a guided filter, or other filtering methods. Preferably, bilateral filtering is used for local filtering;
[0112] The filtered pixel value and the initial brightness value are normalized, and the pixel value to be output is determined according to formula (10):
[0113]
[0114] Wherein, D(i,j) represents the pixel value to be output, S(i,j) represents the initial brightness value, B(i,j) represents the filtered pixel value, i and j are integers, and (i,j) is the coordinate of the current pixel.
[0115] The pixel value to be output is quantized to a value between 0 and 255 to obtain the target brightness value.
[0116] The effect of detail enhancement processing of the image in this embodiment is as follows: Figure 8 shown. Figure 8 (a) is the image to be processed, (b) is the effect of detail enhancement processing without opening the human eye brightness discrimination threshold judgment, and (c) is the effect of detail enhancement processing with opening the human eye brightness discrimination threshold judgment. Figure 8 It can be seen that when the human eye brightness discrimination threshold is turned on for detail enhancement, Figure 8 In the raindrop area), it can significantly reduce the noise ( Figure 8 Synchronous amplification of the face area in the image.
[0117] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium includes 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). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.
[0118] Example embodiments have been disclosed herein, and although specific terms are employed, they are used and should be interpreted only in a general illustrative sense and not for limiting purposes. In some instances, it will be apparent to those skilled in the art that, unless otherwise expressly noted, features, characteristics, and / or elements described in conjunction with a particular embodiment may be used alone or in combination with features, characteristics, and / or elements described in conjunction with other embodiments. Therefore, those skilled in the art will appreciate that various changes in form and detail may be made without departing from the scope of the present disclosure as set forth in the appended claims.
Claims
1. An image processing method, comprising: Determine the local brightness average of the local area corresponding to the current pixel in the image to be processed; Determining a brightness discrimination threshold of a human eye corresponding to the local area according to the local brightness average value; A target brightness value corresponding to the current pixel is determined according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the current pixel.
2. The image processing method according to claim 1, wherein: Determining a target brightness value corresponding to the current pixel according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the current pixel, including: Calculating a brightness difference between the initial brightness value and the local brightness average value; When the brightness difference is greater than or equal to the brightness resolution threshold, detail enhancement processing is performed on the current pixel to obtain the target brightness value.
3. The image processing method according to claim 2, wherein: Performing detail enhancement processing on the current pixel to obtain the target brightness value includes: Performing local filtering on the current pixel to obtain a filtered pixel value; Normalizing the filtered pixel value and the initial brightness value, and determining a pixel value to be output according to the filtered pixel value and the initial brightness value; The pixel value to be output is quantized to obtain the target brightness value.
4. The image processing method according to claim 3, wherein: Based on the following formula, the pixel value to be output is determined according to the filtered pixel value and the initial brightness value: Wherein, D(i,j) represents the pixel value to be output, S(i,j) represents the initial brightness value, B(i,j) represents the filtered pixel value, i and j are integers, and (i,j) is the coordinate of the current pixel.
5. The image processing method according to claim 2, wherein: Determining a target brightness value corresponding to the current pixel according to the local brightness average value, the brightness resolution threshold, and the initial brightness value of the current pixel, further comprising: When the brightness difference value is smaller than the brightness resolution threshold, the initial brightness value is used as the target brightness value.
6. The image processing method according to any one of claims 1 to 5, wherein: Determine the local brightness average of the local area corresponding to the current pixel in the image to be processed, including: A weighted average of brightness values of multiple pixels in the local area is calculated to obtain the local brightness average value.
7. The image processing method according to any one of claims 1 to 5, wherein: Determining a brightness discrimination threshold of a human eye corresponding to the local area according to the local brightness average value includes: The brightness resolution threshold is determined based on the local brightness average value and the brightness reference value, wherein when the local brightness average value is less than the brightness reference value, the brightness resolution threshold is negatively correlated with the local brightness average value; when the local brightness average value is greater than the brightness reference value, the brightness resolution threshold is positively correlated with the local brightness average value.
8. The image processing method according to claim 7, wherein: The brightness resolution threshold is determined based on the following formula according to the local brightness average value and the brightness reference value: Wherein, T(i, j) represents the brightness resolution threshold, Y_block represents the local brightness average value, k represents the brightness reference value, i and j are integers, and (i, j) is the coordinate of the current pixel.
9. The image processing method according to any one of claims 1 to 5, wherein: Determine the local brightness average of the local area corresponding to the current pixel in the image to be processed, including: Determine the local brightness average of at least one channel of the local area corresponding to the current pixel in the image to be processed.
10. The image processing method according to any one of claims 1 to 5, wherein: Before determining the local brightness average value of the local area corresponding to the current pixel in the image to be processed, the image processing method further includes: Image recognition is performed on the image to be processed to determine a region to be processed, wherein the current pixel is a pixel in the region to be processed.
11. An electronic device, comprising: one or more processors; A memory having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the image processing method according to any one of claims 1 to 10.
12. A computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the image processing method according to any one of claims 1 to 10 is implemented.