Image processing method and system based on high-definition display chip

Abstract

The invention provides an image processing method and system based on a high-definition display chip, and relates to the technical field of image processing, the image quality is remarkably improved based on the high-definition display chip, the core is that a multi-scale analysis technology and an intelligent dynamic adjustment mechanism are combined, and the image quality is improved. According to the method, image details can be accurately enhanced, the authenticity and accuracy of color reproduction can be improved, noise can be effectively suppressed, the supersaturation phenomenon can be effectively avoided, and therefore a more natural and harmonious visual effect is provided; the method of determining fusion weight through multi-scale analysis and combination of image complexity ensures that the extracted reflection component can more accurately capture detail information in the image, which is beneficial to highlighting fine textures and edges and lays a foundation for subsequent image quality enhancement. Therefore, the definition and fineness of the whole image can be improved, the effective enhancement of the image is finally realized, and the whole quality of display is improved.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to an image processing method and system based on a high-definition display chip. Background Art

[0002] With the rapid development and progress of the times, as well as the popularization of high-definition display devices, the requirements for image display quality are getting higher and higher, and people's requirements for high-definition video images are also increasing. However, due to the limitations of the times, some existing video images are limited by their own production years. The quality of video images cannot meet the needs of existing high-definition display devices. During playback, the image quality is not high, affecting the visual viewing experience. Traditional display device merchants will enhance the image through hardware during playback. These image enhancement methods mainly include adjusting image parameters such as chromaticity, contrast, brightness, and enhancing the display effect of the image through edge sharpening and other technologies. Although these methods can improve image quality to a certain extent, they often have limitations. They do not pay attention to the influence of the ambient light intensity and ambient color temperature of the image production itself, nor do they go deep into the deep features of the image to improve the image quality, which will cause some problems, such as image oversaturation, noise amplification or artifacts.

[0003] Therefore, it is necessary to provide an image processing method and system based on a high-definition display chip to solve the above technical problems. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides an image processing method and system based on a high-definition display chip, which achieves the beneficial effect of enhancing the display of an image based on a high-definition display chip.

[0005] The present invention provides an image processing method based on a high-definition display chip, wherein the image processing method is performed by the high-definition display chip and comprises the following steps: S1: converting the image to be processed into a Lab image, and obtaining a backlight reference value under the shooting environment of the image to be processed, wherein the backlight reference value is obtained based on the ambient light intensity and the ambient color temperature; S2: Separate the L channel image, the a channel image and the b channel image from the Lab image and obtain the edge map and the reflection component map of the L channel image; S3: obtaining an edge protection weight map based on the edge map, and performing contrast enhancement on the reflection component map in combination with the backlight reference value to obtain a high-contrast reflection map; S4: Correcting the a-channel image and the b-channel image respectively based on the backlight reference value to obtain an a-channel corrected image and a b-channel corrected image; S5: replace the L channel image, a channel image and b channel image in the Lab image with the high contrast reflection image, a channel correction image and b channel correction image respectively, and perform color space inverse conversion on the corrected Lab image to complete image enhancement.

[0006] Preferably, the calculation formula of the backlight reference value is: in, is the backlight reference value, is the proportionality coefficient, is the ambient light intensity, is the reference light intensity, is the reference color temperature, is the ambient color temperature.

[0007] Preferably, in step S2, obtaining the reflection component map comprises the following steps: Reflection components of the L channel image at multiple scales are extracted respectively, and complexity calculations are performed on the reflection components at multiple scales to obtain local complexity maps corresponding to the reflection components at multiple scales; Perform histogram statistics on the local complexity graph at each scale to obtain complexity histograms corresponding to reflection components at multiple different scales; Based on the complexity histogram at each scale, the cumulative distribution functions corresponding to the reflection components at multiple different scales are obtained; Calculate the fusion weights corresponding to the reflection components at multiple different scales based on the cumulative distribution function at each scale; The reflection components at multiple scales are weighted fused based on the fusion weights to obtain a reflection component map.

[0008] Preferably, the calculation formula of the cumulative distribution function at each scale is: in, For scale The cumulative distribution function of the reflected component under For scale The complexity of the reflection component under The number of pixels when is the total number of complexity values.

[0009] Preferably, the complexity values ​​at a plurality of preset percentile positions on the cumulative distribution function are selected as the key complexity threshold.

[0010] Preferably, the calculation formula of the fusion weight is: in, For scale The fusion weight of the reflection component under For scale The standard deviation of the Gaussian filter under is the number of selected key complexity thresholds, hour is the minimum complexity bound of the cumulative distribution function, hour is the maximum complexity boundary of the cumulative distribution function, It is a scale The critical complexity threshold under The cumulative distribution function value at is the decay speed control parameter.

[0011] Preferably, the edge protection weight map is obtained by: is the edge protection weight graph, is the pixel point in the L channel image The edge strength value of Control parameter for weight decay speed.

[0012] Preferably, the acquisition of the high contrast reflection image comprises the following steps: The reflection component image is subjected to preliminary enhancement processing to obtain a preliminary enhanced contrast reflection image. The formula for the preliminary enhancement processing is: in, To initially enhance the contrast reflectance map, is the reflection component map, To control the proportionality factor of the enhancement degree, Pixel The local average brightness value, is the global average brightness value of the reflection component map; The preliminary enhanced contrast reflection image is subjected to final enhancement processing in combination with the edge protection weight map and the backlight reference value to obtain a high contrast reflection image. The formula for the final enhancement processing is: in, For high contrast reflectance images, is the reflection component map, To initially enhance the contrast reflectance map, is the edge protection weight graph, This is the backlight reference value.

[0013] Preferably, the correction formulas of the a-channel corrected image and the b-channel corrected image are: in, Correct the image for channel a, is the b channel corrected image, is the a channel image, is the b channel image, and are the reference color values ​​of the a channel image and the b channel image respectively. This is the backlight reference value.

[0014] The present invention also provides an image processing system based on a high-definition display chip. The image processing system is deployed in the high-definition display chip and applied to an image processing method based on the high-definition display chip, comprising: A color space conversion module is used to convert the image to be processed into a Lab image, and obtain a backlight reference value under the shooting environment of the image to be processed, wherein the backlight reference value is obtained based on the ambient light intensity and the ambient color temperature; An edge detection module is used to separate an L channel image, an a channel image and a b channel image from the Lab image and obtain an edge map and a reflection component map of the L channel image; A contrast enhancement module is used to obtain an edge protection weight map based on the edge map, and to enhance the contrast of the reflection component map in combination with the backlight reference value to obtain a high-contrast reflection map; A chromaticity correction module, used to correct the a-channel image and the b-channel image respectively based on the backlight reference value to obtain an a-channel corrected image and a b-channel corrected image; The image reconstruction module is used to replace the L channel image, a channel image and b channel image in the Lab image with the high contrast reflection map, a channel correction image and b channel correction image respectively, and perform color space inverse conversion on the corrected Lab image to complete image enhancement.

[0015] Compared with the related art, the image processing method and system based on high-definition display chip provided by the present invention have the following beneficial effects: The present invention achieves a significant improvement in image quality based on a high-definition display chip. The core of the present invention is to combine advanced multi-scale analysis technology and intelligent dynamic adjustment mechanism, which can not only accurately enhance image details, improve the authenticity and accuracy of color reproduction, but also effectively suppress noise and avoid oversaturation, thereby providing a more natural and harmonious visual effect. The method of determining the fusion weight by multi-scale analysis and combining image complexity ensures that the extracted reflection component can more accurately capture the detail information in the image, which helps to highlight subtle textures and edges, and paves the way for subsequent image quality enhancement, thereby improving the clarity and delicacy of the overall image. In addition, the present invention particularly optimizes the algorithm structure to support advanced display functions such as high dynamic range and wide color gamut, ensuring that it can automatically adapt to and provide the best image display quality regardless of the display environment. More importantly, the design of this solution takes into account the high compatibility with the existing high-definition display chip technology, adopts the idea of ​​module integration, is easy to integrate and has good scalability, and lays a solid foundation for future technology upgrades, and finally achieves effective enhancement of the image, improves the overall quality of the display, and meets the user's demand for ultimate visual enjoyment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of the flow of an image processing method based on a high-definition display chip according to the present invention; Figure 2 The figure is a schematic diagram of the module structure of an image processing system based on a high-definition display chip according to the present invention. DETAILED DESCRIPTION

[0017] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only the parts related to the present invention, rather than all structures, are shown in the accompanying drawings. In addition, the embodiments of the present invention and the features in the embodiments may be combined with each other without conflict.

[0018] It should also be noted that, for ease of description, only the parts related to the present invention, but not all of the contents, are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the various operations (or steps) as being processed sequentially, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the various operations can be rearranged. The processing can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The processing can correspond to methods, functions, procedures, subroutines, subprograms, etc.

[0019] Embodiment 1 An image processing method based on a high-definition display chip, the image processing method is executed by the high-definition display chip, in the specific implementation process, such as Figure 1 As shown, it shows a schematic diagram of an image processing method based on a high-definition display chip, including the following steps: Step S1: converting the image to be processed into a Lab image, and obtaining a backlight reference value under the shooting environment of the image to be processed, wherein the backlight reference value is obtained based on the ambient light intensity and the ambient color temperature.

[0020] Specifically, the calculation formula of the backlight reference value is: in, is the backlight reference value, is the proportionality coefficient, is the ambient light intensity, is the reference light intensity, is the reference color temperature, is the ambient color temperature.

[0021] During the specific implementation process, the image processing method is executed by a high-definition display chip. In practice, the high-definition display chip, usually including but not limited to a video decoder, is responsible for receiving and decoding the input video signal, an image enhancement engine, which is used for adjusting the image contrast and brightness, as well as reducing noise and enhancing the image edge information, a color management unit, which is used for adjusting the hue, saturation and achieving a wider color gamut coverage to ensure the true reproduction of colors, and a scaling engine, which is used for adjusting the input video resolution to match the physical resolution of the display to achieve smooth image scaling without distortion. In the present invention, the high-definition display chip processes the image, first converting the image from the original color space to the Lab color space to better separate and process the color and brightness. The Lab color space consists of three components, namely, the L channel component, the a channel component and the b channel component. Then, according to the original image information, the ambient light intensity and the ambient color temperature of the image to be processed when it was shot are obtained. Based on the ambient light intensity and the ambient color temperature, the backlight reference value is obtained by the backlight reference value calculation formula for subsequent adjustment of the image brightness and other parameters, wherein, The reference light intensity is usually set based on the average light intensity in a typical working environment. For reference color temperature, it is usually set to 6500K, which is close to the color temperature of natural daylight.

[0022] Step S2: Separate the L channel image, the a channel image and the b channel image from the Lab image and obtain the edge map and the reflection component map of the L channel image.

[0023] During the specific implementation process, in order to enhance the detail information in the image, edge features are extracted from the L channel image, and an edge map is obtained through edge detection algorithms including but not limited to Canny edge detection and Sobel operator detection. The multi-scale Retinex algorithm is used to filter and smooth the processed image at multiple scales to extract reflection components at multiple scales, and the reflection component map is obtained through weighted fusion.

[0024] Specifically, in step S2, obtaining the reflection component map includes the following steps: Reflection components of the L channel image at multiple scales are extracted respectively, and complexity calculations are performed on the reflection components at multiple scales to obtain local complexity maps corresponding to the reflection components at multiple scales; Perform histogram statistics on the local complexity graph at each scale to obtain complexity histograms corresponding to reflection components at multiple different scales; Based on the complexity histogram at each scale, the cumulative distribution functions corresponding to the reflection components at multiple different scales are obtained; Calculate the fusion weights corresponding to the reflection components at multiple different scales based on the cumulative distribution function at each scale; The reflection components at multiple scales are weighted fused based on the fusion weights to obtain a reflection component map.

[0025] Specifically, the calculation formula of the cumulative distribution function at each scale is: in, For scale The cumulative distribution function of the reflected component under For scale The complexity of the reflection component under The number of pixels when is the total number of complexity values.

[0026] In the specific implementation process, the reflection component map is obtained by extracting reflection components of multiple scales through the multi-scale Retinex algorithm, and the reflection component map is obtained by weighted fusion. First, the L channel image is processed at multiple scales using the multi-scale Retinex algorithm to extract reflection components at multiple scales. The selection of each scale should be based on actual needs. For the reflection component at each scale, its local complexity is calculated, and the complexity of the reflection component at each scale is evaluated by edge detection or gradient amplitude to obtain the local complexity map corresponding to the reflection components at multiple different scales. Next, the local complexity map at each scale is histogram-generated to obtain the complexity histogram. The complexity histogram reflects the distribution of the complexity of the reflection components at each scale. Based on each complexity histogram, the corresponding cumulative distribution function is calculated for subsequent weight calculation. The cumulative distribution function represents the proportion of pixels with a complexity less than or equal to a certain value. The fusion weight of the reflection component at each scale is determined based on the cumulative distribution function.

[0027] Specifically, the complexity values ​​at a plurality of preset percentile positions on the cumulative distribution function are selected as the key complexity threshold.

[0028] Specifically, the calculation formula of the fusion weight is: in, For scale The fusion weight of the reflection component under For scale The standard deviation of the Gaussian filter under is the number of selected key complexity thresholds, hour is the minimum complexity bound of the cumulative distribution function, hour is the maximum complexity boundary of the cumulative distribution function, It is a scale The critical complexity threshold under The cumulative distribution function value at is the decay speed control parameter.

[0029] In the specific implementation process, before determining the fusion weight of the reflection component by the cumulative distribution function, it is necessary to determine the key complexity thresholds. These thresholds can be determined according to the percentiles on the cumulative distribution function curve, such as 25%, 50%, and 75%. These thresholds divide the image into different complexity areas. After determining the key complexity thresholds, the fusion weights of the reflection components at the corresponding scales are calculated by the calculation formula of the fusion weights, where: This reflects that the smaller the scale, the more details, and the greater its importance in high-complexity areas. Adjusted the weights and parameters in different complexity ranges Controls the decay speed, the larger The value means that it is more inclined to give higher weights in a smaller complexity range. For example, three scales are selected by the multi-scale Retinex algorithm to obtain reflection components at three different scales, corresponding to the standard deviation of the Gaussian filter. , , , and select the complexity values ​​corresponding to the 25%, 50%, and 75% positions of the cumulative distribution function as three key complexity thresholds, denoted as , , , then in the calculation formula of the fusion weight According to the cumulative distribution function formula, the function value of the cumulative distribution function at one scale is , , , , , here Right now , and They are the range boundaries of the cumulative distribution function respectively. Finally, the fusion weight of the reflection component at this scale is obtained through the calculation formula of the fusion weight. The fusion weight of the reflection component at other scales can be calculated in the same way. Finally, the obtained fusion weight is normalized and used for the fusion of the reflection component to obtain the final reflection component map.

[0030] Step S3: obtaining an edge protection weight map based on the edge map, and performing contrast enhancement on the reflection component map in combination with the backlight reference value to obtain a high-contrast reflection map.

[0031] Specifically, the formula for obtaining the edge protection weight map is: is the edge protection weight graph, is the pixel point in the L channel image The edge strength value of Control parameter for weight decay speed.

[0032] In the specific implementation process, a smoothing filter is used to smooth the edge map to reduce the influence of noise and generate a continuous edge protection weight map. The edge strength is mapped to a value between 0 and 1 according to the edge protection weight map acquisition formula, where a value close to 1 indicates a stronger edge protection and a value close to 0 indicates a weaker protection. The contrast of the reflection component map is adjusted in combination with the backlight reference value. A value of 1 will make the weight map change more smoothly, while a smaller value A value of will cause the weight map to drop rapidly near the edge, providing a stronger edge protection effect. In general contrast enhancement tasks, a typical starting point may be 10 or adjust appropriately based on the scale of the image. This value can be used as a basis for initial attempts, and then fine-tuned based on the results or through experimentation to find the optimal value.

[0033] Specifically, the step of obtaining the high contrast reflection image includes the following steps: Perform preliminary enhancement processing on the reflection component image to obtain a preliminary enhanced contrast reflection image. The formula for preliminary enhancement processing is: in, To initially enhance the contrast reflectance map, is the reflection component map, To control the proportionality factor of the enhancement degree, Pixel The local average brightness value, is the global average brightness value of the reflection component map; The preliminary enhanced contrast reflection image is finally enhanced by combining the edge protection weight map and the backlight reference value to obtain a high contrast reflection image. The final enhancement formula is: in, For high contrast reflectance images, is the reflection component map, To initially enhance the contrast reflectance map, is the edge protection weight graph, This is the backlight reference value.

[0034] In the specific implementation process, the acquisition of high-contrast reflection map includes two detailed steps. First, the reflection component map is preliminarily enhanced by the preliminary enhancement processing formula to obtain a preliminary enhanced contrast reflection map. First, the local average brightness value is calculated. For each pixel point of the reflection component map, the local average brightness value within a certain range around it is calculated. This is achieved by using a filter through a convolution operation. Then, the global average brightness value of the entire reflection component map is calculated. This is to provide a reference point to maintain the consistency of the overall brightness during the enhancement process. Finally, the preliminary enhancement processing formula is applied to adjust the brightness of each pixel point and its local and global average brightness, thereby achieving preliminary contrast enhancement. The final enhancement processing is to perform final enhancement processing on the preliminary enhanced contrast reflection image in combination with the backlight reference value and the edge protection weight map to obtain a high-contrast reflection image. First, consider the backlight reference value under the shooting environment. The backlight reference value is calculated based on the ambient light intensity and the ambient color temperature. It reflects the ideal backlight compensation level. By applying this value to the final enhancement processing step of the reflection component image, it can better adapt to different lighting conditions and ensure the quality of the output image. At the same time, combined with the previously generated edge protection weight map, the changes in the edge area are smoother. In this way, the overall contrast of the image can be improved without destroying the edge structure. Finally, the high-contrast reflection image needs to be post-processed. For example, the high-contrast reflection image is normalized to ensure that the pixel values ​​fall within the appropriate range.

[0035] Step S4: Correct the a-channel image and the b-channel image respectively based on the backlight reference value to obtain an a-channel corrected image and a b-channel corrected image.

[0036] Specifically, the correction formulas for the a-channel corrected image and the b-channel corrected image are: in, Correct the image for channel a, is the b channel corrected image, is the a channel image, is the b channel image, and are the reference color values ​​of the a channel image and the b channel image respectively. This is the backlight reference value.

[0037] In the specific implementation process, it is also necessary to perform color correction on the a-channel image and the b-channel image. To correct the a-channel image and the b-channel image based on the backlight reference value, first, it is necessary to determine the reference color values ​​of the a-channel image and the b-channel image. For example, and By calculating the color distribution histogram of the a channel image and the b channel image respectively, and selecting the 90th percentile value in the color distribution histogram as and Next, use the provided correction formula to perform color correction on the a channel image and the b channel image respectively. After the correction is completed, in order to ensure that the corrected image is within the appropriate color range, normalization processing is required to finally obtain the a channel corrected image and the b channel corrected image.

[0038] Step S5: replace the L channel image, a channel image and b channel image in the Lab image with the high contrast reflection image, a channel correction image and b channel correction image respectively, and perform color space inverse conversion on the corrected Lab image to complete image enhancement.

[0039] During the specific implementation process, the high-contrast reflection image obtained in the previous step replaces the L channel image in the Lab image, and the a channel corrected image and the b channel corrected image obtained in the previous step replace the a channel image and the b channel image in the Lab image respectively, so as to obtain a Lab image completely composed of enhanced and corrected new channels. The corrected Lab image is inversely converted back to the image of the original color space by using a color space conversion algorithm or function to obtain the final enhanced image, thereby realizing the image quality enhancement processing of the high-definition display chip.

[0040] The working principle of an image processing method based on a high-definition display chip provided by the present invention is as follows: Firstly, the image to be processed is converted into Lab color space, and the backlight reference value under the shooting environment is calculated; then, the edge map and reflection component map are extracted from the L channel. The reflection component map is obtained by calculating the complexity of the reflection component at multiple scales to obtain the local complexity map and the corresponding cumulative distribution function, and the multi-scale fusion weight is calculated based on this to perform weighted fusion of the reflection component to obtain the final reflection component map; then, the edge protection weight map is calculated based on the edge map, and the reflection component map is enhanced in combination with the backlight reference value to obtain the enhanced reflection component map, and then the a channel image and the b channel image are corrected respectively using the backlight reference value to ensure color accuracy, and the image is obtained. The invention discloses a channel corrected image and b channel corrected image; finally, the L channel image, the a channel image and the b channel image in the Lab image are replaced by the high contrast reflection image after contrast enhancement and the a channel corrected image and the b channel corrected image after color correction respectively, and then the corrected Lab image is inversely converted back to the image in the original color space, so as to obtain a high-quality enhanced processed image. The method of the invention realizes accurate control of image brightness, contrast and color by comprehensively using multi-scale analysis, edge protection, reflection component optimization and color correction technology, significantly improves the visual effect and display quality of the final image, and thus realizes the processing of the image by the high-definition display chip.

[0041] Embodiment 2 An image processing system based on a high-definition display chip. The image processing system is deployed in the high-definition display chip. In the specific implementation process, Figure 2 As shown, it shows a schematic diagram of the module structure of an image processing system based on a high-definition display chip, and the image processing system includes: The color space conversion module 100 is used to convert the image to be processed into a Lab image, and obtain a backlight reference value under the shooting environment of the image to be processed, wherein the backlight reference value is obtained based on the ambient light intensity and the ambient color temperature; The edge detection module 200 is used to separate the L channel image, the a channel image and the b channel image from the Lab image and obtain the edge map and the reflection component map of the L channel image; The contrast enhancement module 300 is used to obtain an edge protection weight map based on the edge map, and to enhance the contrast of the reflection component map in combination with the backlight reference value to obtain a high-contrast reflection map; A chromaticity correction module 400 is used to correct the a-channel image and the b-channel image respectively based on the backlight reference value to obtain an a-channel corrected image and a b-channel corrected image; The image reconstruction module 500 is used to replace the L channel image, the a channel image and the b channel image in the Lab image with the high contrast reflection image, the a channel correction image and the b channel correction image respectively, and perform color space inverse conversion on the corrected Lab image to complete image enhancement.

[0042] The working principle of an image processing system based on a high-definition display chip provided by the present invention is as follows: First, the color space conversion module 100 converts the image to be processed into a Lab color space image to obtain a Lab image, and calculates the backlight reference value under the shooting environment, where the backlight reference value is calculated based on the ambient light intensity and the ambient color temperature; then, the edge detection module 200 separates the L channel image, the a channel image and the b channel image from the Lab image, and especially extracts the edge map and the reflection component map of the L channel image; then, the contrast enhancement module 300 generates an edge protection weight map according to the edge map, and uses the backlight reference value to perform contrast enhancement on the reflection component map to obtain an enhanced high-contrast reflection map; then, the chromaticity correction module 400 uses the backlight reference value to correct the a channel image and the b channel image respectively, obtains the a channel corrected image and the b channel corrected image, and enhances the color performance; finally, the image reconstruction module 500 reconstructs the Lab image by replacing the L channel image, the a channel image and the b channel image in the Lab image, and then inversely converts the corrected Lab image back to the image of the original color space, thereby obtaining the final enhanced processed image.

[0043] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0044] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0045] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. An image processing method based on a high-definition display chip, wherein the image processing method is executed by a high-definition display chip, characterized in that: The following steps are involved: S1: converting the image to be processed into a Lab image, and obtaining a backlight reference value under the shooting environment of the image to be processed, wherein the backlight reference value is obtained based on the ambient light intensity and the ambient color temperature; S2: Separate the L channel image, the a channel image and the b channel image from the Lab image and obtain the edge map and the reflection component map of the L channel image; S3: obtaining an edge protection weight map based on the edge map, and performing contrast enhancement on the reflection component map in combination with the backlight reference value to obtain a high-contrast reflection map; S4: Correcting the a-channel image and the b-channel image respectively based on the backlight reference value to obtain an a-channel corrected image and a b-channel corrected image; S5: replace the L channel image, a channel image and b channel image in the Lab image with the high contrast reflection image, a channel correction image and b channel correction image respectively, and perform color space inverse conversion on the corrected Lab image to complete image enhancement.

2. The image processing method based on a high-definition display chip according to claim 1, characterized in that: The calculation formula of the backlight reference value is: in, is the backlight reference value, is the proportionality coefficient, is the ambient light intensity, is the reference light intensity, is the reference color temperature, is the ambient color temperature.

3. The image processing method based on a high-definition display chip according to claim 2, characterized in that: In step S2, obtaining the reflection component map includes the following steps: Reflection components of the L channel image at multiple scales are extracted respectively, and complexity calculations are performed on the reflection components at multiple scales to obtain local complexity maps corresponding to the reflection components at multiple scales; Perform histogram statistics on the local complexity graph at each scale to obtain complexity histograms corresponding to reflection components at multiple different scales; Based on the complexity histogram at each scale, the cumulative distribution functions corresponding to the reflection components at multiple different scales are obtained; Calculate the fusion weights corresponding to the reflection components at multiple different scales based on the cumulative distribution function at each scale; The reflection components at multiple scales are weighted fused based on the fusion weights to obtain a reflection component map.

4. The image processing method based on a high-definition display chip according to claim 3, characterized in that: The calculation formula of the cumulative distribution function at each scale is: in, For scale The cumulative distribution function of the reflected component under For scale The complexity of the reflection component under The number of pixels when is the total number of complexity values.

5. The image processing method based on a high-definition display chip according to claim 4, characterized in that: The complexity values ​​at multiple preset percentile positions on the cumulative distribution function are selected as the key complexity threshold.

6. The image processing method based on a high-definition display chip according to claim 5, characterized in that: The calculation formula of the fusion weight is: in, For scale The fusion weight of the reflection component under For scale The standard deviation of the Gaussian filter under is the number of selected key complexity thresholds, hour is the minimum complexity bound of the cumulative distribution function, hour is the maximum complexity boundary of the cumulative distribution function, It is a scale The critical complexity threshold under The cumulative distribution function value at is the decay speed control parameter.

7. The image processing method based on a high-definition display chip according to claim 6, characterized in that: The formula for obtaining the edge protection weight map is: is the edge protection weight map, is the pixel point in the L channel image The edge strength value of Control parameter for weight decay speed.

8. The image processing method based on a high-definition display chip according to claim 7, characterized in that: The acquisition of the high contrast reflection image comprises the following steps: The reflection component image is subjected to preliminary enhancement processing to obtain a preliminary enhanced contrast reflection image. The formula for the preliminary enhancement processing is: in, To initially enhance the contrast reflectance map, is the reflection component map, To control the proportionality factor of the enhancement degree, Pixel The local average brightness value, is the global average brightness value of the reflection component map; The preliminary enhanced contrast reflection image is subjected to final enhancement processing in combination with the edge protection weight map and the backlight reference value to obtain a high contrast reflection image. The formula for the final enhancement processing is: in, For high contrast reflectance images, is the reflection component map, To initially enhance the contrast reflectance map, is the edge protection weight map, This is the backlight reference value.

9. The image processing method based on a high-definition display chip according to claim 8, characterized in that: The correction formulas of the a-channel corrected image and the b-channel corrected image are: in, Correct the image for channel a, is the b channel corrected image, is the a channel image, is the b channel image, and are the reference color values ​​of the a channel image and the b channel image respectively. This is the backlight reference value.

10. An image processing system based on a high-definition display chip, wherein the image processing system is deployed in the high-definition display chip, characterized in that: An image processing method based on a high-definition display chip as described in any one of claims 1 to 9, comprising: A color space conversion module is used to convert the image to be processed into a Lab image and obtain a backlight reference value under the shooting environment of the image to be processed, wherein the backlight reference value is obtained based on the ambient light intensity and the ambient color temperature; An edge detection module is used to separate an L channel image, an a channel image and a b channel image from the Lab image and obtain an edge map and a reflection component map of the L channel image; A contrast enhancement module is used to obtain an edge protection weight map based on the edge map, and to enhance the contrast of the reflection component map in combination with the backlight reference value to obtain a high-contrast reflection map; A chromaticity correction module, used to correct the a-channel image and the b-channel image respectively based on the backlight reference value to obtain an a-channel corrected image and a b-channel corrected image; The image reconstruction module is used to replace the L channel image, a channel image and b channel image in the Lab image with the high contrast reflection map, a channel correction image and b channel correction image respectively, and perform color space inverse conversion on the corrected Lab image to complete image enhancement.

Images