Display method, device and apparatus

Abstract

The application discloses a display method, device and equipment, and relates to the technical field of display. The disclosed method comprises the following steps: acquiring an input image; determining target importance scores of each pixel in the input image according to image features of the input image; and driving each display area to display based on different target display parameters corresponding to the target importance scores of the pixels in the display area where the pixels are located. Since the target importance scores of each pixel are determined according to the image features of the input image, and the display areas where different pixels are located are driven differently based on the target importance scores, instead of uniformly adjusting the whole screen without distinction, the overall power consumption can be reduced, the overall picture quality can be prevented from being reduced, and the viewing experience is effectively improved.

Description

Technical Field

[0001] This application relates to the field of display technology, and in particular to display methods, apparatus and devices. Background Technology

[0002] With the development of display technology, large-size displays such as 116-inch giant TVs and large conference tablets are becoming increasingly widely used. While larger screen sizes offer a more immersive visual experience, a significant problem arises: screen power consumption increases dramatically with size. Larger screen areas require more pixels to drive, and the backlight or self-emissive units consume more power, resulting in high overall power consumption. This leads to higher operating costs for users and places greater demands on the device's heat dissipation and energy efficiency.

[0003] To reduce power consumption in large-size displays, existing technologies typically employ a method of uniformly lowering all display parameters across the screen. For example, the refresh rate of the entire screen is uniformly reduced from a high refresh rate (e.g., 120Hz) to a lower refresh rate (e.g., 60Hz), or the brightness of the entire screen is uniformly dimmed. This approach reduces the overall power consumption of the screen driving circuitry and light-emitting units by uniformly lowering the parameters across the entire image, thus achieving energy savings to some extent.

[0004] However, because the above method uniformly reduces display parameters across all areas of the screen without differentiation, content in different areas of the screen suffers the same degree of quality degradation. Regardless of the level of attention given to content in different areas of the screen, their display parameters are reduced synchronously, resulting in a decline in overall display quality and affecting the viewing experience. Summary of the Invention

[0005] The main purpose of this application is to provide a display method, apparatus, and device to solve the technical problem of declining overall display quality of existing images, which affects the viewing experience.

[0006] To achieve the above objectives, this application proposes a display method, the display method comprising: Obtain the input image; Based on the image features of the input image, determine the target importance score of each pixel in the input image; For the display areas containing pixels with different target importance scores, different display parameters are used based on the corresponding target importance score.

[0007] In one embodiment, the image features include semantic features and visual saliency features. The step of determining the target importance score of each pixel in the input image based on the image features of the input image includes: Extract the semantic features and visual saliency features of each pixel in the input image; Assign a first importance score to the corresponding pixel based on the semantic features; A second importance score is assigned to the corresponding pixel based on the visual saliency features of each pixel; The target importance score of each pixel is determined based on the first importance score and the second importance score.

[0008] In one embodiment, the step of assigning a first importance score to the corresponding pixel based on the semantic feature includes: Determine the current scene information corresponding to the input image; The semantic category to which each pixel belongs is determined based on the semantic features; From multiple preset mapping relationships, a target mapping relationship associated with the current scene information is obtained. The preset mapping relationship includes the mapping relationship between the semantic category and the first importance score. The first importance score corresponding to the same semantic category is different in different preset mapping relationships. Based on the target mapping relationship, each pixel is assigned a corresponding first importance score for its semantic category.

[0009] In one embodiment, the step of assigning a second importance score to the corresponding pixel based on the visual saliency features of each pixel includes: Determine the neighboring pixels corresponding to each pixel, wherein the neighboring pixels are pixels within a preset window centered on the corresponding pixel; The difference between the visual salient features of each pixel and the visual salient features of the corresponding neighboring pixels is determined to obtain the feature difference; Each pixel is assigned a second importance score based on the feature differences.

[0010] In one embodiment, the step of determining the target importance score of each pixel based on the first importance score and the second importance score includes: Obtain the previous frame image of the input image; Based on the previous frame image and the input image, determine the position change information of each pixel in the input image; The motion characteristics of each pixel are determined based on the position change information; Each pixel is assigned a third importance score based on the aforementioned motion features; The target importance score of each pixel is determined based on the first importance score, the second importance score, and the third importance score.

[0011] In one embodiment, the step of determining the target importance score of each pixel based on the first importance score, the second importance score, and the third importance score includes: Select a target weight coefficient combination corresponding to the current scene information from multiple sets of preset weight coefficients. The target weight coefficient combination includes a first weight coefficient corresponding to the first importance score, a second weight coefficient corresponding to the second importance score, and a third weight coefficient corresponding to the third importance score. For each pixel, the first importance score, the second importance score, and the third importance score of the pixel are fused based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient to obtain the target importance score of each pixel.

[0012] In one embodiment, the step of driving the display area to display each pixel in the display panel using different target display parameters based on the corresponding target importance score includes: The corresponding brightness adjustment coefficient is determined based on the score range in which the target importance score of each pixel is located; The original display parameters are adjusted according to the brightness adjustment coefficients to obtain the target display parameters corresponding to each pixel; For each pixel in the display area of ​​the display panel, the display area is driven to display according to each target display parameter.

[0013] In one embodiment, after the step of driving each of the pixels to display in the display area of ​​the display panel according to each of the target display parameters, the method further includes: The display panel is divided into several backlight zones; Calculate the average target importance score of each pixel within each backlight partition to obtain the average importance score of each backlight partition; Based on the score range in which each of the aforementioned average importance scores is located, the target backlight driving coefficient corresponding to each of the aforementioned backlight zones is determined; According to the target backlight driving coefficient, the backlight source in the corresponding backlight zone is driven to emit light.

[0014] Furthermore, to achieve the above objectives, this application also proposes a display driving device, the display driving device comprising: Image input interface, used to acquire input images; A control chip is used to determine the target importance score of each pixel in the input image based on the image features of the input image; The display driving circuit is used to display the display areas where pixels with different target importance scores are located using different display parameters based on the corresponding target importance scores.

[0015] In addition, to achieve the above objectives, this application also proposes a display device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the display method as described above.

[0016] One or more technical solutions proposed in this application have at least the following technical effects: The display method provided in this application includes: acquiring an input image; determining the target importance score of each pixel in the input image based on the image features of the input image; and driving the display of each pixel in the display area of ​​the display panel using different target display parameters based on the corresponding target importance score. Since this application determines the target importance score of each pixel based on the image features of the input image and drives the display of different pixels in a differentiated manner based on the target importance score, rather than uniformly adjusting the entire screen indiscriminately, it can reduce overall power consumption while avoiding a decrease in overall image quality, effectively improving the viewing experience. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the first embodiment of the method shown in this application; Figure 2 This is a flowchart illustrating the second embodiment of the method shown in this application; Figure 3 This is a schematic diagram of content segmentation in the second embodiment of the display method of this application; Figure 4 This is a flowchart illustrating the third embodiment of the method shown in this application; Figure 5 This is a schematic diagram of the module structure of the display driving device in this application; Figure 6 This is a schematic diagram of the structure of a display device according to an embodiment of this application.

[0020] Explanation of icon numbers: 10, Image input interface; 20, Control chip; 30, Drive circuit; 1001, Processing device; 1002, ROM; 1003, Storage device; 1004, RAM; 1005, Bus; 1006, I / O interface; 1007, Input device; 1008, Output device; 1009, Communication device; A, Character category; B, Cloud category; C, Sky category.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] The main solution of this application embodiment is: to determine the target importance score of each pixel in the input image based on the image features of the input image; and to drive the display area of ​​each pixel in the display panel to display based on the corresponding target importance score using different target display parameters.

[0025] Because current technology uniformly reduces display parameters across all areas of the screen without differentiation, content in different areas of the screen suffers the same degree of quality degradation. Regardless of the level of attention given to content in different areas of the screen, their display parameters are reduced simultaneously, resulting in a decline in overall display quality and affecting the viewing experience.

[0026] This application provides a solution that determines the target importance score of each pixel based on the image features of the input image, and performs differentiated display driving on the display areas where different pixels are located based on the target importance score, rather than making uniform adjustments to the entire screen indiscriminately. Therefore, it can reduce overall power consumption while avoiding a decline in overall image quality, effectively improving the viewing experience.

[0027] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or display device capable of performing the above functions. The following description uses a display device as an example to illustrate this embodiment and the subsequent embodiments.

[0028] Based on this, the embodiments of this application provide a display method, referring to... Figure 1 , Figure 1This is a flowchart illustrating the first embodiment of the method shown in this application.

[0029] In this embodiment, the display method includes steps S10 to S30: Step S10: Obtain the input image.

[0030] It should be noted that the input image can be a single frame from a video sequence, such as a frame from a video conference, a frame from a movie, or a frame from a game.

[0031] In a practical implementation, the display device can receive video signals through an image input interface and obtain the input image from the video signal as the frame that needs to be processed.

[0032] Step S20: Determine the target importance score of each pixel in the input image based on the image features of the input image.

[0033] It should be noted that image features can be feature information that reflects the content attributes contained in each pixel or region of an image, such as one or more of the color features, brightness features, texture features, edge features, and shape features of each pixel in the image, or high-level semantic features such as whether a certain region in the image is a face region or a text region.

[0034] Understandably, target importance score can be a quantitative indicator used to measure the visual attention of each pixel in the input image. For example, a pixel with a higher target importance score indicates that the pixel is more visually important, while a pixel with a lower target importance score indicates that the pixel is less visually important.

[0035] In practical implementation, after acquiring the input image, the display device can perform content analysis on the input image, extract image features, and input the extracted image features into a pre-trained analysis model. The analysis model then outputs a target importance score for each pixel based on the image features. The analysis model can be based on a convolutional neural network. The input to the analysis model is the input image or image features extracted from the input image. The output of the analysis model is a target importance score map of the same size as the input image, where the value of each pixel in the target importance score map is the target importance score for that pixel.

[0036] Step S30: For each pixel in the display area of ​​the display panel, different target display parameters are used to drive each display area to display based on the corresponding target importance score.

[0037] It should be noted that the display area can be the physical display position of each pixel in the input image on the display panel.

[0038] Understandably, the target display parameters can be parameters used to control the display panel to display images, such as at least one of the following: brightness parameters, refresh rate parameters, grayscale driving voltage parameters, and color depth parameters.

[0039] In practical implementation, the display device can apply different display parameters to the display areas corresponding to different pixels on the display panel based on the target importance score of each pixel. Specifically, the display device uses higher display parameters for display areas corresponding to pixels with higher target importance scores, and lower display parameters for display areas corresponding to pixels with lower target importance scores. Because lower display parameters are used for display areas corresponding to pixels with lower target importance scores, the display power consumption of these areas is reduced, resulting in a decrease in the overall display power consumption of the input image compared to using uniformly higher display parameters for all display areas. Therefore, by applying different display parameters to the display areas corresponding to different pixels in the image based on the differences in the target importance scores of each pixel, the display device reduces overall display power consumption while ensuring the display quality of high-importance areas.

[0040] This embodiment acquires an input image; determines the target importance score of each pixel in the input image based on its image features; and drives the display of each pixel in the display area of ​​the display panel using different target display parameters based on the corresponding target importance score. Because this embodiment determines the target importance score of each pixel based on the image features of the input image and performs differentiated display driving on the display areas of different pixels based on the target importance score, rather than making indiscriminate adjustments to the entire screen, it can reduce overall power consumption while avoiding a decrease in overall image quality, effectively improving the viewing experience.

[0041] Based on the first embodiment of this application, a second embodiment of this application is proposed. In the second embodiment, content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the method shown in this application.

[0042] In this embodiment, the image features include semantic features and visual saliency features, and step S20 includes steps S201 to S204: Step S201: Extract the semantic features and visual saliency features of each pixel in the input image.

[0043] It should be noted that semantic features can be the attribute features of each pixel in the image at the content level, such as at least one of the pixel's texture features, shape features, and contextual relationship features between the pixel and its surrounding pixels. Semantic features are used to characterize the information of the pixel in the image content dimension, which is different from the low-level visual attributes of the pixel such as color and brightness.

[0044] Understandably, visual salient features can be the feature values ​​of each pixel in an image in terms of underlying visual attributes such as color, brightness, and texture. For example, the red channel value, green channel value, and blue channel value of a pixel, or the brightness value of a pixel. Visual salient features reflect the inherent attributes of the pixel at the visual perception level.

[0045] In a practical implementation, the adjustment device can input the input image into a pre-trained content segmentation model. This content segmentation model can be trained on a convolutional neural network using sample images labeled with semantic categories. The trained content segmentation model can extract semantic features from each pixel in the input image, such as texture features, shape features, and contextual relationship features between the pixel and its surrounding pixels.

[0046] Furthermore, the display device can acquire the color channel values ​​and brightness values ​​of each pixel in the input image, and use the acquired color channel values ​​and brightness values ​​as the visual salient features of each pixel.

[0047] Step S202: Assign a first importance score to the corresponding pixel based on the semantic features.

[0048] It should be noted that the first importance score can be a quantitative value determined based on the semantic features of the pixel, used to characterize the importance of the pixel at the semantic content level. For example, pixels belonging to the people or text categories are assigned a higher first importance score, while pixels belonging to the background or sky categories are assigned a lower first importance score.

[0049] In practical implementation, the display device can determine the first importance score of a pixel based on the object category or scene category to which that pixel belongs, as reflected by the semantic features of that pixel. Pixels reflecting important content are assigned a higher first importance score than pixels reflecting less important content.

[0050] For example, after obtaining the semantic features of each pixel in the video conference frame, the display device assigns a first importance score to each pixel based on these features. For pixels in the participant's face area, the semantic features indicate that these pixels belong to the "person" category. Since people are the focus of attention when watching a video conference, the display device assigns a high first importance score to pixels in the face area. For pixels in the background bookshelf area, the semantic features indicate that these pixels belong to the "background" category. Since the background is secondary content that people don't pay attention to when watching a video conference, the display device assigns a low first importance score to pixels in the background bookshelf area.

[0051] In one feasible implementation, step S202 includes steps S2021 to S2024: Step S2021: Determine the current scene information corresponding to the input image.

[0052] It should be noted that the current scene information can be an identifier indicating the current application scene of the input image. For example, the scene identifier could be a "meeting scene," a "movie viewing scene," or a "game scene." This identifier can be a preset numerical code, a string, or any data marker that can distinguish different scenes. After receiving this identifier, the display device can clearly identify the application environment that needs to be adapted.

[0053] In specific implementations, the display device may obtain current scene information in the following ways, including but not limited to: the display device receives a display mode selection command input by the user through the operation interface or remote control, which carries a scene identifier, and the display device extracts and determines the scene identifier as the current scene information; or, the display device analyzes the content of the input image, identifies the current scene type of the input image, generates a scene identifier corresponding to the identified scene type, and uses it as the current scene information.

[0054] Step S2022: Determine the semantic category to which each pixel belongs based on the semantic features.

[0055] It should be noted that semantic categories can be category labels representing the object type or scene type to which each pixel in the input image belongs at the content level, such as one of the following: people category, text category, building category, sky category, and background category.

[0056] In practical implementation, the display device compares the semantic features of each pixel with feature templates corresponding to multiple pre-defined semantic categories, determines the feature template with the highest degree of matching to the semantic features of each pixel, and identifies the semantic category to which the pixel belongs as the semantic category corresponding to that feature template. The pre-defined feature templates corresponding to the multiple semantic categories are obtained through statistical learning of the semantic features of a large number of sample pixels for each semantic category, and each feature template represents a typical semantic feature pattern of a semantic category. For example, refer to... Figure 3 , Figure 3 This is a schematic diagram of content segmentation in the second embodiment of the display method of this application. Figure 3 In this context, the display device can determine the semantic features of each pixel in the input image. Figure 3 The categories are: People (A), Clouds (B), and Sky (C).

[0057] Step S2023: Obtain the target mapping relationship associated with the current scene information from multiple preset mapping relationships.

[0058] The preset mapping relationship includes the mapping relationship between the semantic category and the first importance score. The first importance score corresponding to the same semantic category is different in different preset mapping relationships.

[0059] It should be noted that the preset mapping relationship can be a pre-defined data set used to record the correspondence between different semantic categories and different first importance scores, such as the correspondence stored in the form of tables, lists or key-value pairs. Each preset mapping relationship corresponds to a use case.

[0060] Understandably, the target mapping relationship can be a set of mapping relationships selected from multiple preset mapping relationships that match the current scene information, used to convert the semantic category of each pixel into the corresponding first importance score in the current usage scenario.

[0061] In its implementation, the display device pre-stores multiple preset mapping relationships, each corresponding to different scene information. The same semantic category corresponds to different first importance scores in different preset mapping relationships. The display device matches the current scene information with the scene information corresponding to each preset mapping relationship, and determines the preset mapping relationship corresponding to the successfully matched scene information as the target mapping relationship associated with the current scene information.

[0062] Step S2024: Assign a corresponding first importance score to the semantic category of each pixel based on the target mapping relationship.

[0063] In its implementation, for each pixel, the display device searches for the first importance score corresponding to that semantic category in the target mapping relationship, based on the semantic category to which the pixel belongs, and assigns the found first importance score to the pixel. Since the same semantic category corresponds to different first importance scores in preset mapping relationships for different scene information, and the target mapping relationship is a mapping relationship associated with the current scene information, the first importance score assigned to each pixel by the display device can be adapted to the current scene. This ensures that semantic categories that are more important in the current scene receive higher first importance scores, while semantic categories that are less important in the current scene receive lower first importance scores.

[0064] Step S203: Assign a second importance score to the corresponding pixel based on the visual saliency features of each pixel.

[0065] It should be noted that the second importance score can be a quantitative value determined based on the visual saliency features of a pixel, used to characterize the importance of the pixel in the visual saliency dimension. For example, pixels that are significantly different from surrounding pixels in color and brightness are given a higher second importance score, while pixels that are less different from surrounding pixels are given a lower second importance score.

[0066] In practical implementation, the display device can determine the second importance score of a pixel based on the degree of prominence of that pixel in terms of color, brightness, etc., as reflected by the visual salient features of that pixel. Specifically, the more prominent the visual salient features of a pixel, the higher the second importance score assigned to that pixel by the display device; the less prominent the visual salient features of a pixel, the lower the second importance score assigned to that pixel by the display device.

[0067] In one feasible implementation, step S203 includes steps S2031 to S2033: Step S2031: Determine the neighboring pixels corresponding to each pixel, wherein the neighboring pixels are pixels within a preset window centered on the corresponding pixel.

[0068] It should be noted that the preset window can be a pre-defined region delineation parameter used to determine the range of neighboring pixels. The preset window defines the pixel range expanding outwards from the current pixel. For example, the preset window can be a rectangular region with a size of M×N pixels, where M is the number of pixels contained in the width direction of the window, N is the number of pixels contained in the height direction of the window, and both M and N are preset positive integers.

[0069] In a specific implementation, for each pixel in the input image, the display device determines all pixels within the preset window, centered on that pixel, according to the range defined by the preset window, and identifies these pixels as the neighboring pixels of that pixel.

[0070] Step S2032: Determine the difference between the visual salient features of each pixel and the visual salient features of the corresponding neighboring pixels to obtain the feature difference.

[0071] It should be noted that feature difference can be a quantitative value used to characterize the degree of difference between the visual salient features of the current pixel and the visual salient features of the corresponding neighboring pixels, such as color difference value and brightness difference value. The larger the feature difference, the less visually similar the current pixel is to its surrounding pixels, and the smaller the feature difference, the closer the current pixel is to its surrounding pixels.

[0072] In its implementation, the display device acquires the visual salient features of each pixel, and simultaneously acquires the visual salient features of its neighboring pixels. The display device compares the visual salient features of the current pixel with those of its neighboring pixels, calculates the difference between them, and uses this difference as the feature difference for that pixel. Specifically, when comparing the visual salient features of the current pixel with those of its neighboring pixels, the display device can compare the color value of the current pixel with the color values ​​of its neighboring pixels to calculate the color difference, and / or compare the brightness value of the current pixel with the brightness values ​​of its neighboring pixels to calculate the brightness difference. The resulting color difference and / or brightness difference are the feature differences.

[0073] Step S2033: Assign a second importance score to each pixel based on the feature differences.

[0074] In its implementation, the display device determines the second importance score for each pixel based on the magnitude of its feature difference and according to a preset correspondence between feature differences and second importance scores. Specifically, a pixel with a larger feature difference indicates a more significant visual difference from its surrounding pixels, and the display device assigns it a higher second importance score; conversely, a pixel with a smaller feature difference indicates a closer visual similarity to its surrounding pixels, and the display device assigns it a lower second importance score.

[0075] Step S204: Determine the target importance score of each pixel based on the first importance score and the second importance score.

[0076] In the specific implementation, the display device performs a fusion operation on the first importance score and the second importance score of each pixel, and uses the result of the fusion operation as the target importance score of the pixel.

[0077] In one feasible implementation, step S204 includes steps S2041 to S2045: Step S2041: Obtain the previous frame image of the input image.

[0078] It should be noted that the previous frame image can be an image in the video sequence that is adjacent to the input image and precedes the input image in time sequence. For example, when the input image is the current frame, the previous frame image is the frame before the current frame.

[0079] In a specific implementation, the display device caches image data of at least one frame preceding the input image. After determining the first importance score and the second importance score of each pixel in the input image, an image adjacent to the input image and preceding the input image in time sequence can be read from the cache and used as the previous frame image.

[0080] Step S2042: Based on the previous frame image and the input image, determine the position change information of each pixel in the input image.

[0081] It should be noted that position change information can be used to characterize the degree and direction of spatial position changes of each pixel in the input image relative to the corresponding pixel in the previous frame. For example, if a pixel moves a certain number of pixels horizontally and vertically between two frames, the position change information reflects the movement of that pixel between consecutive frames.

[0082] In its implementation, for each pixel in the input image, the display device can find a matching pixel in the previous frame, determine the displacement between the pixel's position in the input image and its corresponding position in the previous frame, and use this displacement as the pixel's position change information. Specifically, when searching for the corresponding pixel in the previous frame, the display device can compare the similarity between a local image patch centered on the pixel and an image patch of the same size in the previous frame, and determine the center pixel of the image patch with the highest similarity as the corresponding pixel.

[0083] Step S2043: Determine the motion characteristics of each pixel based on the position change information.

[0084] It should be noted that motion features can be feature information used to characterize the motion attributes of each pixel in the input image between consecutive frames, such as motion amplitude features. The larger the motion amplitude, the greater the distance the pixel moves between two consecutive frames, and the smaller the motion amplitude, the smaller the distance the pixel moves between two consecutive frames.

[0085] In practical implementation, the display device can calculate the motion feature corresponding to each pixel based on the displacement contained in the pixel's position change information. Specifically, the display device can sum the squares of the horizontal and vertical displacements in the position change information and then take the square root, using the calculated total displacement as the pixel's motion amplitude feature. Alternatively, the display device can directly use the horizontal and vertical displacements from the position change information as the pixel's motion feature.

[0086] Step S2044: Assign a third importance score to each pixel based on the motion features.

[0087] It should be noted that the third importance score can be a quantitative value determined based on the motion characteristics of a pixel, used to characterize the importance of the pixel in the motion dimension. For example, pixels with larger motion amplitude are assigned a higher third importance score, while pixels with smaller motion amplitude or that are stationary are assigned a lower third importance score.

[0088] In its implementation, the display device determines the third importance score for each pixel based on the degree of motion represented by its motion features. A pixel with a higher degree of motion represented by its motion features indicates more significant movement within the image, and the display device assigns it a higher third importance score. Conversely, a pixel with a lower degree of motion represented by its motion features, or zero motion, indicates that the pixel is relatively stationary within the image, and the display device assigns it a lower third importance score.

[0089] Step S2045: Determine the target importance score of each pixel based on the first importance score, the second importance score, and the third importance score.

[0090] In the specific implementation, the display device performs a fusion operation on the first importance score, the second importance score, and the third importance score of each pixel, and uses the result of the fusion operation as the target importance score of the pixel.

[0091] It should be understood that, since the target importance score is obtained by fusing scores from three dimensions—semantic content, visual saliency, and motion—it can more comprehensively and accurately reflect the overall importance of each pixel in the input image compared to using scores from only one or two of these dimensions.

[0092] In one feasible implementation, step S2045 may include steps S20451~S20452: Step S20451: Select the target weight coefficient combination corresponding to the current scene information from multiple sets of preset weight coefficients.

[0093] The target weight coefficient combination includes a first weight coefficient corresponding to the first importance score, a second weight coefficient corresponding to the second importance score, and a third weight coefficient corresponding to the third importance score.

[0094] It should be noted that the preset weight coefficients can be multiple sets of weight values ​​that are pre-set and used to perform weighted calculations on the importance scores of different dimensions. Each set of weight values ​​corresponds to a different use case, and the sum of the weight coefficients in each set of weight values ​​is 1.

[0095] Understandably, the target weight coefficient combination can be a set of weight coefficients selected from multiple preset weight coefficients that match the current scene information. The target weight coefficient combination includes the first weight coefficient corresponding to the first importance score, the second weight coefficient corresponding to the second importance score, and the third weight coefficient corresponding to the third importance score, which are used to weight and fuse the importance scores of the three dimensions in the current scene.

[0096] In practice, the display device pre-stores multiple sets of preset weight coefficients, each corresponding to different scene information. The importance score of the same dimension may correspond to different weight coefficients in different combinations of preset weight coefficients. The display device matches the current scene information with the scene information corresponding to each set of preset weight coefficients, and determines the set of preset weight coefficients corresponding to the successfully matched scene information as the target weight coefficient combination.

[0097] Step S20452: For each pixel, the first importance score, the second importance score, and the third importance score of the pixel are fused based on the first weight coefficient, the second weight coefficient, and the third weight coefficient to obtain the target importance score of each pixel.

[0098] In the specific implementation, the following preset score fusion formula is invoked:

[0099] In the formula, As the target importance score, The first weighting coefficient, This is the second weighting coefficient. This is the third weighting coefficient. As the most important score, As the second most important score, It is the third most important score.

[0100] For each pixel, the display device substitutes the first weighting coefficient, the second weighting coefficient, the third weighting coefficient, the first importance score, the second importance score, and the third importance score into a preset score fusion formula. The first importance score is multiplied by the first weighting coefficient to obtain the first weighted score; the second importance score is multiplied by the second weighting coefficient to obtain the second weighted score; and the third importance score is multiplied by the third weighting coefficient to obtain the third weighted score. Then, the first weighted score, the second weighted score, and the third weighted score are added together, and the result is used as the target importance score for that pixel.

[0101] For the sake of understanding, the following explanation is provided by way of example, but does not impose any specific limitations on this embodiment.

[0102] For example, a display device receives a video conference image as input, with a speaker in the center and bookshelves and walls in the background.

[0103] The display device segments the input image to identify the speaker's face region and assigns a first importance score of 0.9 to all pixels within that face region. The display device identifies the bookshelf and wall regions as background and assigns a first importance score of 0.1 to the pixels in the background region. The display device does not identify the bright-colored brooch worn by the speaker as a person region and assigns a first importance score of 0.1 to the pixels in the brooch region.

[0104] The display device performs visual saliency detection on the input image, calculating the degree of difference in color and brightness between each pixel and its surrounding pixels. A significant color and brightness contrast exists between the face area and the background area, so the display device assigns a second importance score of 0.8 to the pixels in the face area. A large color difference exists between the bright-colored brooch worn by the speaker and their clothing, so the display device assigns a second importance score of 0.6 to the pixels in the brooch area. The background bookshelf and wall areas have uniform colors and minimal differences, so the display device assigns a second importance score of 0.1 to the pixels in the background area.

[0105] The display device performs motion analysis on the input image, comparing the positional changes of each pixel in the input image with those in the previous frame. When the speaker is speaking, there are slight movements of the mouth and hands; the display device assigns a third importance score of 0.7 to the pixels in the face and hand areas. The brooch area and the background bookshelf and wall areas remain stationary; the display device assigns a third importance score of 0 to the pixels in the brooch area and the background area.

[0106] The display device performs a weighted fusion operation on the first importance score, the second importance score, and the third importance score of each pixel, with the first weight coefficient being 0.5, the second weight coefficient being 0.3, and the third weight coefficient being 0.2.

[0107] For a single pixel in the face region, the target importance score calculated by the display device is: 0.5×0.9+0.3×0.8+0.2×0.7=0.45+0.24+0.14=0.83.

[0108] For a single pixel in the brooch area, the target importance score calculated by the display device is: 0.5×0.1+0.3×0.6+0.2×0=0.05+0.18+0=0.23.

[0109] For a pixel in a pure background area, the target importance score calculated by the display device is: 0.5×0.1+0.3×0.1+0.2×0=0.05+0.03+0=0.08, which is close to 0.

[0110] The display device generates a target importance score map of the same size as the input image based on the target importance score of each pixel. Pixels in the face area have a high score of 0.83, pixels in the brooch area have a medium score of 0.23, and pixels in the background area have a score close to 0. This target importance score map indicates the visual importance of each area in the image.

[0111] It should be understood that since the target weight coefficient combination is selected from multiple preset weights based on the current scene information, the fused target importance score can be adapted to the current scene, so that the score corresponding to the dimension that receives more attention in the current scene occupies a larger proportion in the target importance score, thereby making the target importance score more accurately reflect the actual importance of each pixel in the current scene.

[0112] Based on the first and second embodiments of this application, a third embodiment of this application is proposed. In this third embodiment, content that is the same as or similar to the first and second embodiments described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 4 , Figure 4 This is a flowchart illustrating the third embodiment of the method shown in this application.

[0113] In this embodiment, step S30 includes steps S301 to S303: Step S301: Determine the corresponding brightness adjustment coefficient based on the score range in which the target importance score of each pixel is located.

[0114] It should be noted that the target importance score is a normalized value that represents the visual importance of each pixel in the displayed image. Its value ranges from [0, 1], with a higher value indicating higher visual importance. Since the human eye has different sensitivities to brightness changes in different importance areas, applying a uniform brightness adjustment strategy to all pixels would either result in image quality degradation in key areas or ineffective energy saving in non-key areas. Therefore, based on the characteristics of human visual attention, the target importance score can be divided into multiple intervals to apply differentiated brightness adjustment intensities to pixels within different intervals.

[0115] For example, in one feasible implementation, the [0, 1] interval can be divided into a first score interval (e.g., [0, 0.2]), a second score interval (e.g., [0.2, 0.6]), and a third score interval (e.g., [0.6, 1]). When the target importance score of a pixel is in the first score interval, it indicates that the pixel belongs to a low importance region, that is, the region where the pixel is located is a region that the human eye is not sensitive to (e.g., static background, sky, or solid color areas, etc., which are not areas of visual attention); when the target importance score of a pixel is in the second score interval, it indicates that the pixel belongs to a medium importance interval, that is, the region where the pixel is located is a region where the human eye has average visual sensitivity, belonging to the transition region between the area of ​​visual attention and the background region; when the target importance score of a pixel is in the third score interval, it indicates that the pixel belongs to a high importance interval, that is, the region where the pixel is located is a region where the human eye is highly sensitive to visual information (e.g., faces, text, or moving subjects, etc.).

[0116] Understandably, the brightness adjustment coefficient can be a parameter used to adjust the original display parameters. The higher the importance score of a pixel, the closer its brightness adjustment coefficient is to 1 or greater than 1. When the brightness adjustment coefficient is greater than 1, it indicates that the original display parameters are being enhanced, resulting in an increase in pixel brightness relative to the original display brightness; when the brightness adjustment coefficient is equal to 1, it indicates that the original display parameters are not being adjusted; when the brightness adjustment coefficient is less than 1, it indicates that the original display parameters are being attenuated, resulting in a decrease in pixel brightness relative to the original display brightness.

[0117] It should be noted that the original display parameters can be parameters that indicate the expected display brightness of each pixel, including but not limited to grayscale values ​​and RGB component values. The larger the value of the original display parameters of a pixel, the higher the display brightness of that pixel during display; the smaller the value of the original display parameters of a pixel, the lower the display brightness of that pixel during display.

[0118] In practical implementation, for different score intervals, a first mapping rule between the target importance score and the brightness adjustment coefficient can be pre-configured, so that different score intervals correspond to different first mapping rules, thereby achieving differentiated brightness adjustment intensities in different importance areas. After obtaining the target importance score of each pixel, the display device compares the target importance score of each pixel with the preset score intervals to determine the score interval to which each pixel's target importance score belongs. Subsequently, for each pixel's score interval, the display device uses the corresponding first mapping rule to map the target importance score to the corresponding brightness adjustment coefficient. The higher the score interval to which the pixel's target importance score belongs, the larger the brightness adjustment coefficient obtained by mapping the target importance score.

[0119] Step S302: Adjust the original display parameters according to the brightness adjustment coefficients to obtain the target display parameters corresponding to each pixel.

[0120] In practice, the display device multiplies the brightness adjustment coefficient corresponding to each pixel with the original display parameters, and the product is used as the target display parameter for the corresponding pixel. Since the brightness adjustment coefficient is determined based on the target importance score of the pixel, the higher the target importance score, the larger the brightness adjustment coefficient. Therefore, through multiplication, the target display parameters of pixels in high importance areas remain unchanged or are improved relative to the original display parameters, while the target display parameters of pixels in low importance areas are compressed and reduced relative to the original display parameters, thereby achieving differentiated adjustment for different importance areas.

[0121] In one feasible implementation, the following example illustrates the concept of a score interval comprising a first score interval, a second score interval, and a third score interval.

[0122] In this implementation, when the target importance score of any pixel falls within the first score range, a pre-constructed first preset parameter formula is invoked:

[0123] In the formula, Indicates the target display parameters. Indicates the original display parameters. Indicates the score representing the importance of the objective. This represents the first baseline coefficient (e.g., 0.92). This represents the first weighting coefficient (e.g., 0.12). This indicates the lower limit value of the original display parameters. This indicates the upper limit of the original display parameters. When the original display parameters are grayscale values, Equal to 0, It equals 255.

[0124] Specifically, for the aforementioned first preset parameter formula, by multiplying the first weighting coefficient by the target importance score, and then adding the multiplication result to the first benchmark coefficient, the resulting value is the brightness adjustment coefficient when the target importance score belongs to the first score range; subsequently, this brightness adjustment coefficient is multiplied by the original display parameters to adjust the original display parameters, obtaining the adjusted display parameters; finally, through... Clip The function restricts the adjusted display parameter to between the upper limit and the lower limit of the original display parameter. That is, when the adjusted display parameter is less than the lower limit of the original display parameter, the lower limit of the original display parameter is output as the target display parameter; when the adjusted display parameter is greater than the upper limit of the original display parameter, the upper limit of the original display parameter is output as the target display parameter; and when the adjusted display parameter is between the upper limit and the lower limit of the original display parameter, its adjusted display parameter is output as the target display parameter.

[0125] When the target importance score of any pixel falls within the second score interval, the pre-constructed second preset parameter formula is invoked:

[0126] In the formula, Indicates the target display parameters. Indicates the original display parameters. Indicates the score representing the importance of the objective. This represents the second baseline coefficient (e.g., 0.94). This represents the second weighting coefficient (e.g., 0.06). This indicates the lower limit value of the original display parameters. This indicates the upper limit of the original display parameters. When the original display parameters are grayscale values, Equal to 0, It equals 255.

[0127] Specifically, for the aforementioned second preset parameter formula, by multiplying the second weighting coefficient by the target importance score, and then adding the multiplication result to the second benchmark coefficient, the resulting value is the brightness adjustment coefficient when the target importance score falls within the second score range. Subsequently, this brightness adjustment coefficient is multiplied by the original display parameters to adjust the original display parameters, obtaining the adjusted display parameters. Finally, through... ClipThe function restricts the adjusted display parameter to between the upper limit and the lower limit of the original display parameter. That is, when the adjusted display parameter is less than the lower limit of the original display parameter, the lower limit of the original display parameter is output as the target display parameter; when the adjusted display parameter is greater than the upper limit of the original display parameter, the upper limit of the original display parameter is output as the target display parameter; and when the adjusted display parameter is between the upper limit and the lower limit of the original display parameter, its adjusted display parameter is output as the target display parameter.

[0128] When the target importance score of any pixel falls within the third score range, the pre-built third preset parameter formula is invoked:

[0129] In the formula, Indicates the target display parameters. Indicates the original display parameters. Indicates the score representing the importance of the objective. This represents the third baseline coefficient (e.g., 1). This represents the third weighting coefficient (e.g., 0.05). f This represents the lower limit of the third fractional interval. This indicates the lower limit value of the original display parameters. This indicates the upper limit of the original display parameters. When the original display parameters are grayscale values, Equal to 0, It equals 255.

[0130] Specifically, for the aforementioned third preset parameter formula, by subtracting the lower limit of the third score interval from the target importance score, multiplying the difference by the third weighting coefficient, and then adding the multiplication result to the third benchmark coefficient, the result is the brightness adjustment coefficient when the target importance score belongs to the third score interval. Subsequently, this brightness adjustment coefficient is multiplied by the original display parameters to adjust the original display parameters, obtaining the adjusted display parameters. Finally, through... Clip The function restricts the adjusted display parameter to between the upper limit and the lower limit of the original display parameter. That is, when the adjusted display parameter is less than the lower limit of the original display parameter, the lower limit of the original display parameter is output as the target display parameter; when the adjusted display parameter is greater than the upper limit of the original display parameter, the upper limit of the original display parameter is output as the target display parameter; and when the adjusted display parameter is between the upper limit and the lower limit of the original display parameter, its adjusted display parameter is output as the target display parameter.

[0131] Step S303: For each pixel in the display area of ​​the display panel, drive each display area to display according to each target display parameter.

[0132] In its implementation, the display device outputs the target display parameters corresponding to each pixel to the display driving circuit. The display driving circuit generates a corresponding driving signal based on the received target display parameters and applies it to the driving electrodes of the corresponding pixels in the display panel, driving each pixel to display at the brightness indicated by the target display parameters. Since the target display parameters for different pixels are obtained after differentiated adjustment based on their respective target importance scores, pixels falling into different score ranges are actually subjected to different driving signal intensities during display: pixels in high-importance areas (such as faces and text areas) are displayed at a brightness no lower than the original brightness, pixels in medium-importance areas are displayed at a brightness close to the original brightness, and pixels in low-importance areas (such as backgrounds and skies) are displayed at a brightness lower than the original brightness. This reduces the power consumption of the display panel without significantly affecting the overall image quality. The display driving circuit is used to drive each pixel to display at the brightness indicated by its corresponding target display parameters.

[0133] In this embodiment, steps S303 are followed by steps S304 to S307: Step S304: Divide the display panel into several backlight zones.

[0134] It should be noted that backlight partitioning can be the physical division of the backlight module of the display panel into several independent and controllable areas, and the backlight source in each backlight partition can be driven independently.

[0135] In practical implementation, the display device can divide the backlight module of the display panel into several backlight zones according to a pre-defined partitioning strategy. The partitioning strategy can be to divide the LED array of the backlight module into a matrix along the row and column directions, forming an M-row × N-column backlight partition matrix, where M and N are positive integers. For example, the panel can be divided into 8 rows × 8 columns for 64 backlight zones, or into 16 rows × 16 columns for 256 backlight zones. Each backlight partition corresponds to a rectangular display area on the panel, and the size of each partition can be the same. Alternatively, non-uniform partitioning can be used based on the display panel's aspect ratio or application scenario. For example, in landscape display mode, the display panel can be divided into a 16-row × 8-column partition matrix to adapt to widescreen displays; in portrait mode, the number of rows and columns can be adjusted accordingly. The partitioning strategy can be pre-stored in the display device's memory, and the display device reads the partitioning scheme from memory and performs the partitioning accordingly during power-on initialization.

[0136] In another implementation, the display device can also dynamically determine the number and size of partitions based on the resolution or display mode of the current input screen. For example, when a large area of ​​identical content is detected in the screen, the size of the backlight partition corresponding to that area can be appropriately increased to reduce the number of unnecessary partitions and simplify the calculation. When rich details or fine subjects are detected in the screen, the partition size can be appropriately reduced to improve the accuracy of backlight control. Those skilled in the art can select a suitable partitioning strategy according to actual product requirements.

[0137] Step S305: Calculate the average value of the target importance score of each pixel in each backlight partition to obtain the average importance score of each backlight partition.

[0138] In the specific implementation, after the display device completes the calculation of the target importance score of each pixel, it obtains the position information of all pixels corresponding to each backlight zone, reads the target importance score of each pixel in the backlight zone in turn based on the position information, accumulates the target importance scores of all pixels in the backlight zone, and then divides the sum by the total number of pixels in the backlight zone. The quotient obtained is the average importance score of the backlight zone.

[0139] Step S306: Determine the target backlight driving coefficient corresponding to each backlight partition based on the score interval where each of the average importance scores is located.

[0140] It should be noted that the target backlight driving coefficient can be a parameter that controls the luminous intensity of the backlight source within the backlight zone.

[0141] In the specific implementation, for different score intervals, a second mapping rule between the average importance score and the target backlight drive coefficient is pre-configured, so that different score intervals correspond to different second mapping rules, thereby achieving differentiated backlight drive intensity applied to different importance areas. After obtaining the average importance score of each backlight zone, the display device compares the average importance score of each backlight zone with the preset score intervals to determine the score interval to which the average importance score of each backlight zone belongs. Subsequently, for the score interval to which the average importance score of each backlight zone belongs, the display device uses the corresponding second mapping rule to map the average importance score to the corresponding target backlight drive coefficient. The higher the score interval to which the average importance score of the backlight zone belongs, the larger the mapped target backlight drive coefficient, ensuring that high-importance areas receive sufficient backlight illumination to guarantee image quality, and low-importance areas receive lower backlight power to achieve energy saving.

[0142] In one feasible implementation, the first score interval (e.g., [0, 0.2]), the second score interval (e.g., [0.2, 0.6]), and the third score interval (e.g., [0.6, 1.0]) described above are used as examples of score interval division. When the average importance score of a certain backlight zone falls into the third score interval, it indicates that the display area corresponding to the backlight zone is dominated by high-importance pixels (e.g., containing core visual content such as faces, text, or moving subjects). The display device determines the target backlight drive coefficient of the backlight zone to be 1, that is, drives the backlight source in the backlight zone at full power to ensure that the area receives sufficient backlight illumination to guarantee image quality.

[0143] When the average importance score of a backlight zone falls into the second score interval, it indicates that the display area corresponding to that backlight zone contains a mixture of high-importance pixels and low-importance pixels, or that the overall importance is at a medium level. The display device multiplies the average importance score by a first preset weight, adds the multiplication result to a first preset benchmark value, and then compares the sum with a first preset lower threshold. The larger of the two values ​​is taken as the target backlight driving coefficient for that backlight zone. The target backlight driving coefficient increases linearly with the increase of the average importance score, and its value is not lower than the first preset lower threshold and does not exceed 1. The first preset lower threshold refers to the lowest driving coefficient retained by the backlight zone within the second score interval, used to prevent the loss of image details that should be retained in the medium-importance zone due to excessively low backlight power. The first preset benchmark value refers to the intercept parameter of the linear mapping function within the second score interval, used to determine the initial value of the target backlight driving coefficient when the average importance score is the lower limit of the interval. The first preset weight refers to the change in the target backlight driving coefficient for each unit change in the average importance score within the second score interval. The first preset lower threshold, the first preset benchmark value, and the first preset weight together constitute the second mapping rule corresponding to the second score interval. For example, when the first preset lower threshold is 0.85, the first preset benchmark value is 0.88, and the first preset weight is 0.15, if the average importance score of a certain backlight zone is 0.4, the product result is 0.06, which is added to the benchmark value of 0.88 to get 0.94. This is then compared with the lower threshold of 0.85, and the larger value is taken, resulting in a target backlight driving coefficient of 0.94. If the average importance score is 0.2, the product result is 0.03, which is added to the benchmark value of 0.88 to get 0.91. This is then compared with the lower threshold of 0.85, and the larger value is taken, resulting in a target backlight driving coefficient of 0.91.

[0144] When the average importance score of a backlight zone falls within the first score interval, it indicates that the display area corresponding to that backlight zone is dominated by low-importance pixels (such as static skies, solid-color backgrounds, and other non-interested areas). The display device multiplies the average importance score by a second preset weight, adds the result to a second preset benchmark value, and then compares the result with a second preset lower threshold. The larger of the two values ​​is taken as the target backlight driving coefficient for that backlight zone. This target backlight driving coefficient increases with the increase of the average importance score and is not lower than the second preset lower threshold. The second preset lower threshold is the lowest driving coefficient retained by the backlight zone within the first score interval. Its purpose is to prevent low-importance zones from having obvious dark areas or brightness bands due to the backlight being completely turned off, thus affecting the overall visual experience. The second preset benchmark value is the initial value of the target backlight driving coefficient when the average importance score is determined to be zero within the first score interval. The second preset weight is the slope parameter of the linear mapping function within the first score interval, used to determine the change in the target backlight driving coefficient for each unit change in the average importance score. The second preset lower threshold, the second preset benchmark value, and the second preset weight together constitute the second mapping rule corresponding to the first score interval. Compared with the second score interval, the second preset benchmark value corresponding to the first score interval is lower, and the second preset weight is larger, so as to achieve a more significant change in the backlight driving coefficient with the change of importance score in the low importance region, thereby obtaining more obvious energy-saving benefits in the non-interested area. For example, when the second preset lower threshold is 0.85, the second preset benchmark value is 0.86, and the second preset weight is 0.22, if the average importance score of a certain backlight partition is 0.1, the product result is 0.022, which is added to the benchmark value of 0.86 to get 0.882. This is compared with the lower threshold of 0.85 and the larger value is taken, resulting in a target backlight driving coefficient of 0.882; if the average importance score is 0, the product result is 0, which is added to the benchmark value of 0.86 to get 0.86. This is compared with the lower threshold of 0.85 and the larger value is taken, resulting in a target backlight driving coefficient of 0.86.

[0145] Step S307: Drive the backlight source in the corresponding backlight zone to emit light according to each of the target backlight driving coefficients.

[0146] In its implementation, the display device outputs the target backlight drive coefficient corresponding to each backlight zone to the backlight drive circuit. Based on the received target backlight drive coefficient, the backlight drive circuit generates a pulse width modulation signal with a corresponding duty cycle or an analog current signal with a corresponding amplitude, and applies it to the driving terminal of the backlight source within the corresponding backlight zone. This controls the backlight source in each backlight zone to emit light according to the power indicated by its respective target backlight drive coefficient. The larger the target backlight drive coefficient, the higher the driving current or driving voltage output by the backlight drive circuit to the corresponding backlight zone, and the higher the luminous intensity of the backlight source within that backlight zone; conversely, the smaller the target backlight drive coefficient, the lower the driving current or driving voltage output by the backlight drive circuit to the corresponding backlight zone, and the lower the luminous intensity of the backlight source within that backlight zone. Since the target backlight drive coefficient for each backlight zone is independently determined based on the average importance score of the pixels within that zone, different backlight zones can have different luminous intensities during actual illumination: the backlight source in high-importance zones illuminates at full power, the backlight source in medium-importance zones illuminates at slightly below full power, and the backlight source in low-importance zones illuminates at the minimum power reserved at a lower threshold. This allows for a reduction in overall power consumption of the display panel while ensuring image quality in high-importance areas, by lowering the backlight power in low-importance areas. The backlight drive circuit can be a circuit that controls the luminous intensity of the backlight source within each backlight zone.

[0147] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the method shown in this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0148] This application also provides a display device, please refer to... Figure 5 , Figure 5 This is a schematic diagram of the module structure of the display device of this application. The display device includes: Image input interface 10 is used to acquire input images.

[0149] The control chip 20 is used to determine the target importance score of each pixel in the input image based on the image features of the input image.

[0150] The driving circuit 30 is used to drive each of the display areas of the display panel to display each pixel based on the corresponding target importance score using different target display parameters.

[0151] The display device provided in this application, employing the display method in the above embodiments, can solve the technical problem of decreased overall display quality and negative impact on viewing experience in the prior art. Compared with the prior art, the beneficial effects of the display device provided in this application are the same as those of the display method provided in the above embodiments, and other technical features in the display device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0152] This application provides a display device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the display method in the first embodiment described above.

[0153] The following is for reference. Figure 6 , Figure 6 This is a schematic diagram of the structure of a display device according to an embodiment of this application. The display device in this application embodiment may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 6 The display device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0154] like Figure 6As shown, the display device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the display device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the display device to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show display devices with various systems, it should be understood that it is not required to implement or possess all of the systems shown. More or fewer systems may be implemented alternatively.

[0155] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0156] The display device provided in this application, employing the display method in the above embodiments, can solve the technical problem of decreased overall display quality and negative impact on viewing experience in the prior art. Compared with the prior art, the beneficial effects of the display device provided in this application are the same as those of the display method provided in the above embodiments, and other technical features of the display device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0157] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0158] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0159] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A display method, characterized in that, The display method includes: Obtain the input image; Based on the image features of the input image, determine the target importance score of each pixel in the input image; For each pixel in the display area of ​​the display panel, different target display parameters are used to drive the display area to display based on the corresponding target importance score.

2. The display method as described in claim 1, characterized in that, The image features include semantic features and visual saliency features. The step of determining the target importance score of each pixel in the input image based on the image features of the input image includes: Extract the semantic features and visual saliency features of each pixel in the input image; Assign a first importance score to the corresponding pixel based on the semantic features; A second importance score is assigned to the corresponding pixel based on the visual saliency features of each pixel; The target importance score of each pixel is determined based on the first importance score and the second importance score.

3. The display method as described in claim 2, characterized in that, The step of assigning a first importance score to the corresponding pixel based on the semantic features includes: Determine the current scene information corresponding to the input image; The semantic category to which each pixel belongs is determined based on the semantic features; From multiple preset mapping relationships, a target mapping relationship associated with the current scene information is obtained. The preset mapping relationship includes the mapping relationship between the semantic category and the first importance score. The first importance score corresponding to the same semantic category is different in different preset mapping relationships. Based on the target mapping relationship, each pixel is assigned a corresponding first importance score for its semantic category.

4. The display method as described in claim 2, characterized in that, The step of assigning a second importance score to the corresponding pixel based on the visual saliency features of each pixel includes: Determine the neighboring pixels corresponding to each pixel, wherein the neighboring pixels are pixels within a preset window centered on the corresponding pixel; The difference between the visual salient features of each pixel and the visual salient features of the corresponding neighboring pixels is determined to obtain the feature difference; Each pixel is assigned a second importance score based on the feature differences.

5. The display method as described in claim 2, characterized in that, The step of determining the target importance score of each pixel based on the first importance score and the second importance score includes: Obtain the previous frame image of the input image; Based on the previous frame image and the input image, determine the position change information of each pixel in the input image; The motion characteristics of each pixel are determined based on the position change information; Each pixel is assigned a third importance score based on the aforementioned motion features; The target importance score of each pixel is determined based on the first importance score, the second importance score, and the third importance score.

6. The display method as described in claim 5, characterized in that, The step of determining the target importance score of each pixel based on the first importance score, the second importance score, and the third importance score includes: Select a target weight coefficient combination corresponding to the current scene information from multiple sets of preset weight coefficients. The target weight coefficient combination includes a first weight coefficient corresponding to the first importance score, a second weight coefficient corresponding to the second importance score, and a third weight coefficient corresponding to the third importance score. For each pixel, the first importance score, the second importance score, and the third importance score of the pixel are fused based on the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient to obtain the target importance score of each pixel.

7. The display method according to any one of claims 1 to 6, characterized in that, The step of driving the display of each pixel in the display area of ​​the display panel to display using different target display parameters based on the corresponding target importance score includes: The corresponding brightness adjustment coefficient is determined based on the score range in which the target importance score of each pixel is located; The original display parameters are adjusted according to the brightness adjustment coefficients to obtain the target display parameters corresponding to each pixel; For each pixel in the display area of ​​the display panel, the display area is driven to display according to each target display parameter.

8. The display method as described in claim 7, characterized in that, After the step of driving each of the aforementioned pixels to display in the display area of ​​the display panel according to the aforementioned target display parameters, the method further includes: The display panel is divided into several backlight zones; Calculate the average target importance score of each pixel within each backlight partition to obtain the average importance score of each backlight partition; Based on the score range in which each of the aforementioned average importance scores is located, the target backlight driving coefficient corresponding to each of the aforementioned backlight zones is determined; According to the target backlight driving coefficient, the backlight source in the corresponding backlight zone is driven to emit light.

9. A display device, characterized in that, The display device includes: Image input interface, used to acquire input images; A control chip is used to determine the target importance score of each pixel in the input image based on the image features of the input image; The display driving circuit is used to display the display areas where pixels with different target importance scores are located using different display parameters based on the corresponding target importance scores.

10. A display device, characterized in that, The display device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the display method as described in any one of claims 1 to 7.

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