A two-dimensional edge perception-based RGBG type display panel sub-pixel rendering method and system

Abstract

The application discloses a kind of based on two-dimensional edge perception's RGBG type display panel subpixel rendering method and system, it is related to image display technical field.The method includes: obtaining source image, the format of target image is obtained;According to the arrangement rule of subpixel in target image, determine first conversion process and second conversion process;Boundary pixel of source image is copied outward and expands, the 3x3 pixel region with the center of target pixel to be rendered is carried out luminance calculation, respectively obtains the luminance difference of row direction, column direction;According to the comparison result of row direction, column direction luminance difference and preset luminance difference threshold, multiple edge conditions are divided;Based on multiple edge conditions, using adaptive weighting strategy, execute first conversion process or second conversion process, calculate the rendering value of target image subpixel, complete subpixel rendering.The application effectively improves the image rendering quality of RGBG type display panel and saves circuit overhead.

Description

Technical Field

[0001] This invention relates to the field of image display technology, and specifically to a method and system for rendering sub-pixels of an RGBG type display panel based on two-dimensional edge perception. Background Technology

[0002] With the rapid development of display technology towards higher resolution and higher yield, OLED panels have become the preferred display medium for mid-to-high-end mobile phones, computers, and other electronic products. RGBG type display panels employ a subpixel design with alternating RG / BG rows, such as Pentile or diamond arrangement. To alleviate the display problems caused by the reduction in the number of subpixels, existing technologies mainly use a method of borrowing neighboring subpixels in the row direction for weighted rendering. This attempts to restore the visual effect of the original RGB image without introducing additional buffers and controlling hardware costs.

[0003] However, existing technologies have obvious limitations: on the one hand, edge detection and weighted calculation in the single-row direction cannot take into account both image clarity and false color suppression, and can only deal with false color problems in the row direction. False color phenomena in the column direction are still quite prominent, and direct weighted averaging can easily lead to excessive smoothing of the overall image and blurring of details; on the other hand, the manufacturing processes of display panels from different manufacturers are different, and existing rendering algorithms lack flexibility and adaptability, making it difficult to balance hardware circuit implementation costs while ensuring universality, and thus failing to meet the diverse needs of panel applications. Summary of the Invention

[0004] This invention provides a sub-pixel rendering method and system for RGBG type display panels based on two-dimensional edge perception, aiming to solve the technical problems of poor image rendering quality and high circuit overhead in existing RGBG type display panels.

[0005] In view of the above problems, the present invention provides a method and system for rendering sub-pixels of an RGBG type display panel based on two-dimensional edge awareness.

[0006] In a first aspect, the present invention provides a sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness, comprising: Obtain the source image and the target image format, wherein each pixel of the source image contains RGB sub-pixel information, and each pixel of the target image contains RG sub-pixel information or BG sub-pixel information; Based on the arrangement rules of sub-pixels in the target image, the first conversion process and the second conversion process are determined; The boundary pixels of the source image are copied and extended outward, and the brightness of the 3×3 pixel region centered on the target pixel to be rendered is calculated to obtain the brightness difference in the row direction and the brightness difference in the column direction respectively. Based on the comparison results of the row-direction brightness difference, column-direction brightness difference and preset brightness difference threshold, multiple edge conditions are defined; Based on the multiple edge conditions, an adaptive weighting strategy is adopted to execute the first or second transformation process, calculate the rendering value of the target image sub-pixels, and complete the sub-pixel rendering.

[0007] Secondly, the present invention provides a sub-pixel rendering system for an RGBG type display panel based on two-dimensional edge awareness, comprising: The image acquisition module is used to acquire a source image and acquire the format of a target image, wherein each pixel of the source image contains RGB sub-pixel information, and each pixel of the target image contains RG sub-pixel information or BG sub-pixel information; The conversion process determination module is used to determine the first conversion process and the second conversion process based on the arrangement rules of sub-pixels in the target image; The brightness difference calculation module is used to copy and expand the boundary pixels of the source image outward, and to calculate the brightness of a 3×3 pixel area centered on the target pixel to be rendered, and to obtain the brightness difference in the row direction and the brightness difference in the column direction respectively. The edge condition segmentation module is used to segment multiple edge conditions based on the comparison results of the row-direction brightness difference, column-direction brightness difference and preset brightness difference threshold. The adaptive rendering module is used to perform the first transformation process or the second transformation process based on the multiple edge conditions and an adaptive weighting strategy, calculate the rendering value of the sub-pixels of the target image, and complete the sub-pixel rendering.

[0008] One or more technical solutions provided in this invention have at least the following technical effects or advantages: This invention provides a sub-pixel rendering method and system for RGBG type display panels based on two-dimensional edge perception. By clearly identifying the sub-pixel structural differences between the source image and the target image of the RGBG type panel, the adaptation and conversion process is determined. Through boundary expansion to complete neighborhood data, calculation of bidirectional brightness differences in rows and columns of a 3×3 region, and multi-edge condition division, a targeted conversion is performed in combination with an adaptive weighting strategy for edge adaptation. This overcomes the limitations of existing single-row edge judgment, effectively suppresses bidirectional false color in rows and columns, maintains image clarity, reduces hardware circuit complexity, improves adaptability and versatility to different panel processes, and achieves an organic unity of display quality, versatility, and hardware overhead, thus optimizing the display effect of RGBG type panels. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a flowchart illustrating a sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the first and second conversion processes; Figure 3 A diagram illustrating the extension of pixel copying for the first line, last line, first line, and last line in the rendering process; Figure 4 This is a schematic diagram showing how a 3×3 pixel region is defined, centered on the position of the target pixel in the expanded source image, and including the target pixel and its upper, lower, left, right, and diagonally adjacent pixels. Figure 5 A schematic diagram of the structure of an RGBG type display panel sub-pixel rendering system based on two-dimensional edge awareness provided in an embodiment of the present invention; The components represented by each number in the attached diagram are explained below: Image acquisition module 11, conversion process determination module 12, brightness difference calculation module 13, edge condition division module 14, adaptive rendering module 15. Detailed Implementation

[0011] This invention provides a sub-pixel rendering method and system for RGBG type display panels based on two-dimensional edge perception, which is used to solve the technical problems of poor image rendering quality and high circuit overhead in existing RGBG type display panels.

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0013] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, this invention provides a sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness, the method comprising: S100: Obtain the source image and the format of the target image, wherein each pixel of the source image contains RGB sub-pixel information, and each pixel of the target image contains RG sub-pixel information or BG sub-pixel information.

[0015] In this embodiment of the invention, a source image and a target image format are acquired. Each pixel of the source image contains RGB sub-pixel information, and each pixel of the target image contains either RG or BG sub-pixel information. To achieve high pixel density and high production yield, RGBG type display panels employ an alternating RG and BG row sub-pixel arrangement design, with each target pixel containing only two sub-pixels (RG or BG). However, to ensure color integrity, each pixel of the source image contains all three sub-pixel information (RGB). Therefore, it is necessary to clearly define the source of the original color data and the data carrier for the panel display, and simultaneously define the differences in their sub-pixel structures. This provides the basic data and arrangement basis for the subsequent conversion and rendering of RGB three-color information to RG / BG two-color display, avoiding rendering deviations due to confusion in data format or arrangement rules.

[0016] Step S100 in the method provided in this embodiment of the invention includes: Obtain a source image frame to be displayed and obtain the pixel coordinates of the source image. Each pixel of the source image contains independent red sub-pixel information, green sub-pixel information and blue sub-pixel information to provide complete original color data. The pixel arrangement rules of the RGBG type display panel are determined, wherein the pixels of the display panel are alternately set as RG rows and BG rows in units of rows; Based on the pixel arrangement rules and the source image pixel coordinates, the sub-pixel type corresponding to the source image pixel coordinates in the target image is determined. If it is in row RG in the display panel, then the target image at that coordinate is an RG type pixel containing red and green sub-pixels. If it is in row BG in the display panel, then it is a BG type pixel containing blue and green sub-pixels, thus obtaining the target image corresponding to the RGBG type display panel.

[0017] First, a source image frame to be displayed is acquired, along with its pixel coordinates. Each pixel in the source image contains independent red, green, and blue sub-pixel information. The source image refers to the original image to be displayed on the display panel, such as a photograph or video frame. Each pixel contains independent red (R), green (G), and blue (B) sub-pixel information, representing the concentration of red, green, and blue in that pixel, respectively. The values ​​range from 0 to 255, where 0 indicates no color and 255 indicates the most concentrated color. The combination of these three values ​​constitutes the complete color of the pixel. A complete source image frame is acquired through an image acquisition device, storage medium, or data transmission channel, ensuring that the RGB sub-pixel information of each pixel in the image is complete and readable. For example, in a landscape image, select a pixel in the sky region, labeled j=2, i=3, where j is the vertical row coordinate and i is the horizontal column coordinate. Its RGB subpixel information is: red subpixel information R=50, green subpixel information G=180, and blue subpixel information B=220. This combination of values ​​represents a light blue sky, providing raw color data for subsequent rendering. Then select a pixel in the tree region (j=3, i=3), whose RGB subpixel information is R=30, G=120, B=40, representing dark green leaves.

[0018] Secondly, the pixel arrangement rule of the RGBG type display panel is determined. The pixels of the display panel are alternately arranged as RG rows and BG rows, unit by row. An RGBG type display panel refers to a display panel that uses alternating RG rows and BG rows, meaning that the sub-pixel types of adjacent rows are different. An RG row means that all pixels in a row are RG type pixels, that is, containing only red and green sub-pixels. A BG row means that all pixels in a row are BG type pixels, that is, containing only blue and green sub-pixels. The technical specifications of the target display panel are consulted to clarify the starting row type and alternation rule of its pixel arrangement, and to determine the type of each row in the panel. For example, the arrangement rule of the target mobile phone RGBG type OLED panel is: row 0 is RG row, row 1 is BG row, row 2 is RG row, row 3 is BG row, and so on, that is, even-numbered rows (j=0, 2, 4, ...) are RG rows, and odd-numbered rows (j=1, 3, 5, ...) are BG rows, thus alternating to form the pixel arrangement basis of the entire panel.

[0019] Finally, based on the pixel arrangement rules and the source image pixel coordinates, the sub-pixel type corresponding to the source image pixel coordinates in the target image is determined. If the pixel is in row RG in the display panel, then the corresponding coordinate in the target image is an RG-type pixel containing red and green sub-pixels. If the pixel is in row BG in the display panel, then the corresponding coordinate is a BG-type pixel containing blue and green sub-pixels, thus obtaining the target image corresponding to the RGBG-type display panel. The target image refers to the image carrier of the display data to be filled, which completely corresponds to the pixel arrangement of the RGBG-type display panel. The sub-pixel type of each pixel is determined by the type of its row. An RG-type pixel is a pixel in row RG that contains only red and green sub-pixels and no blue sub-pixels. A BG-type pixel is a pixel in row BG that contains only blue and green sub-pixels and no red sub-pixels. According to the determined arrangement rules, the coordinates (j, i) of each pixel in the target image are matched one by one with the row type to determine whether the pixel is RG or BG type, ultimately forming a target image where the sub-pixel type of each row is uniform and adjacent rows alternate.

[0020] For example, for the light blue pixel at coordinates (j=2, i=3) in the source image: the row at j=2 in the target image is RG type, so the target pixel at this coordinate is an RG type pixel, and only the rendering values ​​of the red and green sub-pixels need to be calculated later; for the dark green pixel at coordinates (j=3, i=3) in the source image: the row at j=3 in the target image is BG type, so the target pixel at this coordinate is a BG type pixel, and only the rendering values ​​of the blue and green sub-pixels need to be calculated later; by traversing all coordinates according to this rule, the target image is finally obtained, and the sub-pixel type of each pixel is clear.

[0021] In this embodiment of the invention, the complete color data of the source image is clearly defined, providing original materials for subsequent rendering and ensuring the foundation for color reproduction; the pixel arrangement rules of the target panel and the sub-pixel types of the target pixels are defined, enabling the subsequent conversion process to accurately match the corresponding pixels and avoid logical errors; the coordinate correspondence between the source image pixels and the target image pixels is established, providing coordinate anchor points for selecting a 3×3 source pixel area centered on the target pixel, ensuring the relevance and accuracy of the rendering calculation.

[0022] S200: Determine the first conversion process and the second conversion process according to the arrangement rules of sub-pixels in the target image.

[0023] In this embodiment of the invention, a first conversion process and a second conversion process are determined based on the arrangement rules of sub-pixels in the target image. For example... Figure 2The diagram shows the first and second conversion processes. Source refers to the source image; Panel refers to the RGBG type display panel; Pixel(j,i) represents the pixel coordinates, where j is the vertical row coordinate and i is the horizontal column coordinate; r, g, and b represent the red, green, and blue sub-pixels in the source image pixels, respectively; R, G, and B represent the red, green, and blue sub-pixels in the display panel pixels, respectively; RGBG_FIRST indicates the arrangement rule for the panel's starting row being the RG row; BGRG_FIRST indicates the arrangement rule for the panel's starting row being the BG row; j=2m,i=2n (m,n∈N), j=2m+1,i=2n+1 (m,n∈N): where m and n are natural numbers used to characterize the coordinate indexing rules of the pixels in the RG and BG rows, clarifying the pixel row and column positions corresponding to different row types.

[0024] S100 has clearly identified the subpixel type of each pixel in the target image. However, the subpixel compositions of the two types of pixels are fundamentally different, requiring targeted matching of different color conversion logics. If a uniform conversion method is used, invalid operations will occur, such as calculating B subpixel data for RG type pixels and R subpixel data for BG type pixels, leading to rendering failure or display anomalies. Therefore, this step needs to divide the target image into two adaptation scenarios based on the subpixel arrangement rules and determine the corresponding conversion process, providing a clear execution basis for subsequent steps.

[0025] Step S200 in the method provided in this embodiment of the invention includes: Based on the alternating arrangement rule of RG and BG rows of the RGBG type display panel, the row type of each pixel in the target image is determined. The row type includes RG row or BG row. Based on the row type of the pixel, the sub-pixel rendering of the target image is divided into two adaptation scenarios, corresponding to the rendering requirements of RG type pixels and BG type pixels respectively. If the row to which the pixel belongs is an RG-type pixel in row RG, then the first conversion process is determined to be the process of converting the red sub-pixel information and green sub-pixel information of the source image into the red sub-pixel display data and green sub-pixel display data of the corresponding RG-type pixel in the target image; If the row to which the pixel belongs is a BG type pixel in the BG row, then the second conversion process is determined to be the process of converting the blue sub-pixel information and green sub-pixel information of the source image into the blue sub-pixel display data and green sub-pixel display data of the corresponding BG type pixel in the target image.

[0026] First, based on the alternating arrangement rule of RG and BG rows in the RGBG type display panel, the row type of each pixel in the target image is determined. The row type includes either RG or BG rows. Row type refers to the attribute of the row in which a pixel in the target image belongs, and is divided into RG and BG rows, determined by the panel arrangement rule specified in S100. The coordinates (j, i) of all pixels in the target image are traversed, and the row type of each pixel is determined one by one according to the panel arrangement rule specified in S100. For example, the pixel at coordinates (j=2, i=3) in the target image: j=2 is an even-numbered row, and according to the panel rule, its row type is determined to be RG row; the pixel at coordinates (j=3, i=3) in the target image: j=3 is an odd-numbered row, and its row type is determined to be BG row; this logic is repeated for all pixels to complete the row type determination.

[0027] Secondly, based on the row type of the pixels, the sub-pixel rendering of the target image is divided into two adaptation scenarios, corresponding to the rendering requirements of RG-type pixels and BG-type pixels, respectively. An adaptation scenario refers to the category of rendering requirements based on the pixel row type. The core is to clarify which sub-pixel information needs to be extracted from the source image for transformation. RG-type pixels require R+G information, and BG-type pixels require B+G information, corresponding to two independent scenarios. Based on the row type determination results, all pixels in the target image are classified into two scenarios: Scenario 1 (RG row - RG-type pixels) and Scenario 2 (BG row - BG-type pixels), ensuring that the pixel rendering requirements are consistent across each scenario. For example, Scenario 1 (RG type pixel scene): contains all pixels with even j coordinates such as (j=2, i=3), (j=2, i=4), and the core requirement is to extract the R+G information of the source image and convert it into display data; Scenario 2 (BG type pixel scene): contains all pixels with odd j coordinates such as (j=3, i=3), (j=3, i=4), and the core requirement is to extract the B+G information of the source image and convert it into display data.

[0028] Furthermore, if the row to which the pixel belongs is an RG-type pixel in row RG, then the first conversion process is determined to be the process of converting the red sub-pixel information and green sub-pixel information of the source image into red sub-pixel display data and green sub-pixel display data of the corresponding RG-type pixel in the target image. For example... Figure 2 As shown, the first conversion process refers to the color conversion logic adapted to Scene 1 (RG type pixel). Specifically, it refers to the process of extracting R and G sub-pixel information from the RGB information of the source image pixels, calculating and generating the R and G display data of the RG type pixel in the target image. For example, for the pixel at coordinates (j=2, i=3) in Scene 1, the first conversion process is determined to be extracting the R=50 and G=180 information of that pixel in the source image. Subsequently, through edge perception and weighted calculation, the R and G display data of that RG type pixel are generated without using the B=220 information of the source image.

[0029] Furthermore, if the pixel belongs to the BG row, then the second conversion process is determined to be the process of converting the blue sub-pixel information and green sub-pixel information of the source image into the blue sub-pixel display data and green sub-pixel display data of the corresponding BG type pixel in the target image. For example... Figure 2 As shown, the second conversion process refers to the color conversion logic adapted to Scene 2 (BG type pixels). Specifically, it refers to the process of extracting B and G sub-pixel information from the RGB information of the source image pixels, calculating and generating the B and G display data of the BG type pixels in the target image. For example, for the pixel at coordinates (j=3, i=3) in Scene 2, the second conversion process is determined to be extracting the B=40 and G=120 information of that pixel in the source image. Subsequently, through edge perception and weighted calculation, the B display data and G display data of the BG type pixel are generated, without needing the R=30 information of the source image.

[0030] S300: The boundary pixels of the source image are copied and extended outward, and the brightness of the 3×3 pixel region centered on the target pixel to be rendered is calculated to obtain the brightness difference in the row direction and the brightness difference in the column direction respectively.

[0031] In this embodiment of the invention, the boundary pixels of the source image are copied and expanded outwards. Brightness calculations are performed on a 3×3 pixel region centered on the target pixel to be rendered, obtaining brightness differences in both the row and column directions. S200 has determined two conversion processes. Two-dimensional edge perception relies on the neighborhood information of the pixel to be rendered to determine edge characteristics; therefore, a 3×3 region containing the target pixel and eight neighboring pixels needs to be constructed. However, the boundary pixels of the first, last, first, and last rows of the source image lack some neighborhoods, and direct calculation will result in data loss. Simultaneously, RGB color information cannot directly reflect edges and needs to be converted to a uniform brightness value. Then, edge changes are quantified through row and column brightness differences, providing data for edge segmentation conditions in S400. This is the key difference from existing single-row judgment.

[0032] Step S300 in the method provided in this embodiment of the invention includes: The step of copying and extending the boundary pixels of the source image outward includes: If the target pixel to be rendered is located at the first row, last row, first row, or last row in the source image, it is necessary to expand outward by copying the pixel information of the corresponding boundary. The first row of pixels is copied upwards, the last row of pixels is copied downwards, the first row of pixels is copied to the left, and the last row of pixels is copied to the right, thus completing the neighboring pixel data required for the 3×3 pixel area.

[0033] First, such as Figure 3As shown, if the target pixel to be rendered is located at the beginning, end, beginning, or end of a row in the source image, it needs to be expanded outward by copying the pixel information of the corresponding boundary. Boundary pixels refer to the pixels at the beginning, end, beginning, or end of a row in the source image, lacking some neighborhood. The target pixel to be rendered is the pixel whose rendering value needs to be calculated, and its coordinates correspond one-to-one with those in the source image. Based on the source image coordinates (j, i) corresponding to the pixel to be rendered, it is determined whether it is at the beginning, end, beginning, or end of a row, and the pixels that need to be expanded are marked. For example, the pixel to be rendered (j=2, i=3) is not at the beginning / end / beginning / end of a row and does not need to be expanded; the pixel to be rendered (j=0, i=1), j=0 is at the beginning of a row, belongs to the boundary pixel, and needs to be expanded.

[0034] Secondly, the first row of pixels is copied upwards, the last row of pixels downwards, the first row of pixels is copied to the left, and the last row of pixels is copied to the right, completing the necessary neighboring pixel data for the 3×3 pixel area. Copying and expanding involves copying the data of the boundary pixels themselves to the missing neighboring positions, completing the necessary data for the 3×3 area. The first row of pixels is copied upwards, the last row downwards, the first row to the left, and the last row to the right, ensuring that the data in the missing neighboring areas is consistent with the boundary pixels after expansion. For example, as shown... Figure 3 As shown, the boundary pixel Pixel(0,0) is the first pixel of the first row and the first pixel of each row in the source image. The neighborhood data of the 3×3 region needs to be completed: following the rule of copying the first row pixel upwards and the first pixel of each row to the left, the sub-pixel information of Pixel(0,0) is copied to the position above it (row index -1, column index 0) to complete the missing upper neighborhood of the first row, and to the position to its left (row index 0, column index -1) to complete the missing left neighborhood of the first row. Simultaneously, the information of Pixel(0,0) is also copied to its upper left diagonal neighborhood (row index -1, column index -1), thus completing the required neighborhood data for the 3×3 region of this pixel. The remaining boundary pixels are expanded using the same logic.

[0035] Specifically, brightness calculations are performed on a 3×3 pixel region centered on the target pixel to be rendered, obtaining the brightness differences in the row direction and the column direction, including: Centered on the position of the target pixel to be rendered in the expanded source image, a 3×3 pixel region is defined, which includes the target pixel and its upper, lower, left, right, and diagonally adjacent pixels. For each pixel in the 3×3 pixel region, the red sub-pixel information, green sub-pixel information, and blue sub-pixel information of the pixel are weighted and summed according to the preset red channel coefficient, green channel coefficient, and blue channel coefficient to obtain the brightness value corresponding to each pixel; Divide the 3×3 pixel area into three rows of pixels horizontally: top, middle and bottom. Calculate the difference between the maximum and minimum values ​​of the pixel brightness values ​​in each group to obtain three groups of horizontal brightness differences. Take the horizontal brightness difference corresponding to the middle row as the row direction brightness difference. The three sets of lateral brightness differences are analyzed, and the difference between the maximum and minimum values ​​among the three sets of lateral brightness differences is calculated. This difference is taken as the brightness difference in the column direction.

[0036] First, such as Figure 4 As shown, a 3×3 pixel region is defined centered on the position of the target pixel in the expanded source image, encompassing the target pixel and its upper, lower, left, right, and diagonally adjacent pixels. The 3×3 pixel region is a set of pixels in a 3x3 grid, centered on the pixel in the expanded source image, including its upper (j-1, i), lower (j+1, i), left (j, i-1), right (j, i+1), and eight diagonally adjacent pixels. Centered on the pixel coordinates (j, i), nine pixels within the coordinate range [j-1, j+1] × [i-1, i+1] are selected to form the 3×3 region. For example, a 3×3 region for a non-boundary pixel j=2, i=3 contains nine pixels j=1~3 and i=2~4; after expansion, a region for a boundary pixel j=0, i=1 contains nine pixels j=-1~1 and i=0~2.

[0037] Secondly, for each pixel in the 3×3 pixel area, the red, green, and blue sub-pixel information of that pixel are weighted and summed according to preset red, green, and blue channel coefficients to obtain the brightness value corresponding to each pixel. The brightness value is a grayscale value converted from RGB information through weighted summation, and the formula is: Brightness value = Red channel coefficient × R + Green channel coefficient × G + Blue channel coefficient × B, uniformly quantifying the degree of brightness. The channel coefficients are determined based on the characteristics of human vision and industry-wide standards, with the aim of ensuring that the calculated brightness value closely matches the actual perception of brightness and darkness by the human eye, and ensuring that edge judgment conforms to visual logic. For the 9 pixels in the 3×3 area, the brightness value calculation formula is applied to each pixel, and the result is rounded down to the nearest integer to obtain the brightness value of each pixel.

[0038] For example, according to industry standards, the red channel coefficient is set to 0.299, the green channel coefficient to 0.587, and the blue channel coefficient to 0.114. For each pixel in a 3×3 area, the brightness value is calculated by substituting the preset channel coefficients and keeping the integer value. Taking the 3×3 area corresponding to non-boundary pixels j=2 and i=3 as an example, the brightness value of the center pixel is calculated as follows: The brightness value of the center pixel (j=2, i=3) = 0.299×50 + 0.587×180 + 0.114×220 ≈ 146. The brightness values ​​of the 9 pixels are calculated as follows: The brightness values ​​of the three pixels from left to right in the top row (j=1) are 132, 145, and 154 respectively; the brightness values ​​of the three pixels from left to right in the middle row (j=2, including the center pixel) are 141, 146 (center pixel), and 150 respectively; the brightness values ​​of the three pixels from left to right in the bottom row (j=3, leaf area) are 78, 85, and 69 respectively.

[0039] Furthermore, the 3×3 pixel region is horizontally divided into three rows of pixels: top, middle, and bottom. The difference between the maximum and minimum brightness values ​​in each group is calculated, resulting in three sets of horizontal brightness differences. The horizontal brightness difference corresponding to the middle row is taken as the row-direction brightness difference. The horizontal brightness difference refers to the difference between the maximum and minimum brightness values ​​of each row. The row-direction brightness difference is the horizontal brightness difference of the middle row. First, the 3×3 region is divided into three rows: top, middle, and bottom. The horizontal brightness difference is calculated for each row, and the difference in the middle row is taken as the row-direction brightness difference. For example, the brightness values ​​of the top row pixel group are 132, 145, and 154, the brightness values ​​of the middle row pixel group are 141, 146, and 150, and the brightness values ​​of the bottom row pixel group are 78, 85, and 69. Calculate the horizontal brightness difference for each group: Top row pixel group: maximum value 154 - minimum value 132 = 22; Middle row pixel group: maximum value 150 - minimum value 141 = 9; Bottom row pixel group: maximum value 85 - minimum value 69 = 16. Take the horizontal brightness difference of 9 corresponding to the middle row as the row-direction brightness difference.

[0040] Finally, the three sets of lateral brightness differences are analyzed, and the difference between the maximum and minimum values ​​among the three sets of lateral brightness differences is calculated. This difference is taken as the column-direction brightness difference. The column-direction brightness difference is the maximum value minus the minimum value of the three sets of lateral differences. For example, if the three sets of lateral brightness differences are 22, 9, and 16, with a maximum value of 22 and a minimum value of 9, then the column-direction brightness difference = 22 - 9 = 13.

[0041] In this embodiment of the invention, the neighborhood data is supplemented by boundary expansion to avoid edge judgment distortion caused by missing data in boundary pixels; the interference of color channel differences is eliminated by converting RGB to brightness values, providing a unified quantization dimension for edge judgment; the two-dimensional edge feature quantization is realized by the bidirectional brightness difference of rows and columns, breaking through the limitations of the existing single-row judgment and providing accurate data support for the edge division conditions of S400.

[0042] S400: Based on the comparison results of the row-direction brightness difference, column-direction brightness difference and preset brightness difference threshold, multiple edge conditions are defined.

[0043] In this embodiment of the invention, multiple edge conditions are defined based on the comparison results of the row-direction brightness difference, column-direction brightness difference, and preset brightness difference thresholds. S300 has already acquired the brightness differences in both row and column directions, quantifying the changes in edge brightness in the horizontal and vertical directions of the image. However, different combinations of differences correspond to different types of edge scenes. For example, a large difference in both rows and columns may indicate an intersecting edge, while a large difference in only rows may indicate a horizontal edge. Existing technologies lack precise differentiation of multiple edge scenes, resulting in a single rendering strategy that struggles to balance pseudo-color suppression and sharpness at different edges. This step, by configuring preset thresholds, performs dual judgment on row and column brightness differences, defining four types of edge conditions. This allows subsequent rendering strategies to accurately adapt to different edge features, providing a clear basis for S500 to specifically calculate rendering values.

[0044] Step S400 in the method provided in this embodiment of the invention includes: Configure a preset brightness difference threshold for judging edge features, wherein the preset brightness difference threshold is greater than 0 and less than 255; The row-direction brightness difference is compared with the preset brightness difference threshold to determine whether the row-direction brightness difference is greater than the threshold. The column-direction brightness difference is compared with the preset brightness difference threshold to determine whether the column-direction brightness difference is greater than the threshold. Based on the combination of the two comparison results, four marginal conditions are obtained.

[0045] First, a preset brightness difference threshold is configured to determine edge features. This threshold is greater than 0 and less than 255. The preset brightness difference threshold is a manually configured critical value between 0 and 255, used to determine whether the brightness difference is significant. A value greater than the threshold indicates prominent edge features and drastic changes in brightness in that direction, while a value less than or equal to the threshold indicates a smooth transition and no obvious edge. The threshold is flexibly configured based on the display panel technology and image type to ensure effective differentiation between obvious edges and smooth areas. For example, in scenes depicting sky and leaves, a threshold of 10 avoids misjudging smooth areas as edges due to an excessively low threshold, and also prevents overlooking obvious edges due to an excessively high threshold, thus adapting to the edge features of most natural images.

[0046] Next, the row-direction brightness difference is compared with the preset brightness difference threshold to determine whether the row-direction brightness difference is greater than the threshold. The row-direction brightness difference comparison is used to determine whether the change in brightness in the horizontal direction is significant, and the result includes two possibilities: greater than the threshold or less than or equal to the threshold. The row-direction brightness difference obtained in S300 is directly compared with the preset brightness difference threshold, and the comparison result is recorded. For example, if the row-direction brightness difference = 9 and the preset brightness difference threshold = 10, the comparison result is: row-direction brightness difference ≤ preset brightness difference threshold, indicating that the horizontal transition between light and dark is smooth, which is consistent with the characteristic of no obvious edge in the horizontal direction of the sky area.

[0047] Further, the column-direction brightness difference is compared with the preset brightness difference threshold to determine whether the column-direction brightness difference is greater than the threshold. The column-direction brightness difference comparison is used to determine whether the change in brightness in the vertical direction is significant, and the result includes two possibilities: greater than the threshold or less than or equal to the threshold. The column-direction brightness difference obtained in S300 is directly compared with the preset brightness difference threshold, and the comparison result is recorded. For example, if the column-direction brightness difference = 13 and the preset brightness difference threshold = 10, the comparison result is: column-direction brightness difference > preset brightness difference threshold, indicating that the change in brightness in the vertical direction is significant, which is consistent with the characteristic of the vertical edge protruding at the junction of the sky and the leaves.

[0048] Finally, based on the combination of the two comparison results, four marginal conditions were identified.

[0049] Based on the combination of the two comparison results, four marginal conditions are identified, including: The first edge condition is that the brightness difference in the row direction is greater than the preset brightness difference threshold, and the brightness difference in the column direction is greater than the preset brightness difference threshold. The second edge condition is that the brightness difference in the row direction is greater than the preset brightness difference threshold, and the brightness difference in the column direction is less than or equal to the preset brightness difference threshold. The third edge condition is that the brightness difference in the row direction is less than or equal to the preset brightness difference threshold, and the brightness difference in the column direction is greater than the preset brightness difference threshold. The fourth edge condition is that the brightness difference in the row direction is less than or equal to the preset brightness difference threshold, and the brightness difference in the column direction is less than or equal to the preset brightness difference threshold.

[0050] First, the first edge condition is that the brightness difference in the row direction is greater than a preset brightness difference threshold, and the brightness difference in the column direction is also greater than a preset brightness difference threshold. The first edge condition refers to drastic changes in brightness both horizontally and vertically, corresponding to intersecting edge scenes, such as the intersection of lines in an image or the boundary of an object's edge. When both the row-direction brightness difference and column-direction brightness difference thresholds are met, it is determined to be the first edge condition. For example, if a pixel's row difference = 15 > 10 and column difference = 14 > 10, both conditions are met, and it belongs to the first edge condition, corresponding to an edge scene where tree branches intersect.

[0051] Secondly, the second edge condition is that the brightness difference in the row direction is greater than a preset brightness difference threshold, and the brightness difference in the column direction is less than or equal to a preset brightness difference threshold. The second edge condition refers to a situation where only the horizontal brightness changes drastically, while the vertical transition is gradual, corresponding to horizontal edge scenes such as the horizon or the top and bottom borders of text. When the brightness difference in the row direction is greater than the preset brightness difference threshold and the brightness difference in the column direction is less than or equal to the preset brightness difference threshold, it is determined to meet the second edge condition. For example, if a pixel's row difference = 12 > 10 and column difference = 8 ≤ 10, it meets the condition and belongs to the second edge condition, corresponding to the horizontal boundary between the sky and distant mountains.

[0052] Secondly, the third edge condition is that the row-direction brightness difference is less than or equal to a preset brightness difference threshold, and the column-direction brightness difference is greater than a preset brightness difference threshold. The third edge condition refers to a situation where only the vertical brightness change is drastic, while the horizontal transition is smooth, corresponding to vertical edge scenes, such as the left and right outlines of an object, or the vertical boundary between the sky and leaves. When the row-direction brightness difference is less than or equal to the preset brightness difference threshold, and the column-direction brightness difference is greater than the preset brightness difference threshold, it is determined to be a third edge condition. For example, in this case, the row-direction brightness difference = 9 ≤ 10 and the column-direction brightness difference = 13 > 10, which fully meets the condition and belongs to the third edge condition, corresponding to the vertical boundary between the light blue sky (smooth horizontal transition) and the dark green leaves (abrupt vertical transition).

[0053] Finally, the fourth edge condition is that the brightness difference in the row direction is less than or equal to a preset brightness difference threshold, and the brightness difference in the column direction is also less than or equal to a preset brightness difference threshold. The fourth edge condition refers to smooth changes in brightness both horizontally and vertically, with no obvious edges, corresponding to solid color / gradient areas, such as a pure blue sky or a uniform skin tone area. When both the row-direction brightness difference and the column-direction brightness difference are true, it is determined to meet the fourth edge condition. For example, if a pixel's row difference = 6 ≤ 10 and column difference = 4 ≤ 10, it meets the condition and belongs to the fourth edge condition, corresponding to a cloudless, solid-color sky area.

[0054] In this embodiment of the invention, by configuring a preset brightness difference threshold adjustable from 0 to 255, the brightness differences in the row and column directions acquired by S300 are compared twice, accurately classifying four non-overlapping edge conditions: intersecting edges, horizontal edges, vertical edges, and no edges, comprehensively covering various brightness and darkness variations in images. This step breaks through the limitation of existing technologies that only judge edges in a single row, achieving accurate classification of two-dimensional edge features. It avoids the drawback of a single rendering strategy being unable to adapt to different edge scenarios, and adapts to different manufacturers' panel processes and various image types through flexible threshold configuration. This provides a clear and accurate basis for S500 to adapt differentiated weighting strategies for different edge scenarios, while also meeting the design goals of strong versatility and low hardware overhead of this solution, laying the foundation for subsequent precise balance between pseudo-color suppression and image clarity.

[0055] S500: Based on the multiple edge conditions, an adaptive weighting strategy is adopted to execute the first conversion process or the second conversion process, calculate the rendering value of the target image sub-pixels, and complete the sub-pixel rendering.

[0056] In this embodiment of the invention, based on the multiple edge conditions, an adaptive weighting strategy is adopted to execute the first or second conversion process, calculate the rendering value of the target image sub-pixels, and complete the sub-pixel rendering. S400 has accurately divided four types of edge conditions. Different edge scenes have different rendering requirements. For example, vertical edges need to strengthen vertical pixel continuity to suppress column-direction false color while retaining horizontal clarity; edgeless areas need to balance neighborhood weights to avoid excessive blurring. Existing technologies use fixed weighting coefficients, which cannot adapt to multiple edge scenes, making it difficult to balance false color suppression and clarity. This step achieves an adaptive weighting strategy through precise mapping between edge conditions and weighting coefficients. Combined with the conversion process determined in S200, RGB sub-pixel information is extracted specifically to calculate the rendering value, ensuring adaptability to different edge scenes while conforming to low hardware overhead design, ultimately completing a closed loop from two-dimensional edge perception to adaptive rendering.

[0057] Step S500 in the method provided in this embodiment of the invention includes: Among them, based on the multiple edge conditions, an adaptive weighting strategy is adopted, including: An adaptive weighted coefficient lookup table is pre-defined. The table is indexed by the four edge conditions obtained from the division. Each edge condition corresponds to a unique set of weighted coefficients. Each set of weighted coefficients contains five coefficients, which correspond to the left neighboring pixel, itself, right neighboring pixel, upper neighboring pixel, and lower neighboring pixel of the target pixel to be rendered. The sum of each set of coefficients is 1. Each set of coefficients is pre-defined with an adaptive value according to the rendering requirements of different edge scenes. Using the defined edge condition as the query keyword, the preset adaptive weighted coefficient lookup table is retrieved, and a set of adaptive weighted coefficients corresponding to the edge condition is extracted. The adaptive weighted coefficient set is used as the adaptation coefficient for the current pixel rendering calculation.

[0058] First, an adaptive weighted coefficient lookup table is pre-defined. This table uses the four edge conditions as indexes, with each edge condition corresponding to a unique set of weighted coefficients. Each set of weighted coefficients contains five coefficients, corresponding to the left neighbor, itself, right neighbor, top neighbor, and bottom neighbor pixels of the target pixel to be rendered. The sum of each set of coefficients is 1. Each set of coefficients has pre-defined adaptive values ​​based on the rendering requirements of different edge scenes. The adaptive weighted coefficient lookup table is a pre-defined table indexed by the four edge conditions. Each condition corresponds to a unique set of weighted coefficients, with each set containing five weighted coefficients, corresponding to the left neighbor, itself, right neighbor, top neighbor, and bottom neighbor pixels. The sum of each set of coefficients is 1, ensuring that the rendered value after weighted calculation is within a reasonable range of 0-255. The coefficient values ​​are adapted to the edge scene requirements, with higher weights for edge directions and lower weights for non-edge directions.

[0059] For example, based on the rendering requirements of different edge scenes, four sets of coefficients are preset. The table can be stored in a hardware register and retrieved directly without real-time calculation: First edge condition (intersecting edge): left 0.1, itself 0.4, right 0.1, top 0.2, bottom 0.2 (balance row and column weights); Second edge condition (horizontal edge): left 0.2, itself 0.4, right 0.2, top 0.1, bottom 0.1 (strengthen horizontal weights); Third edge condition (vertical edge): left 0.1, itself 0.5, right 0.1, top 0.2, bottom 0.1 (strengthen itself and vertical weights, suppress horizontal interference); Fourth edge condition (no edge): left 0.2, itself 0.2, right 0.2, top 0.2, bottom 0.2 (balance all neighborhood weights).

[0060] Secondly, using the defined edge conditions as query keywords, the preset adaptive weighted coefficient lookup table is retrieved to extract a set of adaptive weighted coefficients corresponding to the edge condition. For example, in this case, the pixel to be rendered (j=2, i=3) belongs to the third edge condition. By retrieving the preset adaptive weighted coefficient lookup table, a set of adaptive weighted coefficients [left 0.1, itself 0.5, right 0.1, top 0.2, bottom 0.1] is obtained. This not only highlights the core role of the central pixel, but also strengthens the vertical coherence through the weights of the upper and lower neighbors, which meets the false color suppression requirement of the vertical intersection of the sky and leaves.

[0061] Finally, the adaptive weighted coefficient set is used as the adaptation coefficient for the current pixel rendering calculation. The adaptation coefficient refers to the weighted coefficient set that uniquely matches the edge conditions of the current pixel and is a core parameter for subsequent rendering calculations. Using the determined edge conditions as keywords, a preset lookup table is searched to directly extract the corresponding coefficient set. For example, the adaptation coefficients for the current pixel rendering calculation are: left = 0.1, itself = 0.5, right = 0.1, top = 0.2, bottom = 0.1. The sum of these coefficients is 0.1 + 0.5 + 0.1 + 0.2 + 0.1 = 1, which meets the calculation requirements.

[0062] The process of executing the first or second conversion process, calculating the rendering value of the target image sub-pixels, and completing the sub-pixel rendering includes: Based on the row type of the target pixel to be rendered in the target image, determine the conversion process to be performed. If the row is RG, perform the first conversion process; if the row is BG, perform the second conversion process. If the first conversion process is performed, the adaptation coefficients are used to perform a weighted summation of the red sub-pixel information and green sub-pixel information of the neighboring source pixels in the 3×3 pixel area to obtain the red sub-pixel rendering value and green sub-pixel rendering value of the target pixel. If the second conversion process is performed, the adaptation coefficients are used to perform weighted summation on the blue sub-pixel information and green sub-pixel information of the neighboring source pixels in the 3×3 pixel area to obtain the blue sub-pixel rendering value and green sub-pixel rendering value of the target pixel. The calculated subpixel rendering value is assigned to the corresponding pixel to be rendered in the target image to complete the subpixel rendering of that pixel.

[0063] First, based on the row type of the target pixel in the target image, the required transformation process is determined. If the row is RG, the first transformation process is executed; if the row is BG, the second transformation process is executed. According to the pixel row type determined in S100, the corresponding transformation process in S200 is called. For RG rows, the first transformation process (processing R+G sub-pixels) is executed; for BG rows, the second transformation process (processing B+G sub-pixels) is executed. For example, if the pixel to be rendered (j=2, i=3) is in the RG row, the first transformation process is executed, requiring the calculation of the rendering values ​​for the R and G sub-pixels. If the pixel to be rendered (j=3, i=3) is in the BG row with a fourth edge condition, the second transformation process is executed, requiring the calculation of the rendering values ​​for the B and G sub-pixels.

[0064] Secondly, if the first conversion process is performed, the adaptation coefficients are used to weight and sum the red and green sub-pixel information of the neighboring source pixels within the 3×3 pixel region to obtain the red and green sub-pixel rendering values ​​of the target pixel. The weighted calculation in the first conversion process refers to, for RG-type pixels, using the adaptation coefficients to weight and sum the R and G sub-pixel information of the left adjacent, itself, right adjacent, top adjacent, and bottom adjacent pixels within the 3×3 region to obtain the final display data. The adaptation coefficients are multiplied one by one by the R sub-pixel information of the corresponding pixel, and the sum is used to obtain the R rendering value; similarly, the G rendering value is calculated, and the result is rounded to the nearest integer. For example, the adaptation coefficients of the pixel to be rendered (j=2, i=3) [left 0.1, itself 0.5, right 0.1, top 0.2, bottom 0.1]: Key R sub-pixel data for a 3×3 region: Left neighbor (j=2, i=2) R=48, itself (j=2, i=3) R=50, right neighbor (j=2, i=4) R=52, top neighbor (j=1, i=3) R=55, bottom neighbor (j=3, i=3) R=30; R sub-pixel rendering value = 48×0.1 + 50×0.5 + 52×0 1 + 55 × 0.2 + 30 × 0.1 = 49; Key G sub-pixel data for the 3×3 region: Left neighbor (j=2, i=2) G=175, itself (j=2, i=3) G=180, Right neighbor (j=2, i=4) G=185, Top neighbor (j=1, i=3) G=185, Bottom neighbor (j=3, i=3) G=120; G sub-pixel rendering value = 175 × 0.1 + 180 × 0.5 + 185 × 0.1 + 185 × 0.2 + 120 × 0.1 = 175.

[0065] Next, if the second conversion process is executed, the adaptation coefficients are used to perform a weighted summation of the blue and green sub-pixel information of the neighboring source pixels within the 3×3 pixel region to obtain the blue and green sub-pixel rendering values ​​of the target pixel. The weighted calculation in the second conversion process refers to, for BG type pixels, using the adaptation coefficients to perform a weighted summation of the B and G sub-pixel information of the corresponding pixels within the 3×3 region to obtain the final display data. The logic is consistent with the first conversion process, only the calculation object is replaced with B sub-pixel information; the calculation logic for G sub-pixels remains the same. For example, the edge condition of the pixel to be rendered (j=3, i=3) is the fourth edge condition, with adaptation coefficients [left 0.2, itself 0.2, right 0.2, top 0.2, bottom 0.2]: Key B sub-pixel data for the 3×3 region: Left neighbor (j=3, i=2) B=45, itself (j=3, i=3) B=40, right neighbor (j=3, i=4) B=35, top neighbor (j=2, i=3) B=220, bottom neighbor (j=4, i=3) B=38; B sub-pixel rendering value = 45×0.2 + 40×0.2 + 35×0.2 .2 + 220 × 0.2 + 38 × 0.2 = 75.6 ≈ 76; Key G sub-pixel data for the 3×3 region: Left neighbor (j=3, i=2) G=125, itself (j=3, i=3) G=120, Right neighbor (j=3, i=4) G=115, Top neighbor (j=2, i=3) G=180, Bottom neighbor (j=4, i=3) G=118; G sub-pixel rendering value = 125 × 0.2 + 120 × 0.2 + 115 × 0.2 + 180 × 0.2 + 118 × 0.2 = 131.6 ≈ 132.

[0066] Finally, the calculated sub-pixel rendering value is assigned to the corresponding pixel to be rendered in the target image, completing the sub-pixel rendering of that pixel. Assigning the rendering value means writing the calculated sub-pixel rendering value into the pixel at the corresponding coordinates in the target image, completing the display data filling for a single pixel. Based on the coordinate mapping between the source and target images, the R / G or B / G rendering values ​​are assigned to the corresponding sub-pixel channels of the target pixel, completing the rendering of a single pixel. For example, for the pixel to be rendered (j=2, i=3), R=49 and G=175 are assigned to the RG-type pixel in the target image (j=2, i=3), locking the display data of that pixel and completing the rendering; for the pixel to be rendered (j=3, i=3), B=76 and G=132 are assigned to the BG-type pixel in the target image (j=3, i=3), locking the display data of that pixel and completing the rendering; following the above logic, all pixels in the target image are traversed, calculated and assigned values ​​one by one, ultimately completing the sub-pixel rendering of the entire frame.

[0067] In this embodiment of the invention, the adaptive weighting coefficients are precisely matched with edge conditions, and the weight allocation is optimized for different scenarios such as vertical edges and horizontal edges. This not only suppresses bidirectional pseudo-color in rows and columns, but also avoids blurring caused by excessive image smoothing, achieving a balance between pseudo-color suppression and clarity. By retrieving a preset adaptive weighting coefficient lookup table, the retrieval and call are efficient and do not require complex real-time calculations. Combined with the conversion logic that only processes target sub-pixel information, it fits the low-overhead design of the two-row hardware cache, reducing the complexity of circuit implementation. The coefficient group can be flexibly adjusted according to different manufacturers' panel processes and image types, and the conversion process is deeply bound to the pixel row type, ensuring that the solution has strong versatility and is compatible with various RGBG type display panels. It completes the accurate conversion and rendering of source image RGB information and target image RG / BG information, and realizes the core logic of two-dimensional edge perception, adaptive weighting, and accurate display in a closed loop, improving the rendering quality of sub-pixels of RGBG type panels.

[0068] Through the specific implementation methods described above, the embodiments of the present invention achieve the following technical effects: This invention provides a sub-pixel rendering method and system for RGBG display panels based on two-dimensional edge perception. It first identifies the sub-pixel structural differences between the source image and the target image of the RGBG display panel. Then, it performs boundary pixel copying and expansion to complete the neighborhood data, calculates the bidirectional brightness difference between rows and columns in a 3×3 region, and accurately divides the image into four types of edge conditions. Finally, it adapts a specific weighting coefficient based on the edge conditions and executes a targeted conversion process. This complete logic overcomes the limitation of existing technologies that only judge edges in a single row. It effectively suppresses the pseudo-color phenomenon in both rows and columns of RGBG panels and avoids the loss of clarity caused by excessive image smoothing. Furthermore, with adjustable weighting coefficients and simplified hardware circuit design, it reduces production costs and circuit complexity, improves the adaptability and universality of the solution to different manufacturers' panel processes, and ultimately achieves an organic unity of display quality, universality, and hardware overhead, optimizing the image display effect of RGBG display panels.

[0069] Example 2, as Figure 5 As shown, the present invention provides a sub-pixel rendering system for an RGBG type display panel based on two-dimensional edge awareness, the system comprising: Image acquisition module 11 is used to acquire a source image and acquire the format of a target image, wherein each pixel of the source image contains RGB sub-pixel information, and each pixel of the target image contains RG sub-pixel information or BG sub-pixel information; The conversion process determination module 12 is used to determine the first conversion process and the second conversion process according to the arrangement rules of sub-pixels in the target image; The brightness difference calculation module 13 is used to copy and expand the boundary pixels of the source image outward, perform brightness calculation on a 3×3 pixel area centered on the target pixel to be rendered, and obtain the brightness difference in the row direction and the brightness difference in the column direction respectively. The edge condition segmentation module 14 is used to segment multiple edge conditions based on the comparison results of the row direction brightness difference, column direction brightness difference and preset brightness difference threshold. The adaptive rendering module 15 is used to perform the first transformation process or the second transformation process based on the multiple edge conditions and an adaptive weighting strategy to calculate the rendering value of the sub-pixels of the target image and complete the sub-pixel rendering.

[0070] In one embodiment, the image acquisition module 11 is further configured to: Obtain a source image frame to be displayed, and obtain the pixel coordinates of the source image. Each pixel of the source image contains independent red sub-pixel information, green sub-pixel information, and blue sub-pixel information. The pixel arrangement rules of the RGBG type display panel are determined, wherein the pixels of the display panel are alternately set as RG rows and BG rows in units of rows; Based on the pixel arrangement rules and the source image pixel coordinates, the sub-pixel type corresponding to the source image pixel coordinates in the target image is determined. If it is in row RG in the display panel, then the target image at that coordinate is an RG type pixel containing red and green sub-pixels. If it is in row BG in the display panel, then it is a BG type pixel containing blue and green sub-pixels, thus obtaining the target image corresponding to the RGBG type display panel.

[0071] In one embodiment, the conversion process determination module 12 is further configured to: Based on the alternating arrangement rule of RG and BG rows of the RGBG type display panel, the row type of each pixel in the target image is determined. The row type includes RG row or BG row. Based on the row type of the pixel, the sub-pixel rendering of the target image is divided into two adaptation scenarios, corresponding to the rendering requirements of RG type pixels and BG type pixels respectively. If the row to which the pixel belongs is an RG-type pixel in row RG, then the first conversion process is determined to be the process of converting the red sub-pixel information and green sub-pixel information of the source image into the red sub-pixel display data and green sub-pixel display data of the corresponding RG-type pixel in the target image; If the row to which the pixel belongs is a BG type pixel in the BG row, then the second conversion process is determined to be the process of converting the blue sub-pixel information and green sub-pixel information of the source image into the blue sub-pixel display data and green sub-pixel display data of the corresponding BG type pixel in the target image.

[0072] In one embodiment, the brightness difference calculation module 13 is further configured to: The step of copying and extending the boundary pixels of the source image outward includes: If the target pixel to be rendered is located at the first row, last row, first row, or last row in the source image, it is necessary to expand outward by copying the pixel information of the corresponding boundary. The first row of pixels is copied upwards, the last row of pixels is copied downwards, the first row of pixels is copied to the left, and the last row of pixels is copied to the right, thus completing the neighboring pixel data required for the 3×3 pixel area.

[0073] Specifically, brightness calculations are performed on a 3×3 pixel region centered on the target pixel to be rendered, obtaining the brightness differences in the row direction and the column direction, including: Centered on the position of the target pixel to be rendered in the expanded source image, a 3×3 pixel region is defined, which includes the target pixel and its upper, lower, left, right, and diagonally adjacent pixels. For each pixel in the 3×3 pixel region, the red sub-pixel information, green sub-pixel information, and blue sub-pixel information of the pixel are weighted and summed according to the preset red channel coefficient, green channel coefficient, and blue channel coefficient to obtain the brightness value corresponding to each pixel; Divide the 3×3 pixel area into three rows of pixels horizontally: top, middle and bottom. Calculate the difference between the maximum and minimum values ​​of the pixel brightness values ​​in each group to obtain three groups of horizontal brightness differences. Take the horizontal brightness difference corresponding to the middle row as the row direction brightness difference. The three sets of lateral brightness differences are analyzed, and the difference between the maximum and minimum values ​​among the three sets of lateral brightness differences is calculated. This difference is taken as the brightness difference in the column direction.

[0074] In one embodiment, the edge condition segmentation module 14 is further configured to: Configure a preset brightness difference threshold for judging edge features, wherein the preset brightness difference threshold is greater than 0 and less than 255; The row-direction brightness difference is compared with the preset brightness difference threshold to determine whether the row-direction brightness difference is greater than the threshold. The column-direction brightness difference is compared with the preset brightness difference threshold to determine whether the column-direction brightness difference is greater than the threshold. Based on the combination of the two comparison results, four marginal conditions are obtained.

[0075] Based on the combination of the two comparison results, four marginal conditions are identified, including: The first edge condition is that the brightness difference in the row direction is greater than the preset brightness difference threshold, and the brightness difference in the column direction is greater than the preset brightness difference threshold. The second edge condition is that the brightness difference in the row direction is greater than the preset brightness difference threshold, and the brightness difference in the column direction is less than or equal to the preset brightness difference threshold. The third edge condition is that the brightness difference in the row direction is less than or equal to the preset brightness difference threshold, and the brightness difference in the column direction is greater than the preset brightness difference threshold. The fourth edge condition is that the brightness difference in the row direction is less than or equal to the preset brightness difference threshold, and the brightness difference in the column direction is less than or equal to the preset brightness difference threshold.

[0076] In one embodiment, the adaptive rendering module 15 is further configured to: Among them, based on the multiple edge conditions, an adaptive weighting strategy is adopted, including: An adaptive weighted coefficient lookup table is pre-defined. The table is indexed by the four edge conditions obtained from the division. Each edge condition corresponds to a unique set of weighted coefficients. Each set of weighted coefficients contains five coefficients, which correspond to the left neighboring pixel, itself, right neighboring pixel, upper neighboring pixel, and lower neighboring pixel of the target pixel to be rendered. The sum of each set of coefficients is 1. Each set of coefficients is pre-defined with an adaptive value according to the rendering requirements of different edge scenes. Using the defined edge condition as the query keyword, the preset adaptive weighted coefficient lookup table is retrieved, and a set of adaptive weighted coefficients corresponding to the edge condition is extracted. The adaptive weighted coefficient set is used as the adaptation coefficient for the current pixel rendering calculation.

[0077] The process of executing the first or second conversion process, calculating the rendering value of the target image sub-pixels, and completing the sub-pixel rendering includes: Based on the row type of the target pixel to be rendered in the target image, determine the conversion process to be performed. If the row is RG, perform the first conversion process; if the row is BG, perform the second conversion process. If the first conversion process is performed, the adaptation coefficients are used to perform a weighted summation of the red sub-pixel information and green sub-pixel information of the neighboring source pixels in the 3×3 pixel area to obtain the red sub-pixel rendering value and green sub-pixel rendering value of the target pixel. If the second conversion process is performed, the adaptation coefficients are used to perform weighted summation on the blue sub-pixel information and green sub-pixel information of the neighboring source pixels in the 3×3 pixel area to obtain the blue sub-pixel rendering value and green sub-pixel rendering value of the target pixel. The calculated subpixel rendering value is assigned to the corresponding pixel to be rendered in the target image to complete the subpixel rendering of that pixel.

[0078] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0079] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0080] This specification and accompanying drawings are merely illustrative examples of the invention and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its scope. Therefore, if such modifications and modifications fall within the scope of the invention and its equivalents, the invention is intended to include these modifications and modifications.

Claims

1. A sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness, characterized in that, include: Obtain the source image and the target image format, wherein each pixel of the source image contains RGB sub-pixel information, and each pixel of the target image contains RG sub-pixel information or BG sub-pixel information; Based on the arrangement rules of sub-pixels in the target image, the first conversion process and the second conversion process are determined; The source image is copied and extended outward from its boundary pixels. Brightness calculations are performed on a 3×3 pixel region centered on the target pixel to be rendered, obtaining the row-direction brightness difference and column-direction brightness difference, including: Centered on the position of the target pixel in the expanded source image, a 3×3 pixel region is defined, encompassing the target pixel and its upper, lower, left, right, and diagonally adjacent pixels. For each pixel in the 3×3 pixel region, the red, green, and blue sub-pixel information of that pixel is weighted and summed according to preset red, green, and blue channel coefficients to obtain the brightness value corresponding to each pixel. The 3×3 pixel region is horizontally divided into three rows of pixels: upper, middle, and lower. The difference between the maximum and minimum brightness values ​​in each group is calculated to obtain three sets of horizontal brightness differences. The horizontal brightness difference corresponding to the middle row is taken as the row-direction brightness difference. The three sets of horizontal brightness differences are analyzed, and the difference between the maximum and minimum values ​​in the three sets of horizontal brightness differences is calculated. This difference is taken as the column-direction brightness difference. Based on the comparison results of the row-direction brightness difference, column-direction brightness difference, and preset brightness difference thresholds, multiple edge conditions are defined, including: Configure a preset brightness difference threshold for judging edge features, wherein the preset brightness difference threshold is greater than 0 and less than 255; compare the row-direction brightness difference with the preset brightness difference threshold to determine whether the row-direction brightness difference is greater than the threshold; compare the column-direction brightness difference with the preset brightness difference threshold to determine whether the column-direction brightness difference is greater than the threshold; based on the combination of the two comparison results, edge conditions are obtained, wherein the edge conditions include a first edge condition, a second edge condition, a third edge condition, and a fourth edge condition, wherein the first edge condition corresponds to an intersecting edge scenario, the second edge condition corresponds to a horizontal edge scenario, the third edge condition corresponds to a vertical edge scenario, and the fourth edge condition corresponds to a no-edge scenario; Based on the aforementioned multiple edge conditions, an adaptive weighting strategy is employed to execute either the first or second transformation process, calculate the rendering values ​​of sub-pixels in the target image, and complete sub-pixel rendering, including: A pre-defined adaptive weighted coefficient lookup table is used, indexed by the defined edge conditions. Each edge condition corresponds to a unique set of weighted coefficients. Each set of weighted coefficients contains five coefficients, corresponding to the left neighbor, itself, right neighbor, top neighbor, and bottom neighbor of the target pixel to be rendered, respectively. The sum of each set of coefficients is 1. Each set of coefficients has a pre-defined adaptation value based on the rendering requirements of different edge scenes. Using the determined edge condition as the query keyword, the pre-defined adaptive weighted coefficient lookup table is searched to extract the set of adaptive weighted coefficients corresponding to the edge condition. The set of adaptive weighted coefficients is used as the adaptation coefficients for the current pixel rendering calculation. Based on the row type of the target pixel to be rendered in the target image, the required transformation is determined. The conversion process is as follows: if the row belongs to row RG, a first conversion process is executed; if the row belongs to row BG, a second conversion process is executed. If the first conversion process is executed, the adaptation coefficients are used to perform a weighted summation of the red and green sub-pixel information of the neighboring source pixels within a 3×3 pixel region to obtain the red and green sub-pixel rendering values ​​of the target pixel. If the second conversion process is executed, the adaptation coefficients are used to perform a weighted summation of the blue and green sub-pixel information of the neighboring source pixels within a 3×3 pixel region to obtain the blue and green sub-pixel rendering values ​​of the target pixel. The calculated sub-pixel rendering values ​​are then assigned to the corresponding pixel to be rendered in the target image to complete the sub-pixel rendering of that pixel.

2. The sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness according to claim 1, characterized in that, Obtain the source image and the target image format, including: Obtain a source image frame to be displayed, and obtain the pixel coordinates of the source image. Each pixel of the source image contains independent red sub-pixel information, green sub-pixel information, and blue sub-pixel information. The pixel arrangement rules of the RGBG type display panel are determined, wherein the pixels of the display panel are alternately set as RG rows and BG rows in units of rows; Based on the pixel arrangement rules and the source image pixel coordinates, the sub-pixel type corresponding to the source image pixel coordinates in the target image is determined. If it is in row RG in the display panel, then the target image at that coordinate is an RG type pixel containing red and green sub-pixels. If it is in row BG in the display panel, then it is a BG type pixel containing blue and green sub-pixels, thus obtaining the target image corresponding to the RGBG type display panel.

3. The sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness according to claim 1, characterized in that, Based on the arrangement rules of sub-pixels in the target image, a first conversion process and a second conversion process are determined, including: Based on the alternating arrangement rule of RG and BG rows of the RGBG type display panel, the row type of each pixel in the target image is determined. The row type includes RG row or BG row. Based on the row type of the pixel, the sub-pixel rendering of the target image is divided into two adaptation scenarios, corresponding to the rendering requirements of RG type pixels and BG type pixels respectively. If the row to which the pixel belongs is an RG-type pixel in row RG, then the first conversion process is determined to be the process of converting the red sub-pixel information and green sub-pixel information of the source image into the red sub-pixel display data and green sub-pixel display data of the corresponding RG-type pixel in the target image; If the row to which the pixel belongs is a BG type pixel in the BG row, then the second conversion process is determined to be the process of converting the blue sub-pixel information and green sub-pixel information of the source image into the blue sub-pixel display data and green sub-pixel display data of the corresponding BG type pixel in the target image.

4. The sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness according to claim 1, characterized in that, The process of copying and extending the boundary pixels of the source image outward includes: If the target pixel to be rendered is located at the first row, last row, first row, or last row in the source image, it is necessary to expand outward by copying the pixel information of the corresponding boundary. The first row of pixels is copied upwards, the last row of pixels is copied downwards, the first row of pixels is copied to the left, and the last row of pixels is copied to the right, thus completing the neighboring pixel data required for the 3×3 pixel area.

5. The sub-pixel rendering method for an RGBG type display panel based on two-dimensional edge awareness according to claim 1, characterized in that, Based on the combination of the two comparison results, the marginal conditions are determined, including: The first edge condition is that the brightness difference in the row direction is greater than the preset brightness difference threshold, and the brightness difference in the column direction is greater than the preset brightness difference threshold. The second edge condition is that the brightness difference in the row direction is greater than the preset brightness difference threshold, and the brightness difference in the column direction is less than or equal to the preset brightness difference threshold. The third edge condition is that the brightness difference in the row direction is less than or equal to the preset brightness difference threshold, and the brightness difference in the column direction is greater than the preset brightness difference threshold. The fourth edge condition is that the brightness difference in the row direction is less than or equal to the preset brightness difference threshold, and the brightness difference in the column direction is less than or equal to the preset brightness difference threshold.

6. A sub-pixel rendering system for an RGBG type display panel based on two-dimensional edge awareness, characterized in that, The system is used to implement the RGBG type display panel sub-pixel rendering method based on two-dimensional edge awareness as described in any one of claims 1-5, the system comprising: The image acquisition module is used to acquire a source image and acquire the format of a target image, wherein each pixel of the source image contains RGB sub-pixel information, and each pixel of the target image contains RG sub-pixel information or BG sub-pixel information; The conversion process determination module is used to determine the first conversion process and the second conversion process based on the arrangement rules of sub-pixels in the target image; The brightness difference calculation module is used to copy and expand the boundary pixels of the source image outward, and to calculate the brightness of a 3×3 pixel area centered on the target pixel to be rendered, and to obtain the brightness difference in the row direction and the brightness difference in the column direction respectively. The edge condition segmentation module is used to segment multiple edge conditions based on the comparison results of the row-direction brightness difference, column-direction brightness difference and preset brightness difference threshold. The adaptive rendering module is used to perform the first transformation process or the second transformation process based on the multiple edge conditions and an adaptive weighting strategy, calculate the rendering value of the sub-pixels of the target image, and complete the sub-pixel rendering.

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