Image display method and display device

Abstract

The application provides an image display method and a display device. The image display method comprises the following steps: synchronously acquiring a pixel brightness value, an original RGB pixel value and a signal frame rate of a to-be-displayed image; when the signal frame rate is greater than a preset frame rate threshold, completing binaryzation through a brightness threshold to obtain a binaryzation image; using a sliding matrix to traverse and identify an image high-frequency scene; determining a high-frequency level based on a pure color row arrangement mode; obtaining compensation gain information through a first mapping relationship between the high-frequency level and the signal frame rate; and finally correcting and outputting the original RGB pixel value. The image high-frequency scene and the grading mechanism are used to realize gain differentiation matching, which overcomes the defect that the global uniform compensation of the prior art cannot adapt to different high-frequency picture working conditions, and effectively improves the image color accuracy and scene adaptability under high frame rate display.

Description

Technical Field

[0001] This application belongs to the field of display device technology, and in particular relates to an image display method and display device. Background Technology

[0002] When high refresh rate display devices transmit high-frequency image signals, the scan lines and data lines of the display device panel are densely intertwined to form a parasitic coupling network. Rapid voltage jumps can easily cause capacitive crosstalk in the lines, resulting in abnormal offset of the RGB sub-pixel driving voltage, which in turn causes problems such as color cast and color distortion.

[0003] Existing color cast optimization solutions mostly rely on overall hardware voltage adjustment, which is a global unified compensation method. However, this method is not targeted and has poor adaptability for high-frequency texture images such as alternating bright and dark lines, and there are still obvious color cast residues, resulting in poor color consistency and display quality. Summary of the Invention

[0004] In view of this, embodiments of this application provide an image display method and display device that can optimize high-frequency color shift problems, improve scene adaptability, and enhance image quality.

[0005] In a first aspect, embodiments of this application provide an image display method, including: Obtain the brightness value, original RGB pixel value, and signal frame rate of the pixels in the image to be displayed; When the signal frame rate is greater than a preset frame rate threshold, the brightness values ​​of the pixels in the image to be displayed are binarized according to the brightness value and the brightness threshold to obtain a binarized image. The binary image is traversed using a sliding matrix. Based on the binary brightness values ​​of the pixels in each sliding matrix, it is determined whether each pixel matrix is ​​a high-frequency scene of the image. In the case that the pixel matrix is ​​a high-frequency scene of the image, all pixel rows in the pixel matrix are solid color rows. When the target pixel matrix is ​​a high-frequency scene of the image, the high-frequency level of the image high-frequency scene is obtained based on the arrangement pattern of the solid color rows in the target pixel matrix; Based on the image high frequency level, the signal frame rate, and the pre-established first mapping relationship, the compensation gain information corresponding to the target pixel matrix is ​​obtained, wherein the first mapping relationship includes the correspondence between the image high frequency level, the signal frame rate, and the compensation gain information; The original RGB pixel values ​​of the pixels in the target pixel matrix are corrected based on the compensation gain information, so that the image is displayed based on the corrected RGB pixel values.

[0006] The method provided in this application synchronously acquires the pixel brightness values, original RGB pixel values, and signal frame rate of the image to be displayed. When the signal frame rate is greater than a preset frame rate threshold, binarization is performed using the brightness threshold to obtain a binarized image. A sliding matrix is ​​used to traverse and identify high-frequency scenes in the image, and the high-frequency level is determined based on the solid color row arrangement pattern. Then, compensation gain information is obtained through the first mapping relationship between the high-frequency level and the signal frame rate. Finally, the original RGB pixel values ​​are corrected and output for display. By relying on the high-frequency scene and hierarchical mechanism of the image to achieve differentiated gain matching, the shortcomings of the existing technology's global uniform compensation cannot adapt to different high-frequency image conditions are overcome, effectively improving the color accuracy and scene adaptability of the image under high frame rate display.

[0007] In some embodiments, correcting the original RGB pixel values ​​of pixels in the target pixel matrix based on the compensation gain information includes: The color component values ​​of the RGB pixel values ​​of each pixel in the target pixel matrix are compared with a preset high-brightness pixel threshold and a preset low-brightness pixel threshold to obtain a comparison result, wherein the high-brightness pixel threshold is greater than the low-brightness pixel threshold. Based on the comparison results, it is determined whether each pixel simultaneously has a bright component and a low component, wherein the bright component is defined as a color component value greater than the bright pixel threshold, and the low component is defined as a color component value less than the low pixel threshold. When a target pixel has both high-brightness and low-brightness components, the RGB pixel value of the target pixel is corrected based on the compensation gain information.

[0008] The method provided in this application compares the RGB color components of each pixel using high-brightness pixel thresholds and low-brightness pixel thresholds to identify target pixels that simultaneously possess both high-brightness and low-brightness components. Correction compensation is then performed only on these target pixels exhibiting color imbalance. This method can accurately locate color-skewed pixels with imbalanced RGB channels within a single pixel, distinguishing them from normal pixels and achieving pixel-level precise targeted correction. It avoids color distortion and detail loss in normal images caused by uniform compensation across all pixels, preserving the original image display details to the maximum extent while correcting color casts.

[0009] In some embodiments, correcting the RGB pixel values ​​of the target pixel based on the compensation gain information includes: Calculate the pixel difference between the highlight component and the low brightness component in the target pixel; Calculate the compensation coefficient corresponding to the target pixel based on the pixel difference; The high-brightness component is attenuated based on the compensation coefficient and compensation gain information, and the low-brightness component is compensated to correct the RGB pixel value of the target pixel.

[0010] The method provided in this application calculates the pixel difference between the highlight and low-brightness components of a target pixel, calculates a corresponding compensation coefficient based on this pixel difference, and combines compensation gain information to attenuate the highlight component and compensate for the low-brightness component to correct the RGB pixel values. It can quantify the degree of color cast based on the true channel difference of a single pixel, making the compensation coefficient match the magnitude of the color cast of a single pixel. This solves the problem that a fixed compensation level cannot adapt to the color cast differences of different pixels, significantly improving the accuracy and specificity of single-pixel color correction.

[0011] In some embodiments, calculating the compensation coefficient corresponding to the target pixel based on the pixel difference includes: When the pixel difference is less than the low threshold of the difference, the preset basic low gain coefficient is determined as the compensation coefficient; When the pixel difference is greater than or equal to the low difference threshold and less than or equal to the high difference threshold, the compensation coefficient is calculated based on the low difference threshold, the high difference threshold, the basic low gain coefficient, the preset basic high gain coefficient, and the brightness difference. If the pixel difference is greater than the high threshold of the difference, the basic high gain coefficient is determined as the compensation coefficient.

[0012] The method provided in this application, based on the relationship between pixel difference and low and high threshold values, uses a basic low gain coefficient, an interpolated gain coefficient, and a basic high gain coefficient as compensation coefficients to achieve graded adaptation of color cast degree. It can match corresponding compensation levels for pixels with slight, moderate, and severe color cast, avoiding the technical defects of overcompensation for slight color cast and undercompensation for severe color cast, and significantly improving the stability and adaptability of the compensation algorithm under different color cast scenarios.

[0013] In some embodiments, calculating the compensation coefficient based on the low difference threshold, the high difference threshold, the basic low gain coefficient, a preset basic high gain coefficient, and the brightness difference includes: Calculate a first difference between the brightness difference and the low threshold of the difference; calculate a second difference between the base high gain coefficient and the base low gain coefficient; and calculate a third difference between the high threshold of the difference and the low threshold of the difference. Divide the second difference by the third difference to obtain the difference ratio, and multiply the difference ratio by the first difference to obtain the increase in the compensation coefficient; The compensation coefficient is obtained by adding the increase in the compensation coefficient to the basic low gain coefficient.

[0014] The method provided in this application defines a linear interpolation calculation logic for the compensation coefficient. The increase in the compensation coefficient is calculated step-by-step using a first difference, a second difference, and a third difference, and then superimposed with a base low-gain coefficient to obtain the final compensation coefficient. This ensures that the compensation coefficient changes continuously and smoothly with the pixel difference within a moderate color cast range, eliminating abrupt changes and level shifts in the compensation coefficient. It effectively avoids color banding and screen flickering caused by abrupt compensation changes in dynamic scenes, ensuring the continuity and stability of the displayed image.

[0015] In some embodiments, attenuating the high-brightness component and compensating for the low-brightness component based on the compensation coefficient and compensation gain information includes: The attenuation is obtained by multiplying the high brightness component, the compensation coefficient, and the compensation gain information; Subtract the attenuation amount from the highlight component to obtain the pixel value of the attenuated highlight component; The low-brightness component, the compensation coefficient, and the compensation gain information are multiplied to obtain the lift amount; The low-brightness component is then augmented with an uplift amount to obtain the compensated pixel value of the low-brightness component.

[0016] The method provided in this application specifies that the attenuation of the high-brightness component and the enhancement of the low-brightness component are calculated by multiplying the compensation coefficient and the compensation gain information, and the pixel values ​​of the high-brightness and low-brightness components are updated accordingly. Based on the above-mentioned standardized proportional operation characteristics, it achieves accurate reduction of abnormally high-brightness components and accurate enhancement of abnormally low-brightness components, offsetting the RGB channel voltage imbalance deviation caused by high-frequency signal coupling, correcting the color cast problem caused by hardware crosstalk at the image pixel level, and the color correction logic conforms to the fault mechanism, resulting in a stable and reliable correction effect.

[0017] In some embodiments, the brightness threshold includes a high brightness threshold and a low brightness threshold, wherein the high brightness threshold is greater than the low brightness threshold, and the step of binarizing the brightness values ​​of pixels in the image to be displayed based on the brightness value and the brightness threshold to obtain a binarized image includes: Set the brightness value of pixels whose brightness value is greater than the high brightness threshold to 1; The brightness values ​​of pixels with brightness values ​​less than the low brightness threshold are set to 0 to perform binarization processing on the brightness values ​​of pixels in the image to be displayed.

[0018] The method provided in this application specifies that pixel brightness values ​​are binarized using high brightness thresholds and low brightness thresholds, with values ​​greater than the high brightness threshold marked as 1 and values ​​less than the low brightness threshold marked as 0. This unifies the pixel brightness binarization judgment standard for the entire frame image, providing quantified and unified basic feature data for subsequent high-frequency scene recognition and solid color row judgment using sliding matrix, effectively reducing the probability of feature recognition misjudgment and improving the accuracy of high-frequency scene detection and the overall robustness of the algorithm.

[0019] In some embodiments, obtaining the image high-frequency level of the high-frequency scene based on the arrangement pattern of solid color rows in the target pixel matrix includes: The arrangement pattern of solid color rows in the target pixel matrix is ​​matched with a pre-established second mapping relationship to obtain the high-frequency level of the image corresponding to the target pixel matrix. The second mapping relationship includes the correspondence between the arrangement pattern of solid color rows and the high-frequency level of the image.

[0020] The method provided in this application relies on a second mapping relationship between solid color row arrangement patterns and high-frequency levels to match and obtain the corresponding high-frequency level of the image. It can standardize the level classification of high-frequency images with different solid color row arrangement patterns and different densities, providing a precise scene level basis for subsequent gain matching of the first mapping relationship, achieving accurate correspondence between scene features and compensation gain, and improving the matching accuracy of differentiated compensation.

[0021] In some embodiments, the image high-frequency level includes: a first image high-frequency level and a second image high-frequency level, wherein the first image high-frequency level is higher than the second image high-frequency level, and the number of consecutive solid color rows corresponding to the first image high-frequency level is greater than the number of consecutive solid color rows corresponding to the second image high-frequency level; in the first mapping relationship, when the image high-frequency levels are the same, the higher the signal frame rate, the greater the compensation gain information; when the signal frame rate is the same, the higher the image high-frequency level, the greater the gain compensation information.

[0022] The method provided in this application specifies the number of consecutive solid color rows corresponding to high and low frequency levels, and simultaneously defines a dual control rule under the first mapping relationship: for the same level, the higher the frame rate, the greater the gain; for the same frame rate, the higher the level, the greater the gain. This can match the hardware-coupled color cast rules of high refresh rate screens (the denser the rows and the higher the frame rate, the more severe the color cast), achieving adaptive dynamic control with higher compensation intensity for more stringent color cast conditions. It adapts to all refresh rates and all types of high-frequency texture images, significantly improving the overall optimization effect of high-frequency coupled color cast on high refresh rate screens.

[0023] In a second aspect, embodiments of this application provide a display device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any one of the first aspects; Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any of the above-mentioned embodiments.

[0024] Fourthly, embodiments of this application provide a computer program product that, when run on a terminal device, causes a display device to execute any of the methods described above. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 A schematic diagram illustrating the implementation flow of an image display method provided in an embodiment of this application; Figure 2 A schematic diagram illustrating the implementation process of step S106 provided in an embodiment of this application; Figure 3 A schematic diagram illustrating the implementation process of step S63 provided in an embodiment of this application; Figure 4 This application provides a schematic diagram illustrating the correspondence between pixel differences and compensation coefficients in an embodiment of the present application. Figure 5 This is a schematic diagram illustrating the implementation process of binarization processing provided in an embodiment of this application; Figure 6 A schematic diagram illustrating a first mapping relationship provided in an embodiment of this application; Figure 7 A flowchart illustrating a specific example of an image display method provided in this application embodiment; Figure 8 This is a schematic diagram of the structure of a display device provided in an embodiment of this application. Detailed Implementation

[0027] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0028] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0029] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0030] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once detected," or "in response to detection."

[0031] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0032] References to "one embodiment" or "some embodiments" in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in still other embodiments" appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized.

[0033] In view of the problems in related technologies, this application provides an image display method that can be applied to display devices, such as mobile phones, computers, and televisions. Figure 1 This is a schematic diagram illustrating the implementation process of an image display method provided in an embodiment of this application, such as... Figure 1 As shown, it includes: Step S101: Obtain the brightness value, original RGB pixel value and signal frame rate of the pixels of the image to be displayed.

[0034] In this embodiment, the image to be displayed refers to the original image signal frame that has been rendered by the display device driver but has not yet been refreshed and output to the display panel. The brightness value of a pixel is a single-channel value calculated by weighting the original RGB three-channel component values ​​of a single pixel. It is used to characterize the brightness and darkness features of a single pixel and is used for image scene feature recognition. The original RGB pixel value is the basic data that constitutes the color of a single pixel, containing three channel component values: R (red), G (green), and B (blue). It is the original image color signal to be corrected and directly corresponds to the sub-pixel driving amplitude of the display panel. The signal frame rate is the number of frames of the image signal transmitted to the display panel per second. It characterizes the refresh rate of the image signal and directly corresponds to the switching rate of the high refresh rate pixel clock. It is a core hardware parameter for judging the risk of hardware coupling color deviation.

[0035] In this embodiment, before the image is refreshed and displayed, the complete image to be displayed is captured in real time, the original RGB three-channel values ​​of the image are extracted pixel by pixel, and the brightness value corresponding to each pixel is calculated by a fixed brightness weighting formula; at the same time, the real-time signal frame rate of the current display link is read synchronously to complete the synchronous acquisition of image data and hardware operating data.

[0036] Step S102: When the signal frame rate is greater than a preset frame rate threshold, the brightness values ​​of the pixels in the image to be displayed are binarized according to the brightness value and the brightness threshold to obtain a binarized image.

[0037] In this embodiment, the brightness threshold is a preset pixel brightness judgment standard used to distinguish between bright and low-brightness pixels in the image. It includes a high brightness threshold and a low brightness threshold, which serve as the quantitative judgment basis for image binarization processing. The binarized image is a feature image obtained after thresholding the pixel brightness values ​​of the original image. It includes two marked states, used to remove color interference and simply retain the brightness and darkness arrangement texture features of the image.

[0038] In this embodiment, image scene detection is initiated only when the real-time signal frame rate exceeds a preset high refresh rate threshold or there is a risk of hardware-induced color distortion. The preset high and low brightness thresholds are called, and the pixel brightness value is compared with the threshold value pixel by pixel to complete the binary marking of the pixels. The original brightness image with multiple gray levels is converted into a feature image containing two states, eliminating complex color and gray level interference, and standardizing the image brightness and texture features to facilitate the unified recognition and judgment of high-frequency scenes. The brightness values ​​of pixels that are greater than the low brightness threshold and less than the high brightness threshold do not need to be processed.

[0039] Step S103: The binary image is traversed using a sliding matrix. Based on the binary brightness values ​​of the pixels in each sliding matrix, it is determined whether each pixel matrix is ​​a high-frequency scene of the image. In the case that the pixel matrix is ​​a high-frequency scene of the image, all pixel rows in the pixel matrix are solid color rows.

[0040] In this embodiment, the sliding matrix is ​​a matrix window used for local image feature traversal detection. It scans the entire frame of the binarized image in a sliding traversal manner to extract the brightness and darkness distribution patterns of local scenes and identify high-frequency scene features. The sliding matrix can be a 5x5 matrix. Solid color rows are rows of pixels in an image that exhibit a single brightness and darkness characteristic, including rows with all high brightness and rows with all low brightness, without any mixing of bright and dark pixels. They are the basic units constituting high-frequency color-shifting images.

[0041] In this embodiment, the binary image is traversed region by region by sliding matrix, and all pixel rows in each matrix are checked. If all pixel rows in the matrix are solid color rows and there are no mixed non-solid color rows, the local area is determined to be a high-frequency scene of the image, locking the high-occurrence area of ​​color cast and avoiding invalid calculations in low frame rate scenes without color cast.

[0042] Step S104: When the target pixel matrix is ​​a high-frequency scene of the image, the high-frequency level of the image high-frequency scene is obtained based on the arrangement pattern of the solid color rows in the target pixel matrix.

[0043] In this embodiment, the high-frequency level of the image is a scene level divided according to the arrangement pattern of solid color rows and the density of continuous arrangement, which is used to quantify and distinguish the severity of color cast in different images.

[0044] In this embodiment, for the target pixel matrix that has been determined to be a high-frequency scene in the image, the arrangement features such as the alternation pattern of solid color rows and the number of consecutive rows in the matrix are extracted, and matched with the preset level classification rules to quantify the high-frequency level of the image, so as to distinguish different color cast scenes and realize the fine classification of color cast conditions.

[0045] Step S105: Based on the image high frequency level, the signal frame rate, and the pre-established first mapping relationship, obtain the compensation gain information corresponding to the target pixel matrix, wherein the first mapping relationship includes the correspondence between the image high frequency level, the signal frame rate, and the compensation gain information.

[0046] In this embodiment of the application, the first mapping relationship is a pre-established and fixed correspondence relationship, specifically the matching association of the image high frequency level, signal frame rate and compensation gain information, which is used to adaptively match the corresponding compensation intensity according to the scene conditions.

[0047] In this embodiment, a pre-trained and solidified first mapping relationship model can be invoked. With the high frequency level of the current image and the real-time signal frame rate as dual input parameters, the compensation gain information corresponding to the high frequency scene of the current image can be accurately matched and output. This allows the overall compensation strength to adapt to both the image texture features and the hardware refresh conditions, achieving accurate matching between the working conditions and the compensation strength.

[0048] Step S106: Correct the original RGB pixel values ​​of the pixels in the target pixel matrix based on the compensation gain information, so as to display the image based on the corrected RGB pixel values.

[0049] In this embodiment, the compensation gain information is the overall compensation intensity parameter corresponding to different high-frequency scenes and different frame rate conditions of different images. It is used to constrain the overall amplitude of pixel RGB correction and adapt to coupling color cast problems of different severity.

[0050] In this embodiment, the matched compensation gain information is applied to all pixels in the target high-frequency scene area to perform differential correction on the original RGB channel values ​​of the pixels, thereby offsetting the color shift problem caused by high-frequency signal coupling; the corrected RGB pixel values ​​are output to the display panel to complete the final screen refresh display.

[0051] The method provided in this application synchronously acquires the pixel brightness value, original RGB pixel value, and signal frame rate of the image to be displayed. When the signal frame rate is greater than a preset frame rate threshold, binarization is performed using the brightness threshold to obtain a binarized image. A sliding matrix is ​​used to traverse and identify high-frequency scenes in the image, and the high-frequency level is determined based on the solid color row arrangement pattern. Then, compensation gain information is obtained through the first mapping relationship between the high-frequency level and the signal frame rate. Finally, the original RGB pixel values ​​are corrected and output for display. Compensation can be triggered only for high frame rate, high-frequency color-shifting scenes, avoiding invalid compensation calculations. At the same time, gain differentiation matching is achieved by relying on the high-frequency scene and hierarchical mechanism of the image, overcoming the defect of the existing technology that global uniform compensation cannot adapt to different high-frequency image conditions, effectively improving the color accuracy and scene adaptability of the image under high frame rate display.

[0052] In some embodiments, Figure 2 This application provides a schematic diagram of the implementation process of step S106, as shown in the embodiment. Figure 2 As shown, step S106 can be achieved through the following steps: Step S61: Compare the color component values ​​of the RGB pixel values ​​of each pixel in the target pixel matrix with a preset high-brightness pixel threshold and a preset low-brightness pixel threshold to obtain a comparison result, wherein the high-brightness pixel threshold is greater than the low-brightness pixel threshold.

[0053] In this embodiment, color component values ​​refer to the independent R-channel, G-channel, and B-channel values ​​in the original RGB pixel values ​​of a single pixel. These are independent sub-channel amplitudes that constitute the pixel color and are the smallest comparison unit for determining single-pixel color imbalance. The high-brightness pixel threshold is a preset upper limit threshold for channel amplitude determination, used to determine whether there are abnormally high components in a single RGB channel. This threshold value is greater than the low-brightness pixel threshold, serving as a quantitative standard for determining single-channel high-brightness characteristics. The low-brightness pixel threshold is a preset lower limit threshold for channel amplitude determination, used to determine whether there are abnormally low components in a single RGB channel, serving as a quantitative standard for determining single-channel low-brightness characteristics. The comparison result refers to the magnitude relationship obtained after comparing each RGB color component value of a single pixel with the high-brightness pixel threshold and the low-brightness pixel threshold, used to determine whether there is an RGB channel brightness imbalance within a single pixel.

[0054] In this embodiment, for all pixels in the target pixel matrix of the locked high-frequency scene, the independent R, G, and B color component values ​​of each pixel are split, and the values ​​of each color component are compared with the preset high-brightness pixel threshold and low-brightness pixel threshold. The amplitude comparison results of each channel are output uniformly based on the fixed threshold standard to complete the quantitative screening of the amplitude status of a single pixel in multiple channels.

[0055] Step S62: Based on the comparison result, determine whether each pixel simultaneously has a bright component and a low component, wherein the bright component is defined as a color component value greater than the bright pixel threshold, and the low component is defined as a color component value less than the low pixel threshold.

[0056] In this embodiment, the high-brightness component is an abnormally high-value channel component in the RGB color components of a single pixel, where the component value is greater than the high-brightness pixel threshold. It corresponds to the color channel that is boosted by voltage coupling in high-frequency coupled color cast. The low-brightness component is an abnormally low-value channel component in the RGB color components of a single pixel, where the component value is less than the low-brightness pixel threshold. It corresponds to the color channel that is suppressed and has insufficient amplitude in high-frequency coupled color cast.

[0057] In this embodiment, based on the comparison results obtained from the aforementioned channel comparison, the channel status can be screened pixel by pixel to determine whether there are both high-brightness channels that meet the criteria for high brightness components and low-brightness channels that meet the criteria for low brightness components within the same pixel. This allows for the accurate screening of abnormal pixels with RGB channel imbalance and coupled color cast characteristics, thus distinguishing between normal unbalanced pixels and pixels at risk of color cast.

[0058] Step S63: When the target pixel has both high-brightness and low-brightness components, the RGB pixel value of the target pixel is corrected based on the compensation gain information.

[0059] In this embodiment, the target pixel is a single pixel in a high-frequency scene region that simultaneously contains both high-brightness and low-brightness components, exhibits color coupling imbalance, and requires RGB correction.

[0060] In this embodiment, a correction logic is initiated for imbalanced target pixels that simultaneously possess both high-brightness and low-brightness components. The original RGB pixel values ​​of such pixels are specifically corrected for color, and invalid correction operations for normal pixels without imbalance are eliminated, thereby achieving precise targeted correction of color-biased pixels.

[0061] The method provided in this application compares the RGB color components of each pixel using high-brightness pixel thresholds and low-brightness pixel thresholds to identify target pixels that simultaneously possess both high-brightness and low-brightness components. Correction compensation is then performed only on these target pixels exhibiting color imbalance. This method can accurately locate color-skewed pixels with imbalanced RGB channels within a single pixel, distinguishing them from normal pixels and achieving pixel-level precise targeted correction. It avoids color distortion and detail loss in normal images caused by uniform compensation across all pixels, preserving the original image display details to the maximum extent while correcting color casts.

[0062] In some embodiments, Figure 3 A schematic diagram illustrating the implementation flow of step S63 provided in an embodiment of this application is shown below. Figure 3 As shown, step S63 can be achieved through the following steps: Step S631: Calculate the pixel difference between the high-brightness component and the low-brightness component in the target pixel.

[0063] In this embodiment, the pixel difference refers to the numerical difference between the determined high-brightness component and low-brightness component within the same target pixel. It is used to quantify the degree of imbalance of the RGB channels of a single pixel and is the core calculation variable of the compensation coefficient.

[0064] In this embodiment, for the selected target pixels to be corrected, the high brightness component value and low brightness component value of the pixel are retrieved, and the difference is calculated to obtain a precise pixel difference value. The RGB channel imbalance caused by high frequency coupling of the current pixel is represented in the form of quantitative data, providing a precise numerical basis for subsequent differential compensation coefficient calculation.

[0065] Step S632: Calculate the compensation coefficient corresponding to the target pixel based on the pixel difference.

[0066] In this embodiment, the compensation coefficient is a pixel-level correction coefficient dynamically calculated based on the actual channel difference of a single pixel. It is used to characterize the adaptation compensation strength of a single pixel, which is different from the scene-level compensation gain information, and realizes fine-grained compensation adjustment in the single-pixel dimension.

[0067] In this embodiment, the pixel difference obtained by quantization is used as the only input variable. According to the preset coefficient calculation rules, a unique compensation coefficient corresponding to the imbalance degree of the pixel is generated, so that each color-biased pixel has an independent correction parameter that adapts to its own imbalance degree, thereby realizing pixel-level differential parameter adaptation.

[0068] Step S633: Attenuate the high-brightness component and compensate the low-brightness component based on the compensation coefficient and compensation gain information to correct the RGB pixel value of the target pixel.

[0069] In this embodiment, compensation gain information from the scene dimension and compensation coefficients from the pixel dimension are integrated to form a dual-layer compensation control parameter; numerical attenuation calculation is performed on the abnormally high brightness component, and numerical boost compensation calculation is performed on the abnormally low brightness component, thus bidirectionally correcting the imbalance of the single pixel RGB channel and finally achieving accurate correction of the original RGB pixel value of the target pixel.

[0070] The method provided in this application calculates the pixel difference between the highlight and low-brightness components of a target pixel, calculates a corresponding compensation coefficient based on this pixel difference, and combines compensation gain information to attenuate the highlight component and compensate for the low-brightness component to correct the RGB pixel values. It can quantify the degree of color cast based on the true channel difference of a single pixel, making the compensation coefficient match the magnitude of the color cast of a single pixel. This solves the problem that a fixed compensation level cannot adapt to the color cast differences of different pixels, significantly improving the accuracy and specificity of single-pixel color correction.

[0071] In some embodiments, step S632 can be implemented by the following steps: Step S6321: If the pixel difference is less than the low threshold of the difference, the preset basic low gain coefficient is determined as the compensation coefficient.

[0072] In this embodiment, the low threshold for difference is a preset lower limit for pixel difference judgment, used to define the range of slight color imbalance in pixels, and is the critical judgment criterion for fixed low gain compensation. The basic low gain coefficient is a preset fixed compensation coefficient, corresponding to the basic compensation level for cases with small pixel differences and slight color cast.

[0073] In this embodiment, when the pixel difference of the target pixel is less than the preset low threshold of difference, it is determined that the RGB channel imbalance of the pixel is slight and the color cast is weak. The preset fixed basic low gain coefficient is directly called as the final compensation coefficient of the current pixel, and a small compensation method is used to correct the slight color deviation, so as to avoid over-compensation causing image distortion.

[0074] In this embodiment of the application, the above steps can be expressed as: when Diff < Th_Low, Gain = Low_Gain, where Low_Gain is the basic low gain coefficient, Th_Low is the low threshold of the difference, and Diff is the pixel difference.

[0075] Step S6322: When the pixel difference is greater than or equal to the low difference threshold and less than or equal to the high difference threshold, calculate the compensation coefficient based on the low difference threshold, the high difference threshold, the basic low gain coefficient, the preset basic high gain coefficient, and the brightness difference.

[0076] In this embodiment, the high threshold for difference is a preset upper limit for pixel difference judgment, used to define the range of severe color imbalance in pixels. It is the critical judgment standard for fixed high gain compensation, and the value of the high threshold for difference is greater than the value of the low threshold for difference. The basic high gain coefficient is a preset fixed compensation coefficient, corresponding to the extreme compensation level for cases with large pixel differences and severe color cast. Its coefficient value is greater than the basic low gain coefficient.

[0077] In this embodiment, when the pixel difference of the target pixel is in the medium imbalance range between the low difference threshold and the high difference threshold, it is determined that the pixel has a moderate coupling color cast. Instead of using a fixed coefficient compensation, the dynamic compensation coefficient that adapts to the current imbalance level is solved by combining the range threshold boundary, the high and low basic gain coefficients and the actual difference of the current pixel through linkage calculation, so as to realize that the compensation intensity adapts to the color cast level.

[0078] Step S6323: If the pixel difference is greater than the difference high threshold, the basic high gain coefficient is determined as the compensation coefficient.

[0079] In this embodiment, when the pixel difference of the target pixel is greater than the preset high threshold of difference, it is determined that the RGB channel of the pixel is severely unbalanced and the high-frequency coupling color cast problem is prominent. The preset fixed basic high gain coefficient is directly called as the final compensation coefficient to correct the severe color cast defect with the maximum compensation force and ensure the color correction effect of the severely unbalanced pixel.

[0080] In this embodiment of the application, the above steps can be expressed as: when Diff > Th_High, Gain = High_Gain; High_Gain is the basic high-gain coefficient.

[0081] Figure 4 This application provides a schematic diagram illustrating the correspondence between pixel differences and compensation coefficients in an embodiment of the present application. Figure 4As shown in the figure, the horizontal axis is Diff and the vertical axis is the compensation coefficient. When Diff < Th_Low, Gain = Low_Gain. When Th_Low < Diff < Th_High, the compensation coefficient gradually increases. When Diff > Th_High, Gain = High_Gain.

[0082] The method provided in this application, based on the relationship between pixel difference and low and high threshold values, uses a basic low gain coefficient, an interpolated gain coefficient, and a basic high gain coefficient as compensation coefficients to achieve graded adaptation of color cast degree. It can match corresponding compensation levels for pixels with slight, moderate, and severe color cast, avoiding the technical defects of overcompensation for slight color cast and undercompensation for severe color cast, and significantly improving the stability and adaptability of the compensation algorithm under different color cast scenarios.

[0083] In some embodiments, step S6322 can be implemented by the following steps: Calculate the first difference between the brightness difference and the low threshold of the difference; calculate the second difference between the base high gain coefficient and the base low gain coefficient; and calculate the third difference between the high threshold of the difference and the low threshold of the difference; divide the second difference by the third difference to obtain the difference ratio; multiply the difference ratio by the first difference to obtain the increase in the compensation coefficient; add the increase in the compensation coefficient to the base low gain coefficient to obtain the compensation coefficient.

[0084] In this embodiment of the application, the above steps can be represented by the following formula: ; in, For compensation coefficient, Based on low gain coefficient, Based on high gain coefficient, For the high threshold of the difference, For the low threshold of the difference, This represents the brightness difference.

[0085] The method provided in this application defines a linear interpolation calculation logic for the compensation coefficient. The increase in the compensation coefficient is calculated step-by-step using a first difference, a second difference, and a third difference, and then superimposed with a base low-gain coefficient to obtain the final compensation coefficient. This ensures that the compensation coefficient changes continuously and smoothly with the pixel difference within a moderate color cast range, eliminating abrupt changes and level shifts in the compensation coefficient. It effectively avoids color banding and screen flickering caused by abrupt compensation changes in dynamic scenes, ensuring the continuity and stability of the displayed image.

[0086] In some embodiments, step S633 can be implemented by the following steps: Step S6331: Multiply the highlight component, the compensation coefficient, and the compensation gain information to obtain the attenuation amount; subtract the attenuation amount from the highlight component to obtain the pixel value of the attenuated highlight component.

[0087] In this embodiment of the application, taking the highlight classification as the G component as an example, the calculation of the pixel value of G can be expressed as: G_out = GG × Gain × Gx; Where G_out is the pixel value of the attenuated highlight component, G is the original pixel value of the highlight component, Gain is the compensation coefficient, and Gx is the compensation gain information.

[0088] Step S6332: Multiply the low brightness component, the compensation coefficient, and the compensation gain information to obtain the uplift amount, and add the uplift amount to the low brightness component to obtain the pixel value of the compensated low brightness component.

[0089] In this embodiment of the application, taking the low-brightness component as the B component as an example, the calculation of the pixel value of B can be expressed as follows: B_out = B + B × Gain × Gx; Where B_out is the pixel value of the corrected low-brightness component, and B is the pixel value of the low-brightness component.

[0090] In this embodiment of the application, if R is a high-brightness component, G is also a high-brightness component, and B is a low-brightness component, then R, G, and B all need to be compensated. The compensation formula is as follows: R_out=RR×Gain×Gx; G_out=GG×Gain×Gx; B_out=B+B×Gain×Gx; Other situations can be handled similarly.

[0091] The method provided in this application specifies that the attenuation of the high-brightness component and the enhancement of the low-brightness component are calculated by multiplying the compensation coefficient and the compensation gain information, and the pixel values ​​of the high-brightness and low-brightness components are updated accordingly. Based on the above-mentioned standardized proportional operation characteristics, it achieves accurate reduction of abnormally high-brightness components and accurate enhancement of abnormally low-brightness components, offsetting the RGB channel voltage imbalance deviation caused by high-frequency signal coupling, correcting the color cast problem caused by hardware crosstalk at the image pixel level, and the color correction logic conforms to the fault mechanism, resulting in a stable and reliable correction effect.

[0092] In some embodiments, the brightness threshold includes a high brightness threshold and a low brightness threshold, wherein the high brightness threshold is greater than the low brightness threshold.

[0093] In this embodiment, the high brightness threshold is an upper critical threshold used for image brightness binarization. It is a pre-set fixed brightness value used to determine whether a pixel belongs to a high-brightness pixel, and the value is greater than the low brightness threshold. The low brightness threshold is a lower critical threshold used for image brightness binarization. It is a pre-set fixed brightness value used to determine whether a pixel belongs to a low-brightness pixel, and the value is less than the high brightness threshold.

[0094] Step S102 can be achieved through the following steps: Step S1021: Set the brightness value of pixels whose brightness value is greater than the high brightness threshold to 1.

[0095] In this embodiment, all pixels of the image to be displayed are traversed, and the original brightness value of a single pixel is compared with a preset high brightness threshold. For pixels whose brightness value exceeds the high brightness threshold, their binarized feature markers are uniformly assigned a value of 1, which is used to standardize the characterization of the bright pixel area in the image and complete the feature quantization marking of the bright pixels.

[0096] Step S1022: Set the brightness value of pixels with a brightness value less than the low brightness threshold to 0 to perform binarization processing on the brightness values ​​of pixels in the image to be displayed.

[0097] In this embodiment, pixels whose brightness values ​​do not reach the high brightness threshold are further thresholded, and pixels whose brightness values ​​are less than the low brightness threshold are uniformly assigned a binary feature mark of 0 to standardize the low brightness pixel area in the image. The binarization conversion of the pixel brightness of the entire frame image is completed through the double threshold and double assignment rules to generate a standardized binary image containing two feature marks of 0 and 1.

[0098] For example, a 5×5 sliding matrix is ​​used to extract features from the entire frame of the image. For each sliding matrix, the consistency of pixels within each row is checked. Each row of the 5×5 matrix is ​​traversed, and the sum of all pixel values ​​in that row is calculated (or the sum of the first pixel value and all subsequent pixel values ​​is checked). In the 5×5 matrix (1 for highlight, 0 for shadow), if all pixel values ​​in a row are 0, it is considered a "fully shadow row". If all pixel values ​​in a row are 1, it is considered a "fully highlight row". When all pixel values ​​are either 1 or 0, it is a solid color row; if the row contains both 0 and 1, it is considered a "non-solid color row". (A "tolerance" parameter can be set. For example, if more than 90% of the pixels in a row have the same value, it is considered that all pixels are the same.)

[0099] Figure 5 This is a schematic diagram illustrating the implementation process of binarization processing provided in an embodiment of this application, as shown below. Figure 5 As shown, a binarization process can be performed using a threshold filter to obtain a binarized image. In this sliding matrix, only the values ​​of 0 and 1 are included.

[0100] The method provided in this application specifies that pixel brightness values ​​are binarized using high brightness thresholds and low brightness thresholds, with values ​​greater than the high brightness threshold marked as 1 and values ​​less than the low brightness threshold marked as 0. This unifies the pixel brightness binarization judgment standard for the entire frame image, providing quantified and unified basic feature data for subsequent high-frequency scene recognition and solid color row judgment using sliding matrix, effectively reducing the probability of feature recognition misjudgment and improving the accuracy of high-frequency scene detection and the overall robustness of the algorithm.

[0101] In some embodiments, step S104 can be implemented through the following steps: The arrangement pattern of solid color rows in the target pixel matrix is ​​matched with a pre-established second mapping relationship to obtain the high-frequency level of the image corresponding to the target pixel matrix. The second mapping relationship includes the correspondence between the arrangement pattern of solid color rows and the high-frequency level of the image.

[0102] In this embodiment, the solid color row arrangement pattern refers to the overall texture arrangement feature composed of the number of consecutive solid color rows, the frequency of alternation, and the density of arrangement within the target pixel matrix. It is a core feature parameter for distinguishing the severity of color cast in different high-frequency scenes. The second mapping relationship is a pre-established and fixed exclusive correspondence, which stores the one-to-one matching rules between the solid color row arrangement pattern and the high-frequency level of the image separately. It does not require the participation of frame rate parameters and realizes direct quantitative mapping from image texture features to scene high-frequency levels.

[0103] In this embodiment, for a target pixel matrix that has been determined to be a high-frequency scene in an image, the arrangement and combination features of all solid color rows in the matrix are accurately extracted to form a unique arrangement pattern feature vector for the current matrix. The pre-trained and fixed second mapping relationship database is retrieved, and the solid color row arrangement pattern extracted in real time is traversed and matched with the preset standard arrangement pattern in the database to accurately match the high-frequency level of the image corresponding to the texture features of the current scene, thereby completing the quantitative grading output of the high-frequency scene and providing a grading basis for subsequent compensation gain matching.

[0104] In this embodiment of the application, the image high frequency level includes: a first image high frequency level and a second image high frequency level. The first image high frequency level is higher than the second image high frequency level. The number of consecutive solid color rows corresponding to the first image high frequency level is greater than the number of consecutive solid color rows corresponding to the second image high frequency level. In the first mapping relationship, when the image high frequency levels are the same, the higher the signal frame rate, the greater the compensation gain information. When the signal frame rate is the same, the higher the image high frequency level, the greater the gain compensation information.

[0105] For example, the high-frequency levels of an image may include: G1, G2, G3, G4, where the first high-frequency level of the image is G2, the second image level can be G1, the first image level can be G3, the second image level can be G2 or G1, and so on.

[0106] In this embodiment, the alternation pattern of fully highlighted rows and fully low-brightness rows in a solid color row can be checked. Assuming all rows are "fully highlighted rows" and / or "fully low-brightness rows", starting from the first row, it is checked whether the types of adjacent rows alternate.

[0107] For example, four high-frequency levels of the image can be defined. The high-frequency level G1 of the image corresponds to an alternating arrangement pattern of full-brightness rows and full-low-brightness rows. Table 1 is a schematic table of an alternating arrangement pattern of full-brightness rows and full-low-brightness rows provided in the embodiments of this application, as shown in Table 1:

[0108] The high-frequency level G2 of the image corresponds to an arrangement pattern in which two rows of full-brightness lines repeat, or two rows of full-low-brightness lines repeat. Table 2 is a schematic table of an arrangement pattern in which two rows of full-brightness lines repeat or two rows of full-low-brightness lines repeat, provided in the embodiments of this application, as shown in Table 2:

[0109] The high-frequency level G3 of the image corresponds to an arrangement pattern in which three rows of all bright lines repeat or three rows of all dark lines repeat. Table 3 is a schematic table of an arrangement pattern in which three rows of all bright lines repeat or three rows of all dark lines repeat, provided by an embodiment of this application. As shown in Table 3:

[0110] The image high-frequency level G4 corresponds to an arrangement pattern in which four rows of all bright lines repeat, or four rows of all dark lines repeat. Table 4 is a schematic table of an arrangement pattern in which four rows of all bright lines repeat, or four rows of all dark lines repeat, provided by an embodiment of this application. As shown in Table 4:

[0111] In this embodiment, the higher the frame rate, the more severe the coupling color cast phenomenon becomes. With high refresh rate signals, the pixel clock frequency is extremely high, and the data signal switches between "0" (low voltage) and "1" (high voltage) very quickly. This means the voltage difference is very large, leading to a sharp increase in coupling current and exacerbating the coupling color cast problem. If a preset frame rate threshold of 120Hz is defined, color cast is predicted to occur when the signal frame rate is ≥120Hz and the image high-frequency level is G1~G4. Based on the frame rate and image high-frequency level, compensation gain information is determined. Figure 6 This is a schematic diagram of a first mapping relationship provided in an embodiment of this application, as shown below. Figure 6 As shown, in Figure 6 In the middle, the compensation gain information in the direction of the arrow becomes larger and larger.

[0112] Based on the foregoing embodiments, this application provides a specific example. Figure 7 A flowchart illustrating a specific example of an image display method provided in this application embodiment is shown below. Figure 7 As shown, it includes: Step S701, Image preprocessing.

[0113] In this embodiment of the application, the preprocessing is to obtain the brightness, RGB pixel values ​​and signal frame rate.

[0114] Step S702: Determine whether the signal frame rate is greater than 120Hz.

[0115] In this embodiment of the application, if yes, step S703 is executed; if no, step S708 is executed.

[0116] Step S703: The image is processed into a binary image.

[0117] Step S704: Determine the scene type and the high frequency level.

[0118] Step S705: Does a high-frequency level exist between levels 1 and 4?

[0119] In this embodiment of the application, if no, step S610 is executed; if yes, step S606 is executed.

[0120] Step S706: Obtain compensation gain information based on the signal and high-frequency image level.

[0121] Step S707: Does the pixel simultaneously contain both a highlight component and a low-brightness component?

[0122] In this embodiment, if G is a high-brightness component and B is a low-brightness component, then G and B need to be compensated using the following formulas: G_out = GG × Gain × Gx; B_out = B + B × Gain × Gx; If R is a high-brightness pixel and B is a low-brightness component, then R and B need to be compensated using the following formulas: R_out = RR × Gain × Gx; B_out = B + B × Gain × Gx; If R is a high-brightness pixel, G is also a high-brightness pixel, and B is a low-brightness component, then G, R, and B all need to be compensated using the following formulas: R_out = RR × Gain × Gx; G_out = GG × Gain × Gx; B_out = B + B × Gain × Gx. If not, then step S708 is executed.

[0123] If not, proceed to step S708.

[0124] Step S708: Output the final RGB pixel values.

[0125] In some embodiments, the high brightness threshold, the low brightness threshold, the low difference threshold, and the high difference threshold are adaptively updated thresholds; The method further includes: collecting historical color cast sample data under different display frame rates, and iteratively updating the values ​​of each threshold based on the historical color cast sample data, so that each threshold is adapted to different display panel parameters and different frame rate conditions.

[0126] In some embodiments, traversing the binarized image using a sliding matrix includes: The sliding step size of the sliding matrix is ​​dynamically adjusted according to the current signal frame rate; the higher the signal frame rate, the smaller the sliding step size of the sliding matrix, and the lower the signal frame rate, the larger the sliding step size of the sliding matrix; the binarized image is traversed and detected region by region based on the dynamically adjusted sliding step size.

[0127] In some embodiments, traversing the binarized image using a sliding matrix includes: When the sliding matrix traverses to the edge region of the image and the matrix cannot fall completely within the image pixel range, edge pixel filling processing is performed on the missing pixels at the image edge. The filling method is to copy and fill the edge pixels. Based on the complete sliding matrix after filling, high-frequency scene recognition in the edge region is completed.

[0128] In some embodiments, after correcting the original RGB pixel values ​​of the pixels in the target pixel matrix based on the compensation gain information, the method further includes: Obtain the compensation gain information of the current frame pixel and the historical compensation gain information of the corresponding pixel in the previous adjacent frame, and calculate the inter-frame gain difference; if the inter-frame gain difference is greater than the preset gain jump threshold, then perform smoothing constraint processing on the compensation gain of the current frame to suppress the sudden change in compensation intensity between consecutive frames, and output the smoothed corrected RGB pixel value for image display.

[0129] In some embodiments, when correcting the original RGB pixel values ​​of pixels in the target pixel matrix, a preset saturation protection threshold is set; Obtain the color saturation of the target pixel before correction. When the original color saturation of the pixel is less than the saturation protection threshold, turn off the dynamic compensation coefficient correction logic and only use a fixed base gain for light correction to preserve the original color texture of the low-saturation image and avoid color distortion, color bleeding, and grayscale shift in light-colored images.

[0130] In some embodiments, the method further includes constructing a high-frequency scene compensation mask; A binary compensation mask is generated based on the identified target pixel matrix. RGB correction is performed only on the high-frequency areas covered by the mask, while the original RGB pixel values ​​remain unchanged for the ordinary display areas outside the mask. This achieves precise local compensation and eliminates color interference in the normal picture caused by global compensation.

[0131] In some embodiments, the first mapping relationship is also associated with panel temperature parameters; The operating temperature of the display panel is collected in real time. The panel temperature, image high frequency level, and signal frame rate are used to construct a three-dimensional first mapping relationship. The higher the temperature, the more severe the color cast due to coupling crosstalk. The larger the matching compensation gain information, the more adaptive enhancement of color cast compensation under high temperature conditions is achieved.

[0132] In some embodiments, the method further includes a preset maximum gain limiting threshold; During the process of correcting RGB pixel values ​​based on compensation coefficients and compensation gain information, it is determined in real time whether the current correction gain exceeds the maximum gain limit threshold. If it does, the correction gain is forcibly constrained to the maximum gain limit threshold to prevent color banding, image whitening, and pixel distortion caused by excessive compensation in extreme high-frequency scenarios.

[0133] Figure 8 This is a schematic diagram of the structure of a display device provided in an embodiment of this application. Figure 8 As shown, the display device 300 of this embodiment may include: at least one processor 30 ( Figure 8 Only one processor 30, memory 31, and computer program 32 stored in memory 31 and executable on at least one processor 30 are shown. When the processor 30 executes the computer program 32, it implements the steps in any of the above method embodiments, or the processor 30 executes the computer program 32 to implement the functions of each module / unit in the above device or system embodiments.

[0134] For example, computer program 32 may be divided into one or more modules / units, one or more of which are stored in memory 31 and executed by processor 30 to complete this application. One or more modules / units may be a series of computer program 32 instruction segments capable of performing a specific function, which describe the execution process of computer program 32 in display device 300.

[0135] This application also provides a computer-readable storage medium storing a computer program 32, which, when executed by a processor 30, implements the steps described in the above-described method embodiments.

[0136] This application provides a computer program product that, when run on a display device, enables the display device to implement the steps described in the various method embodiments above.

[0137] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program 32 instructing related hardware. The computer program 32 can be stored in a computer-readable storage medium, and when executed by the processor 30, it can implement the steps of the various method embodiments described above. The computer program 32 includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium can include at least: any entity or device capable of carrying computer program code to a terminal, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0138] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0139] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0140] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0141] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0142] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An image display method, characterized in that, include: Obtain the brightness value, original RGB pixel value, and signal frame rate of the pixels in the image to be displayed; When the signal frame rate is greater than a preset frame rate threshold, the brightness values ​​of the pixels in the image to be displayed are binarized according to the brightness value and the brightness threshold to obtain a binarized image. The binary image is traversed using a sliding matrix. Based on the binary brightness values ​​of the pixels in each sliding matrix, it is determined whether each pixel matrix is ​​a high-frequency scene of the image. In the case that the pixel matrix is ​​a high-frequency scene of the image, all pixel rows in the pixel matrix are solid color rows. When the target pixel matrix is ​​a high-frequency scene of the image, the high-frequency level of the image high-frequency scene is obtained based on the arrangement pattern of the solid color rows in the target pixel matrix; Based on the image high frequency level, the signal frame rate, and the pre-established first mapping relationship, the compensation gain information corresponding to the target pixel matrix is ​​obtained, wherein the first mapping relationship includes the correspondence between the image high frequency level, the signal frame rate, and the compensation gain information; The original RGB pixel values ​​of the pixels in the target pixel matrix are corrected based on the compensation gain information, so that the image is displayed based on the corrected RGB pixel values.

2. The method according to claim 1, characterized in that, The step of correcting the original RGB pixel values ​​of pixels in the target pixel matrix based on the compensation gain information includes: The color component values ​​of the RGB pixel values ​​of each pixel in the target pixel matrix are compared with a preset high-brightness pixel threshold and a preset low-brightness pixel threshold to obtain a comparison result, wherein the high-brightness pixel threshold is greater than the low-brightness pixel threshold. Based on the comparison results, it is determined whether each pixel simultaneously has a bright component and a low component, wherein the bright component is defined as a color component value greater than the bright pixel threshold, and the low component is defined as a color component value less than the low pixel threshold. When a target pixel has both high-brightness and low-brightness components, the RGB pixel value of the target pixel is corrected based on the compensation gain information.

3. The method according to claim 2, characterized in that, The step of correcting the RGB pixel values ​​of the target pixel based on the compensation gain information includes: Calculate the pixel difference between the highlight component and the low brightness component in the target pixel; Calculate the compensation coefficient corresponding to the target pixel based on the pixel difference; The high-brightness component is attenuated based on the compensation coefficient and compensation gain information, and the low-brightness component is compensated to correct the RGB pixel value of the target pixel.

4. The method according to claim 3, characterized in that, The step of calculating the compensation coefficient corresponding to the target pixel based on the pixel difference includes: When the pixel difference is less than the low threshold of the difference, the preset basic low gain coefficient is determined as the compensation coefficient; When the pixel difference is greater than or equal to the low difference threshold and less than or equal to the high difference threshold, the compensation coefficient is calculated based on the low difference threshold, the high difference threshold, the basic low gain coefficient, the preset basic high gain coefficient, and the brightness difference. If the pixel difference is greater than the high threshold of the difference, the basic high gain coefficient is determined as the compensation coefficient.

5. The method according to claim 4, characterized in that, The calculation of the compensation coefficient based on the low threshold of the difference, the high threshold of the difference, the basic low gain coefficient, the preset basic high gain coefficient, and the brightness difference includes: Calculate a first difference between the brightness difference and the low threshold of the difference; calculate a second difference between the base high gain coefficient and the base low gain coefficient; and calculate a third difference between the high threshold of the difference and the low threshold of the difference. Divide the second difference by the third difference to obtain the difference ratio, and multiply the difference ratio by the first difference to obtain the increase in the compensation coefficient; The compensation coefficient is obtained by adding the increase in the compensation coefficient to the basic low gain coefficient.

6. The method according to claim 3, characterized in that, The attenuation of the high-brightness component and the compensation of the low-brightness component based on the compensation coefficient and compensation gain information include: The attenuation amount is obtained by multiplying the highlight component, the compensation coefficient, and the compensation gain information, and the attenuation amount is subtracted from the highlight component to obtain the pixel value of the attenuated highlight component. The low-brightness component, the compensation coefficient, and the compensation gain information are multiplied together to obtain the uplift amount. The uplift amount is then added to the low-brightness component to obtain the pixel value of the compensated low-brightness component.

7. The method according to any one of claims 1 to 6, characterized in that, The brightness threshold includes a high brightness threshold and a low brightness threshold, wherein the high brightness threshold is greater than the low brightness threshold. The step of binarizing the brightness values ​​of pixels in the image to be displayed based on the brightness value and the brightness threshold to obtain a binarized image includes: Set the brightness value of pixels whose brightness value is greater than the high brightness threshold to 1; The brightness values ​​of pixels with brightness values ​​less than the low brightness threshold are set to 0 to perform binarization processing on the brightness values ​​of pixels in the image to be displayed.

8. The method according to claim 1, characterized in that, The process of obtaining the image high-frequency level of the high-frequency scene based on the arrangement pattern of solid color rows in the target pixel matrix includes: The arrangement pattern of solid color rows in the target pixel matrix is ​​matched with a pre-established second mapping relationship to obtain the high-frequency level of the image corresponding to the target pixel matrix. The second mapping relationship includes the correspondence between the arrangement pattern of solid color rows and the high-frequency level of the image.

9. The method according to claim 8, characterized in that, The image high frequency level includes: a first image high frequency level and a second image high frequency level. The first image high frequency level is higher than the second image high frequency level. The number of consecutive solid color rows corresponding to the first image high frequency level is greater than the number of consecutive solid color rows corresponding to the second image high frequency level. In the first mapping relationship, when the image high frequency level is the same, the higher the signal frame rate, the greater the compensation gain information. When the signal frame rate is the same, the higher the image high frequency level, the greater the gain compensation information.

10. A display device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

Images