Liquid crystal display gray scale control method based on self-adaptive brightness compensation

Abstract

The invention discloses a liquid crystal display screen gray scale control method based on adaptive brightness compensation, which relates to the technical field of liquid crystal display screen control, and comprises the following steps: collecting environmental spectrum distribution information and a pixel gray scale voltage response curve of a liquid crystal display screen in real time, and carrying out fusion processing to form a time sequence joint feature vector; through multi-mode synchronous sampling and time sequence joint feature vector generation, ambient light and screen content changes are accurately captured, target adjustment values of backlight power and gray scale voltage are dynamically predicted, and response lag and overshoot are avoided. Through spectral domain balancing and a self-adaptive damping scheduling mechanism, cooperative control of backlight and gray scale is optimized, high-frequency oscillation is suppressed, and linear response of a low-frequency band is ensured. Meanwhile, Gamma mapping and global color gamut calibration are dynamically refreshed, accurate adjustment of area-level brightness and gray scale is achieved, and continuity of the display effect and visual experience of a user are improved.

Description

Technical Field

[0001] This invention relates to the field of liquid crystal display control technology, and more specifically to a method for controlling the grayscale of a liquid crystal display based on adaptive brightness compensation. Background Technology

[0002] Adaptive brightness compensation-based grayscale control of LCD screens refers to dynamically sensing changes in ambient light brightness or screen content and adjusting the backlight intensity and pixel grayscale voltage in real time to ensure accurate grayscale reproduction and visual consistency under different brightness conditions. Its working principle is as follows: First, a light sensor or content analysis detects the current ambient light or overall image brightness and generates a brightness compensation factor. Then, based on this brightness compensation factor, the backlight brightness is dynamically adjusted to prevent insufficient grayscale contrast or color distortion due to excessively bright or dark environments. Simultaneously, fine compensation is applied to the grayscale driving voltage of the LCD pixels to ensure that the grayscale level remains linearly responsive under different brightness levels, avoiding color shift or loss of detail. This mechanism, through dual compensation of backlight adjustment and grayscale voltage, balances screen energy consumption and image quality, achieving more accurate grayscale reproduction and a more comfortable visual experience.

[0003] The existing technology has the following shortcomings: Existing LCD displays suffer from nonlinear coupling issues in adaptive brightness compensation based on a combination of ambient light and screen content. Specifically, when the compensation algorithm dynamically adjusts backlight brightness, excessively rapid adjustments or large compensation magnitudes can lead to lag or overshoot in the corresponding grayscale driving voltage adjustment, resulting in a closed-loop positive feedback effect between brightness and grayscale control. This effect further induces frequent flickering or grayscale jumps in certain areas of the screen, potentially causing visual fatigue, dizziness, and even image misinterpretation in medical imaging and precision recognition scenarios. Furthermore, abnormal oscillations in the grayscale voltage can cause the panel driving circuit to operate under unsteady high-voltage excitation for extended periods, posing a risk of voltage overload and component damage, thus affecting the display's lifespan and reliability.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a grayscale control method for liquid crystal displays based on adaptive brightness compensation. By employing multimodal synchronous sampling and temporal joint feature vector generation, it accurately captures changes in ambient light and screen content, dynamically predicts target adjustment values ​​for backlight power and grayscale voltage, and avoids response lag and overshoot. Through spectral domain balancing and adaptive damping scheduling mechanisms, it optimizes the coordinated control of backlight and grayscale, suppresses high-frequency oscillations, and ensures linear response in the low-frequency band. This scheme effectively avoids the positive feedback effect between brightness and grayscale, reduces flicker and grayscale jumps, and improves display stability. Simultaneously, dynamic refresh of Gamma mapping and global color gamut calibration achieve precise adjustment of brightness and grayscale at the regional level, improving the continuity of display effects and the user's visual experience, thereby solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a grayscale control method for a liquid crystal display screen based on adaptive brightness compensation, comprising the following steps: A multimodal synchronous sampling model is constructed to collect environmental spectral distribution information and pixel grayscale voltage response curves of the LCD screen in real time. The collected data is then fused to form a temporal joint feature vector, which serves as high-dimensional input data for dynamic regulation. Based on the temporal joint feature vector, a feedforward recursive prediction model is trained to dynamically predict the target adjustment values ​​of the backlight power and pixel grayscale voltage of the LCD screen in the next frame. A bidirectional gating delay mechanism is introduced in the prediction process to perform temporal correction on the predicted target adjustment values ​​in order to compensate for the response lag effect. Based on the time-corrected target adjustment value, a collaborative control matrix for brightness power and grayscale voltage is constructed. The spectral domain balancing method is used to couple the rate of change of backlight power and the gain function of grayscale voltage based on frequency domain characteristics, so as to suppress the positive feedback effect caused by the nonlinear coupling between brightness power and grayscale voltage. Based on the cooperative control matrix, an adaptive damping scheduling mechanism is applied to adjust the eigenvalues ​​and spectral amplitude of the cooperative control matrix in real time to weaken the high-frequency oscillation tendency and ensure the linear response characteristics of gray-level voltage in the low-frequency band. Based on the output of the adaptive damping scheduling mechanism, the Gamma mapping lookup table is dynamically refreshed to continuously optimize the continuity of photoelectric conversion mapping of the LCD screen and to perform global calibration on the pixel color gamut consistency of the screen. The results after global photoelectric conversion mapping and color gamut calibration are mapped to multiple zones of the LCD screen. The brightness power and grayscale voltage of each zone are independently adjusted, and the coupling tensor between the zones is constructed. Based on the difference in brightness gradient and grayscale curvature at the boundaries of each zone, the coupling strength of the zones is dynamically adjusted to achieve stable control and smooth transition of brightness and grayscale at the zone level.

[0007] Preferably, the training of feedforward recursive prediction models includes: A time-series joint feature vector is loaded at the input end. The feature vector is generated based on changes in ambient light and screen content, reflecting the dynamic characteristics of the LCD screen in real time. At the output end, the target adjustment values ​​of backlight power and grayscale voltage are predicted by regression method. The prediction model combines feedforward neural network and recurrent neural network, which are responsible for modeling nonlinear relationship and time-dependent characteristics, respectively. By using multiple batches of training samples, the model parameters are optimized to enable it to adapt to different lighting environments and content changes, thus possessing strong generalization ability.

[0008] Preferably, the bidirectional gating delay mechanism includes: A forward gating unit is used to adjust the response to recent dynamic changes in the predicted path; The inverse gating unit is used to review the regulatory behavior of historical sequences and provide cumulative effects. The two work together to dynamically compensate for response lag in the predicted output. The gating mechanism uses a time-step adaptive adjustment strategy to adjust the gating delay depth and width in real time according to the rate of change of ambient light and screen content, ensuring that the compensation process can flexibly adapt to different changing scenarios and ultimately generate accurate predicted adjustment values.

[0009] Preferably, the method for constructing the collaborative control matrix includes: Based on the time-corrected backlight power and grayscale voltage target adjustment values, a two-parameter control space for brightness power and grayscale voltage is defined, and a cooperative control matrix is ​​constructed. The spectral domain balancing method is adopted to map the backlight power change rate and grayscale voltage gain in the time domain to the frequency domain through Fourier transform, analyze and correct the difference in their frequency response, and ensure their coordinated balance in each frequency band. Based on the frequency domain optimized cooperative control matrix, a nonlinear coupling compensation unit is applied, and a bivariate cubic interpolation model is used to correct the nonlinear gain effect in the matrix, thus maintaining the linearization trend of the regulation behavior. A positive feedback suppression mechanism is introduced. By monitoring the matrix eigenvalues ​​and spectral energy distribution, the feedback attenuation strategy is dynamically adjusted to suppress the positive feedback effect that may be triggered.

[0010] Preferably, the adaptive damping scheduling mechanism includes: By extracting the eigenvalues ​​and spectral amplitude of the cooperative control matrix, the dynamic stability and frequency resonance risk of the matrix are evaluated. Based on the analysis of eigenvalue change rate and high-frequency energy in the spectral domain, an adaptive damping scheduling model is constructed, which dynamically adjusts the damping coefficient according to the amplitude and change rate of matrix eigenvalues ​​and high-frequency energy density. Attenuation weights are applied in the high-frequency oscillation region, while linear response of grayscale voltage is ensured in the low-frequency oscillation region to maintain consistency between voltage and backlight power adjustment.

[0011] Preferably, the real-time damping coefficient calculation method further includes: The amplitude spectrum of the cooperative control matrix in the frequency domain is extracted by Fourier transform, with a focus on analyzing the energy accumulation rate in the high-frequency band. The rate of change of eigenvalues ​​and high-frequency energy density are input into the response function of the damping scheduling model, and the real-time damping coefficient is calculated through a preset nonlinear mapping relationship.

[0012] Preferred methods for gamma mapping refresh and color gamut calibration include: Based on the cooperative control matrix output by the adaptive damping scheduling mechanism, photoelectric conversion data after backlight power and grayscale voltage adjustment are collected in real time, and a multidimensional photoelectric response dataset is generated. Based on photoelectric response data, a Gamma mapping model is dynamically constructed and the Gamma mapping lookup table is updated by nonlinear curve fitting to ensure a smooth transition between low and high gray levels. Based on the updated Gamma mapping results, a multi-channel color sensor was used to collect full-screen RGB color coordinates and brightness values, perform color gamut consistency calibration, and resolve color shift caused by differences in regional damping adjustment. Through periodic self-checking and dynamic feedback mechanisms, the photoelectric conversion mapping and color gamut output are continuously optimized to ensure the consistency of color and brightness of the LCD screen under different lighting and content changes.

[0013] Preferably, the zonal adjustment method includes: Based on the dataset after global photoelectric conversion mapping and color gamut calibration, the display area of ​​the liquid crystal display screen is divided into multiple independent zones, and dynamic adjustment of brightness power and grayscale voltage is performed in each zone. By collecting local photoelectric response data of each zone in real time, the backlight power adjustment range and grayscale voltage compensation value of the zone are dynamically adjusted to ensure that the brightness and grayscale response of the zone are in the optimal state. Construct coupling tensors between regions, generate coupling weight coefficients by analyzing the differences in brightness gradient and grayscale curvature, and dynamically adjust the coupling strength according to changes in image content and ambient light. Based on dynamically adjusted coupling weights, the zonal adjustment commands are fine-tuned to ensure continuous and smooth brightness and grayscale curves between zones, achieving stable control and delicate transitions of brightness and grayscale at the regional level.

[0014] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention accurately captures changes in ambient light and screen content through multimodal synchronous sampling and temporal joint feature vector generation, dynamically predicting target adjustment values ​​for backlight power and grayscale voltage, thus avoiding response lag and overshoot effects. Simultaneously, through spectral domain balancing and adaptive damping scheduling mechanisms, the coordinated control between backlight power and grayscale voltage is further optimized, suppressing high-frequency oscillations and ensuring linear response in the low-frequency band. This scheme effectively avoids the positive feedback effect between brightness and grayscale, reducing screen flicker and grayscale jumps, and improving the stability and continuity of the display effect. Furthermore, the dynamic refresh of the Gamma mapping lookup table and global color gamut calibration enable more precise brightness and grayscale adjustment between different zones of the display, ultimately achieving stable regional-level brightness and grayscale control, as well as a more natural and delicate visual transition, significantly improving the user's visual experience and the long-term reliability of the display. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0016] Figure 1 This is a flowchart of the grayscale control method for a liquid crystal display screen based on adaptive brightness compensation according to the present invention. Detailed Implementation

[0017] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0018] This invention provides, for example Figure 1 The grayscale control method for a liquid crystal display screen based on adaptive brightness compensation, as shown, includes the following steps: A multimodal synchronous sampling model is constructed to collect environmental spectral distribution information and pixel grayscale voltage response curves of the LCD screen in real time. The collected data is then fused to form a temporal joint feature vector, which serves as high-dimensional input data for dynamic regulation. In this embodiment: First, based on the physical characteristics of the liquid crystal display and the requirements of the usage scenario, multiple sets of environmental optical sensing devices and liquid crystal panel electrical acquisition devices are configured. The environmental optical sensing devices are used for real-time measurement of light intensity, color temperature, and spectral distribution across the entire spectrum, ensuring coverage of ultraviolet, visible, and near-infrared bands to comprehensively reflect the spectral characteristics of the external lighting environment. Simultaneously, the liquid crystal panel electrical acquisition devices accurately capture the optical response of the liquid crystal material under different voltage driving conditions by real-time acquisition of the grayscale voltage of each pixel or pixel array, especially recording the nonlinear relationship between voltage and brightness, contrast, and response time. This configuration ensures holographic perception of ambient light and electrical responses, laying the foundation for subsequent data fusion.

[0019] After completing the real-time acquisition of the aforementioned optical and electrical data, the acquired environmental spectral distribution data and grayscale voltage response data are time-synchronized, aligned, and spatially mapped. Specifically, a high-precision timestamp mechanism ensures a one-to-one correspondence between the ambient light information acquired at the same moment and the grayscale voltage data of the liquid crystal pixels. Simultaneously, a spatial mapping algorithm is used to correlate the spatial location of the illumination distribution and grayscale response of different areas of the liquid crystal panel under external lighting conditions, forming a precise photoelectric spatial correlation. This process compensates for data inconsistencies caused by differences in the distribution or resolution of sensing devices through multi-dimensional data interpolation and spatial weighting, ensuring the integrity and consistency of the data foundation before fusion.

[0020] Then, based on the dataset after time synchronization and spatial mapping, a multimodal feature fusion algorithm is executed, employing a dual strategy of feature-level fusion and decision-level fusion. Feature-level fusion extracts composite features that can jointly characterize brightness, contrast, and color stability by cross-analyzing the optical response characteristics corresponding to characteristic bands, intensity gradients, and grayscale voltages in the spectral distribution. Decision-level fusion, on the other hand, further introduces a dynamic weight adjustment mechanism based on feature fusion. According to the rate of dynamic change of ambient light and the sensitivity of grayscale response, it adjusts the weight ratio of various features in the fusion vector in real time, so that the fusion result not only reflects the static photoelectric relationship but also has the ability to respond to dynamic changes, forming a fusion feature set that is highly adaptable to changing environments.

[0021] Finally, based on the aforementioned fused feature set, the continuous fused features are vectorized in chronological order to construct a temporal joint feature vector, which serves as a high-dimensional input for subsequent dynamic regulation. This temporal joint feature vector not only includes optical information such as spectral intensity, wavelength distribution, and color temperature parameters, but also integrates electrical and behavioral features such as grayscale voltage, electro-optic response sensitivity, and historical adjustment states. Regularization and normalization processes ensure scale uniformity and computational stability among the features.

[0022] This process enables the full perception, deep fusion, and high-precision construction of dynamic inputs of environmental spectra and grayscale voltages, significantly improving the input quality of subsequent control models and the accuracy of predictive control.

[0023] Based on the temporal joint feature vector, a feedforward recursive prediction model is trained to dynamically predict the target adjustment values ​​of the backlight power and pixel grayscale voltage of the LCD screen in the next frame. A bidirectional gating delay mechanism is introduced in the prediction process to perform temporal correction on the predicted target adjustment values ​​in order to compensate for the response lag effect. Based on the aforementioned constructed temporal joint feature vector, a prediction model integrating feedforward and recursive structures was designed and trained. Structurally, this model combines the strong fitting ability of feedforward neural networks for nonlinear mappings with the dynamic capture ability of recursive neural networks on time-series data, thereby achieving dual modeling of the nonlinear and temporal dependence characteristics between backlight power and pixel grayscale voltage. During training, the input continuously loads temporal joint feature vectors from different time periods, and the output simultaneously regresses and predicts the target values ​​of backlight power and corresponding pixel grayscale voltage at the corresponding time points. Guided by training samples from multiple batches and scenarios, the model can gradually learn the adjustment rules and trends of backlight and grayscale voltage under different lighting environments and content changes, forming a stable and highly generalizable prediction capability.

[0024] After completing the basic training of the prediction model, a bidirectional gating delay mechanism is further introduced to address the potential response lag issue in the predicted output. This mechanism introduces forward and reverse time gating units simultaneously during the prediction phase. Forward gating adjusts the response to recent dynamic changes in the prediction path, while reverse gating reviews the cumulative impact of historical sequences on the current adjustment behavior. The combined effect of these two mechanisms effectively compensates for lag factors dynamically. Furthermore, the gating mechanism incorporates an adaptive time step adjustment strategy, adjusting the depth and width of the gating delay in real time based on the dynamic changes in ambient light and screen content. This allows the correction process to flexibly adapt to different changing scenarios, ensuring that the predicted output closely matches actual control requirements.

[0025] Subsequently, based on the prediction results obtained after introducing a bidirectional gating delay mechanism, a time-series correction operation is performed. This operation uses historical predicted values ​​and actual acquired backlight power and grayscale voltage adjustment values ​​as reference baselines, and employs a weighted residual feedback method to gradually correct the error range of the current predicted value. During the correction process, the time difference between the prediction time and the sampling time is further considered, and the residual weights are dynamically adjusted to ensure that the correction magnitude is neither too extreme nor too gradual, avoiding the introduction of new response oscillations or adjustment lags. Through multiple rounds of iterative correction, not only is the accumulation of prediction errors effectively suppressed, but the stability and accuracy of the model in continuous prediction processes are also improved.

[0026] Based on the predicted target value after timing correction, a final adjustment command is generated to adapt the backlight power and grayscale voltage of the LCD screen for the next frame. To further enhance the stability and continuity of the predictive adjustment, a smoothing factor and a dynamic adjustment threshold are embedded in the command sequence to ensure that the command change curve remains smooth during multi-frame continuous adjustment, avoiding drastic jumps in backlight power or grayscale voltage caused by prediction differences.

[0027] Through the above processing, not only was dynamic prediction and high-precision timing correction of the target adjustment values ​​of backlight power and grayscale voltage achieved, but the problems of unstable adjustment and visual discomfort caused by prediction lag were also effectively solved, laying a solid foundation for subsequent collaborative control.

[0028] Based on the time-corrected target adjustment value, a collaborative control matrix for brightness power and grayscale voltage is constructed. The spectral domain balancing method is used to couple the rate of change of backlight power and the gain function of grayscale voltage based on frequency domain characteristics, so as to suppress the positive feedback effect caused by the nonlinear coupling between brightness power and grayscale voltage. In this implementation: First, based on the target adjustment values ​​of backlight power and pixel grayscale voltage after time-corrected adjustment, a two-parameter control space for brightness power and grayscale voltage is defined, and a collaborative control matrix is ​​constructed on this basis. This collaborative control matrix uses a dynamic mapping method to establish a mathematical relationship between the rate of change of backlight power and the adjustment amplitude of grayscale voltage. The row vectors of the matrix represent the rate of change of backlight power in a continuous frame sequence, while the column vectors correspond to the dynamic response gain of grayscale voltage in the corresponding frame sequence. Through the construction of the matrix, parallel modeling and coupling of backlight and grayscale voltage adjustment behaviors can be achieved, ensuring that their dynamic relationship no longer evolves in isolation. To improve the adaptability of collaborative control, the matrix elements adopt an adaptive weighting strategy, dynamically adjusting the weight distribution based on historical adjustment accuracy and current change trends. This allows the control matrix to flexibly adapt to different environmental and content changes, improving the robustness and sensitivity of the control.

[0029] After establishing the cooperative control matrix, a spectral domain balancing method was used to uniformly adjust the frequency domain characteristics of the backlight power change rate and the gray-scale voltage gain function, addressing the frequency response differences between them. Specifically, a Fourier transform was first applied to each parameter sequence in the cooperative control matrix to map the backlight power change rate sequence and the gray-scale voltage gain sequence in the time domain to the frequency domain, obtaining their respective spectral distributions. By comparing and analyzing their energy distributions in the low, mid, and high frequency bands, potential frequency domain mismatch regions were identified, with particular attention paid to the over-amplitude response of the gray-scale voltage gain in the high frequency band and the delayed response of the backlight power change in the low frequency band. Based on the spectral characteristics, amplitude limiting and phase correction were further applied to the gray-scale voltage gain in the frequency domain, while corresponding gain compensation and phase guidance were applied to the backlight power change rate, ensuring that the response amplitude and phase relationship of the two reached a cooperative balance in each frequency band. Through spectral domain balancing, the dynamic response deviation caused by the difference in their frequency domain characteristics was effectively suppressed, laying the foundation for subsequent stable control.

[0030] After frequency domain balancing, the frequency domain characteristics are back-mapped to the time domain to form a frequency-optimized collaborative control matrix. This matrix not only possesses temporal synchronization but also achieves high coordination in the amplitude and phase of the dynamic response. Furthermore, a nonlinear coupling compensation unit is introduced to address potential nonlinear gain effects in the control matrix. A nonlinear correction model based on bivariate cubic interpolation is established to dynamically adjust and correct parameters exhibiting nonlinear growth or decay trends, ensuring that the adjustment behavior of backlight power and grayscale voltage maintains a linear trend across the entire dynamic range. This compensation is effective not only in forward adjustment but also in reverse adjustment (such as brightness reduction or dark field enhancement), comprehensively guaranteeing the linear response characteristics of the control matrix.

[0031] Finally, based on the nonlinearly compensated cooperative control matrix, a positive feedback suppression mechanism is further established. This mechanism monitors the determinant change trend and spectral energy distribution of the control matrix in real time. When an abnormal amplification trend of matrix eigenvalues ​​or spectral energy is detected in a specific frequency band, a feedback attenuation strategy is immediately activated to dynamically reduce the backlight power change rate and grayscale voltage gain value corresponding to that frequency band, preventing the two from forming a positive feedback loop under specific conditions. In addition, a dynamic damping factor is introduced into the positive feedback suppression mechanism, adjusting the damping coefficient in real time according to the dynamic changes of the matrix spectrum, enhancing the ability to quickly suppress potential oscillations or response instability.

[0032] By implementing this step, deep coordination and stable control of brightness power and grayscale voltage are achieved in the fully dynamic adjustment process, completely suppressing the positive feedback risk caused by nonlinear coupling, and improving the grayscale reproduction accuracy and visual stability of the LCD screen under complex ambient lighting and changing screen content.

[0033] Based on the cooperative control matrix, an adaptive damping scheduling mechanism is applied to adjust the eigenvalues ​​and spectral amplitude of the cooperative control matrix in real time to weaken the high-frequency oscillation tendency and ensure the linear response characteristics of gray-level voltage in the low-frequency band. Based on the aforementioned cooperative control matrix after frequency domain balancing and nonlinear compensation correction, eigenvalues ​​and spectral amplitude distributions of the matrix are extracted as input parameters for adaptive damping scheduling. Eigenvalue extraction, using eigenvalue decomposition, accurately reflects the dominant direction of the matrix's response and the concentration of dynamic amplitude at different time series. Simultaneously, for the spectral amplitude of the cooperative control matrix, multi-scale discrete Fourier transform is applied to decompose the amplitude spectra of low-frequency, mid-frequency, and high-frequency segments, accurately assessing the energy distribution of the current matrix in different frequency ranges. Through joint sensing of eigenvalues ​​and spectral amplitudes, a comprehensive understanding of the dynamic stability of the cooperative control matrix and potential frequency resonance risks can be achieved, providing data support for subsequent damping scheduling.

[0034] Secondly, an adaptive damping scheduling model is constructed based on the extracted eigenvalues ​​and spectral amplitude of the collaborative control matrix. This model introduces a dynamic scheduling factor, dynamically adjusting the strength and distribution of the damping coefficient according to the absolute amplitude and rate of change of the matrix eigenvalues, as well as the energy accumulation rate in the high-frequency band of the spectral domain. Specifically, when the matrix eigenvalues ​​change drastically or the high-frequency energy in the spectral domain rises rapidly, the damping scheduling model activates a high-intensity damping coefficient, applying attenuation weights to the high-frequency components to suppress oscillation amplitude; while when the low-frequency characteristics exhibit a stable and continuous linear response, the damping coefficient gradually weakens to ensure that the sensitivity and response speed of grayscale voltage adjustment are not suppressed. The model also integrates the rate parameter of dynamic changes in ambient light and the frequency of screen content changes as supplementary scheduling criteria, achieving context-aware and adaptive optimization of damping scheduling, ensuring a balance between oscillation suppression and response efficiency in different scenarios.

[0035] Subsequently, based on the real-time damping coefficient calculated by the damping scheduling model, dynamic adjustment of the eigenvalues ​​and spectral amplitude of the cooperative control matrix is ​​performed. During the adjustment process, the damping coefficient is directly applied to the frequency domain mapping of the cooperative control matrix, an exponential decay function is applied to the high-frequency amplitude, and an adaptive smoothing operation is applied to the rate of change of the matrix eigenvalues ​​to prevent drastic fluctuations in the matrix response due to transient disturbances. For the low-frequency adjustment of grayscale voltage, a linear gain preservation mechanism is specifically set up to ensure that the amplitude and phase relationship of the low-frequency response are not weakened under the damping scheduling, maintaining the linear consistency of voltage and backlight power coordinated adjustment. In addition, the feedback effect of damping adjustment is monitored in real time during the dynamic adjustment process. Through rapid iterative calculation and residual evaluation, the damping coefficient is continuously optimized to avoid adjustment delay or insufficient response due to over-damping.

[0036] The real-time damping coefficient of the damping scheduling model is obtained through joint dynamic analysis of the eigenvalue change rate of the cooperative control matrix and the high-frequency energy density in the spectral domain. Specifically, the method is as follows: First, within each time period, the cooperative control matrix is ​​decomposed into eigenvalues, and the absolute amplitude of the eigenvalues ​​and their change rates in adjacent periods are calculated to reflect the dynamic intensity of the system response. Second, the amplitude spectrum of the cooperative control matrix in the frequency domain is extracted using Fourier transform, with a focus on monitoring the energy accumulation rate and energy proportion in the high-frequency range. Subsequently, the eigenvalue change rate and high-frequency energy density are input into the response function of the damping scheduling model. This function, based on a preset nonlinear mapping relationship and combined with historical adjustment residuals and the ambient light change rate, calculates the damping coefficient adapted to the current dynamic state. Finally, the real-time damping coefficient is adaptively adjusted according to the current dynamic instability of the matrix; a higher coefficient value indicates a stronger damping effect, while a lower value preserves response sensitivity, ensuring an optimal balance between stability and responsiveness.

[0037] Finally, the collaborative control matrix, adjusted by the adaptive damping scheduling mechanism, forms a dynamic control foundation with stability, linear response, and anti-oscillation capability. Based on the backlight power and grayscale voltage adjustment commands output by this matrix, these are further incorporated into subsequent Gamma mapping refresh and color gamut calibration processes, ensuring the stability and continuity of the dynamic response throughout the entire adjustment process. This further guarantees the durability of the damping scheduling effect.

[0038] By fully implementing the above steps, not only is the tendency of high-frequency oscillation in the collaborative control process effectively reduced, but the stable linear response of the grayscale voltage of the LCD screen in the low-frequency band is also ensured, greatly improving the smoothness and visual comfort of the overall display effect, while extending the reliable working cycle of the panel driver.

[0039] Based on the output of the adaptive damping scheduling mechanism, the Gamma mapping lookup table is dynamically refreshed to continuously optimize the continuity of photoelectric conversion mapping of the LCD screen and to perform global calibration on the pixel color gamut consistency of the screen. The cooperative control matrix, output by the adaptive damping scheduling mechanism, is weakened by high-frequency oscillations and ensured by low-frequency linear response. Real-time photoelectric conversion data is then acquired after adjusting backlight power and pixel grayscale voltage. This data includes key optical indicators such as brightness response, contrast change, and color saturation for each pixel under the current backlight power and grayscale voltage. To ensure comprehensiveness and accuracy, the acquisition process combines dynamic partition sampling with pixel-level fine-tuning detection. This not only monitors the overall photoelectric characteristics of the entire screen in real time but also meticulously captures the response differences in local areas and boundary transition zones. This process generates a multi-dimensional response dataset reflecting the comprehensive photoelectric performance of the entire screen and local areas, providing real and dynamic photoelectric foundational data for refreshing the Gamma mapping lookup table.

[0040] Secondly, based on the collected multidimensional photoelectric response data, a fitting curve for the Gamma mapping model is dynamically constructed, and the Gamma mapping lookup table is updated accordingly. Specifically, by fitting the nonlinear relationship between the grayscale voltage and the corresponding brightness response at each level, a set of Gamma curves is generated that are dynamically updated in real time as ambient light changes, backlight power adjustment, and damping scheduling change. During the fitting process, a combination of piecewise progressive interpolation and polynomial fitting is used to ensure both delicate representation in the low grayscale range and smooth transition in the high grayscale range. Simultaneously, slight adjustments are made to the voltage response affected by damping scheduling to avoid continuity discontinuities in the Gamma mapping caused by dynamic compensation. The updated Gamma mapping lookup table is loaded into the display control path in real time, ensuring that each frame of the image, after grayscale voltage and backlight power adjustment, can achieve accurate brightness and grayscale reproduction through optimal Gamma mapping, significantly improving the sense of layering and realism of the display effect.

[0041] After dynamically refreshing the Gamma mapping lookup table, a global calibration of the pixel color gamut consistency of the LCD screen is performed based on the photoelectric conversion characteristics after mapping. This calibration uses the refreshed Gamma mapping result as the calibration baseline, combined with real-time full-screen RGB color coordinates and brightness values ​​collected by multi-channel color sensors. Color gamut matching and color balance algorithms are employed to correct the color output deviation of each pixel one by one. Color gamut consistency calibration not only focuses on the overall color temperature and color accuracy of the screen, but also specifically compensates for and balances color shifts caused by differences in local compensation and regional damping adjustment. Through a dual strategy of global adjustment and local fine-tuning of the color gamut curve, it ensures that color performance meets the requirements of consistency and accuracy across the entire screen under different brightness and grayscale adjustment states. This step effectively solves problems such as color unevenness and saturation imbalance that may occur during dynamic compensation and damping scheduling, further improving the visual experience.

[0042] Finally, based on the dynamically refreshed Gamma mapping lookup table and the globally calibrated pixel color gamut data, a set of dynamic photoelectric conversion mapping templates is formed. These templates serve as the standard for real-time correction during subsequent LCD operation, continuously and dynamically correcting and optimizing the screen's photoelectric conversion and color gamut output. To ensure long-term consistency between the templates and the display state, this implementation also incorporates a periodic self-check and dynamic feedback mechanism. This mechanism periodically resamples and analyzes the photoelectric response and color gamut output of each area of ​​the screen. If a deviation between the Gamma mapping curve and the color gamut performance is detected, the system automatically initiates a new round of Gamma mapping refresh and color gamut calibration.

[0043] Through the coordinated execution of the above steps, dynamic optimization of Gamma mapping and global color gamut consistency control based on damping scheduling results are achieved, comprehensively improving the photoelectric performance stability and color reproduction accuracy of the LCD screen under different environments and dynamic adjustments, and meeting the stringent requirements for high-quality visual display.

[0044] The results after global photoelectric conversion mapping and color gamut calibration are mapped to multiple zones of the LCD screen. The brightness power and gray level voltage of each zone are independently adjusted, and the coupling tensor between the zones is constructed. Based on the difference in brightness gradient and gray level curvature at the boundary of each zone, the coupling strength of the zone is dynamically adjusted to achieve stable control and smooth transition of brightness and gray level at the zone level. In this specific implementation: First, based on the dataset after global photoelectric conversion mapping and color gamut calibration, the display area of ​​the LCD screen is divided into multiple independent spatial partitions. Each partition corresponds to a certain number of pixel units, and the partitioning is dynamically performed according to the physical distribution of the screen, the weight of the visual field center, and the complexity of the content. This partitioning not only considers spatial uniformity but also introduces a visual attention factor, making the partitioning of the area of ​​human eye focus more detailed, thereby enhancing the precision of visual perception. After the partitioning is completed, the global photoelectric conversion mapping and color gamut calibration results are mapped and transformed within each partition to form the initial brightness power and grayscale voltage target values ​​for each partition based on the current lighting environment and image content. This step ensures that each partition has a baseline of global mapping and calibration at the beginning of the adjustment, avoiding the problem of inconsistent adjustment effects between partitions due to differences in initial conditions.

[0045] After global mapping is completed for each zone, dynamic adjustment of brightness power and grayscale voltage is performed independently for each zone. Specifically, real-time local photoelectric response parameters are first collected for each pixel unit within each zone, including key indicators such as current brightness level, contrast distribution, grayscale voltage response curve, and color saturation. Based on this locally collected real-time data, the backlight power adjustment range and grayscale voltage compensation value of that zone are dynamically adjusted to ensure that the brightness and grayscale response of that zone are always in an optimal state under the current lighting environment and image content. To prevent local adjustments from causing deviations from global calibration, a difference constraint mechanism is introduced during the adjustment process to control the zone adjustment range within the tolerance range of the global baseline, ensuring both local optimization effects and maintaining overall visual consistency. Through this independent and controlled zone adjustment, regional-level photoelectric control flexibility and precision are achieved.

[0046] To address the potential for discontinuities or visual fragmentation at region boundaries caused by independent adjustment of multiple regions, a coupling tensor between regions is constructed as a bridge to coordinate the adjustment effects of each region with the smoothness of its boundaries. This coupling tensor is built based on the differences in brightness gradient and grayscale curvature between adjacent regions. The brightness gradient is used to evaluate the rate of brightness change at the boundary between two regions, while the grayscale curvature reflects the smoothness of the grayscale changes at the boundary. Through quantitative analysis of these differences, coupling weight coefficients are formed between each pair of adjacent regions. A higher coupling weight coefficient indicates a larger brightness or grayscale difference at the boundary between the two regions, requiring stronger adjustment coupling. The coupling tensor is also dynamic in the time dimension, updating the coupling weights in real time as the image content and ambient light continuously change. This ensures that the adjustment between regions is both relatively independent and has a coherent transition characteristic at any given time, avoiding visual discontinuities or abrupt changes at the boundaries caused by independent adjustment.

[0047] Finally, based on the coupling tensor and its dynamic weight distribution, dynamic adjustment of the coupling strength between regions is implemented to achieve stable control and smooth transition of brightness and grayscale at the region level. In this step, a weighted adjustment factor is generated by multiplying the coupling tensor with the partition adjustment command, and the adjustment value of each partition is slightly adjusted to make the brightness and grayscale curves at the partition boundaries more continuous and smooth. For the dynamic changes in coupling strength, a boundary flexible adjustment mechanism is introduced to apply more detailed brightness and grayscale interpolation processing to the boundaries of high-weight partitions, ensuring that the boundary pixels naturally blend with the visual characteristics of adjacent partitions in physical location. At the same time, a feedback evaluation process is set up to continuously monitor the stability and visual smoothness of the region-level control, and continuously optimize the coupling strength and adjustment strategy through perceptual feedback. In this process, the adjustment of coupling strength is not limited to boundary pixels, but also applies a gradual adjustment transition to the inner pixels near the boundary, forming a multi-layered transition zone, which effectively improves the overall visual continuity and naturalness of the screen. Through this series of dynamic adjustments and coupling controls, the LCD screen achieves stable brightness and grayscale performance in multi-zone dynamic photoelectric control, and forms a delicate and seamless visual transition between different zones, greatly improving the display quality and visual comfort in high dynamic scenes and complex image content.

[0048] This invention successfully solves the nonlinear coupling problem between brightness adjustment and grayscale voltage compensation in existing technologies by constructing a grayscale control method for liquid crystal displays based on adaptive brightness compensation. This method accurately captures changes in ambient light and screen content through multimodal synchronous sampling and the generation of temporal joint feature vectors, dynamically predicting the target adjustment values ​​of backlight power and grayscale voltage, thus avoiding response lag and overshoot effects. Simultaneously, through spectral domain balancing and adaptive damping scheduling mechanisms, the coordinated control between backlight power and grayscale voltage is further optimized, suppressing high-frequency oscillations and ensuring linear response in the low-frequency band. This scheme effectively avoids the positive feedback effect between brightness and grayscale, reduces screen flicker and grayscale jumps, and improves the stability and continuity of the display effect. Furthermore, the dynamic refresh of the Gamma mapping lookup table and global color gamut calibration make the brightness and grayscale adjustment of the display in different zones more precise, ultimately achieving stable regional-level brightness and grayscale control, as well as a more natural and delicate visual transition, significantly improving the user's visual experience and the long-term reliability of the display.

[0049] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for gray scale control of a liquid crystal display panel based on adaptive brightness compensation, characterized by, The method comprises the following steps: Real-time acquisition of the ambient spectral distribution information of the liquid crystal display screen and the pixel gray scale voltage response curve and fusion processing to form a time sequence joint feature vector; Based on the time sequence joint feature vector, a feedforward recurrent prediction model is trained to dynamically predict the target adjustment value of the backlight power and the pixel gray scale voltage of the next frame of the liquid crystal display screen, and a bidirectional gate delay mechanism is introduced in the prediction process to perform time sequence correction on the target adjustment value obtained by prediction; According to the target adjustment value corrected in time sequence, a brightness power and gray scale voltage cooperative control matrix is constructed; On the basis of the cooperative control matrix, an adaptive damping scheduling mechanism is applied to real-time adjust the eigenvalue and spectral domain amplitude of the cooperative control matrix; Based on the output result of the adaptive damping scheduling mechanism, the Gamma mapping lookup table is dynamically refreshed, and the global calibration of the pixel color gamut consistency of the display screen is performed; The results of the global photoelectric conversion mapping and the color gamut calibration are mapped to the multiple partitions of the liquid crystal display screen, the independent adjustment of the brightness power and the gray scale voltage is performed on each partition, and the coupling tensor between regions is constructed, and the region coupling strength is dynamically adjusted according to the brightness gradient and gray scale curvature difference of the region boundary.

2. The method for controlling the gray scale of a liquid crystal display based on adaptive brightness compensation according to claim 1, wherein, The training of the feedforward recurrent prediction model comprises: The time sequence joint feature vector is loaded at the input end, the feature vector is generated based on the change of ambient light and screen content, and the dynamic characteristics of the liquid crystal display screen are reflected in real time; The target adjustment value of the backlight power and the gray scale voltage is predicted at the output end by a regression method, wherein the prediction model combines a feedforward neural network and a recurrent neural network, which are respectively responsible for modeling the nonlinear relationship and the time sequence dependent characteristics; Through multiple batches of training samples, the model parameters are optimized to adapt to different lighting environments and content changes.

3. The method for controlling the gray scale of a liquid crystal display based on adaptive brightness compensation according to claim 2, characterized in that, The bidirectional gate delay mechanism comprises: A forward gate unit is used to adjust the recent dynamic change response in the prediction path; A reverse gate unit is used to review the adjustment behavior of the historical sequence and provide cumulative influence, and the two cooperate to dynamically compensate for the response lag in the prediction output; The gate mechanism adjusts the gate delay depth and width in real time according to the change rate of the ambient light and the screen content through a time step adaptive adjustment strategy, ensures that the compensation process flexibly adapts to different change scenarios, and finally generates accurate prediction adjustment values.

4. The method for controlling the gray scale of a liquid crystal display based on adaptive brightness compensation according to claim 1, wherein, The cooperative control matrix construction method comprises: Based on the target adjustment value of the backlight power and the gray scale voltage corrected in time sequence, a two-parameter control space of brightness power and gray scale voltage is defined, and a cooperative control matrix is constructed; A spectral domain equalization method is used to map the backlight power change rate and the gray scale voltage gain in the time domain to the frequency domain through Fourier transform, analyze and correct the frequency response difference between the two, and ensure the cooperative balance of the two in each frequency band; Based on the cooperative control matrix optimized in the frequency domain, a nonlinear coupling compensation unit is applied to correct the nonlinear gain effect in the matrix through a double-variable cubic interpolation model to maintain the linearization trend of the adjustment behavior; A positive feedback suppression mechanism is introduced to dynamically adjust the feedback attenuation strategy by monitoring the matrix eigenvalue and spectral energy distribution to suppress the induced positive feedback effect.

5. The method for gray scale control of liquid crystal display based on adaptive brightness compensation according to claim 1, wherein, The adaptive damping scheduling mechanism comprises: The dynamic stability and frequency resonance risk of the matrix are evaluated by extracting the eigenvalues and spectral domain amplitudes of the cooperative control matrix; An adaptive damping scheduling model is constructed based on the analysis of the eigenvalue change rate and high-frequency energy, and the damping coefficient is dynamically adjusted according to the amplitude and change rate of the matrix eigenvalue and the high-frequency energy density; An attenuation weight is applied in the high-frequency oscillation region, while the linear response of the gray voltage is ensured in the low-frequency oscillation region, maintaining the consistency of the voltage and backlight power adjustment.

6. The method for gray scale control of a liquid crystal display based on adaptive brightness compensation according to claim 5, wherein, The real-time damping coefficient calculation method includes: The amplitude spectrum of the cooperative control matrix in the frequency domain is extracted by Fourier transform, and the energy accumulation rate of the high-frequency band is analyzed; The eigenvalue change rate and high-frequency energy density are input into the response function of the damping scheduling model, and the real-time damping coefficient is calculated through the preset nonlinear mapping relationship.

7. The method for gray scale control of liquid crystal display based on adaptive brightness compensation according to claim 1, wherein, The Gamma mapping refresh and color gamut calibration method includes: Based on the cooperative control matrix output by the adaptive damping scheduling mechanism, real-time acquisition of the photoelectric conversion data after backlight power and gray voltage adjustment is performed, and a multi-dimensional photoelectric response data set is generated; Based on the photoelectric response data, a Gamma mapping model is dynamically constructed and updated through nonlinear curve fitting of the Gamma mapping lookup table; According to the updated Gamma mapping results, multi-channel color sensors are used to collect full-screen RGB color coordinates and luminance values, perform color gamut consistency calibration, and solve the color shift caused by regional damping adjustment differences; Through periodic self-checking and dynamic feedback mechanism, the photoelectric conversion mapping and color gamut output are continuously optimized to ensure the color and brightness consistency of the liquid crystal display under different light and content changes.

8. The method for gray scale control of liquid crystal display based on adaptive brightness compensation according to claim 1, wherein, The partition adjustment method includes: Based on the data set after global photoelectric conversion mapping and color gamut calibration, the display area of the liquid crystal display is divided into multiple independent partitions, and the dynamic adjustment of the brightness power and gray voltage is performed in each partition; By real-time acquisition of the local photoelectric response data of each partition, the backlight power adjustment amplitude and gray voltage compensation value of the partition are dynamically adjusted to ensure that the partition brightness and gray scale response are in the optimal state; A coupling tensor between regions is constructed, and the coupling weight coefficient is generated by analyzing the brightness gradient and gray curvature difference, and the coupling strength is dynamically adjusted according to the image content and ambient light change; According to the dynamically adjusted coupling weight, the partition adjustment instruction is fine-tuned to ensure the continuous and smooth brightness and gray scale curve between partitions.

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