Self-adaptive color cast compensation method and device for liquid crystal display screen and storage medium

Abstract

The invention relates to the technical field of display, and discloses a self-adaptive color cast compensation method and device for a liquid crystal display screen and a storage medium, and the method comprises the steps: collecting real-time ambient light change data, and generating an ambient light feature data set; analyzing a mapping relation between screen color deviation and light parameters in the ambient light feature data set, and determining an interference mode of ambient light on screen colors; constructing a color rule database according to the interference mode, and generating a reference data matrix for real-time color cast compensation; based on the reference data matrix, generating an adaptive color adjustment curve, and determining color compensation parameters under different ambient light conditions; a color compensation scheme is generated according to the color compensation parameters, and color presentation of a display screen is adjusted in real time. The problem that the color of the liquid crystal display screen deviates in a complex and changeable light environment is solved, real-time correction of the liquid crystal display screen is achieved, and the accuracy of color display in different light environments is ensured.

Description

Technical Field

[0001] The present application relates to the field of display technology, and in particular to a method, device, and storage medium for adaptive color shift compensation of a liquid crystal display screen. Background Art

[0002] In the field of display technology, liquid crystal displays (LCDs) hold a key position among various display devices due to their mature technology, reasonable cost, and excellent display quality. LCDs are widely used in numerous fields due to their high refresh rate, high resolution, and wide color gamut.

[0003] The accuracy and adaptability of LCD screen color are key factors in improving user experience and device performance. With the widespread use of display devices in various scenarios, from bright outdoor environments to dim indoor spaces, users have higher expectations for screen color consistency in different environments. However, current LCD screens face a significant challenge in color adjustment: color adjustment methods for environmental changes often rely on fixed calibration patterns.

[0004] However, this fixed calibration mode has obvious limitations and is difficult to dynamically adapt to complex and changing lighting conditions, resulting in deviations in screen color in environments with dynamically changing lighting. Summary of the Invention

[0005] The embodiments of the present application provide an adaptive color deviation compensation method, device, and storage medium for liquid crystal display screens. The related art is difficult to effectively deal with the problem of complex light interference in the environment through the calibration method of fixed brightness adjustment. This is mainly reflected in the nonlinear dynamic change of color deviation pattern caused by the mixture of natural light and artificial light and instantaneous strong light; there is spatial heterogeneity in different areas of large display screens, such as the top is directly affected by spotlights and the bottom is affected by ground reflected light; and the color deviation response of different liquid crystal panels to the same light is hardware-dependent. However, the present application solves the problem of color deviation of liquid crystal display screens when facing complex light, which causes the display screen content to be unable to display normally, through closed-loop control from multi-sensor collaborative perception, interference pattern modeling to dynamic compensation matrix generation, and realizes real-time and accurate correction of display screen color to ensure the accuracy of color display under different lighting conditions.

[0006] The present invention provides an adaptive color cast compensation method for a liquid crystal display screen. The adaptive color cast compensation method for a liquid crystal display screen includes: Collect real-time ambient light change data and generate ambient light feature data sets; Analyzing the mapping relationship between the screen color deviation and the light parameters in the ambient light feature data set to determine the interference pattern of the ambient light on the screen color; Building a color law database based on the interference pattern and generating a reference data matrix for real-time color deviation compensation; generating an adaptive color adjustment curve based on the reference data matrix and determining color compensation parameters under different ambient light conditions; A color compensation solution is generated according to the color compensation parameters, and the color presentation of the display screen is adjusted in real time.

[0007] Optionally, the step of analyzing the mapping relationship between the screen color deviation and the light parameter in the ambient light feature data set to determine the interference pattern of the ambient light on the screen color includes: Obtaining the difference between the ambient light brightness and the light intensity in the ambient light feature dataset; If the difference value is not within the preset difference threshold range, marking the difference value as an abnormal light interval, and extracting the color temperature distribution characteristics of the abnormal light interval; The synergistic effect between the color temperature distribution characteristics and the light incident angle is analyzed, the interference pattern characteristics that cause the color distortion of the display screen are extracted, and the interference pattern is determined.

[0008] Optionally, the step of constructing a color law database according to the interference pattern and generating a reference data matrix for real-time color deviation compensation includes: Based on the interference pattern, the ambient light feature data set is classified to generate interference types containing color deviation rules, thereby obtaining preliminary classification data; Matching the preliminary classification data with the dynamic change parameters of the ambient light to generate the color law database; Matching the color regularity database with preset association rules to generate color deviation association quantification results; Based on the color deviation correlation quantification result, the real-time ambient light data is compared with the screen color deviation to generate the reference data matrix.

[0009] Optionally, after the step of comparing the real-time ambient light data with the screen color deviation based on the color deviation correlation quantification result to generate the reference data matrix, the following steps are included: Obtaining reference data content in the reference data matrix, and detecting a deviation between the reference data content and an actual detection value; If the deviation value is greater than the preset deviation value, the historical reference data content, the actual detection value and the screen response data are fused to adjust the reference data matrix.

[0010] Optionally, the step of generating an adaptive color adjustment curve based on the reference data matrix and determining color compensation parameters under different ambient light conditions includes: Classify and match the environmental variables and light conditions in the reference data matrix using preset data mapping rules to generate preliminary mapping data; Obtaining the change of the light condition and the trend of color shift in the preliminary mapping data to generate the adaptive color adjustment curve; If it is detected that the adaptive color adjustment curve deviates from the expected adjustment curve, the adaptive color adjustment curve is corrected, and a compensation parameter range corresponding to the correction is obtained to generate a compensation parameter set; Adaptively matching the compensation parameter set with the light conditions to determine the color compensation parameters.

[0011] Optionally, after the step of adaptively matching the compensation parameter set with the light conditions to determine the color compensation parameters, the method further includes: Dynamically monitor real-time light conditions and obtain at least one environmental variable data set related to light intensity; If the light intensity in the monitored environmental variable data set exceeds a preset light intensity threshold range, the environmental variable data set is compared with the real-time light condition to generate preliminary adjustment data corresponding to the current ambient light; Obtaining a color shift pattern that matches the real-time light condition from a historical database, and correcting the preliminary adjustment data according to the color shift pattern to update the compensation parameter set; The updated compensation parameter set is matched with actual display requirements to determine the color compensation parameters that match the real-time light conditions.

[0012] Optionally, the step of generating a color compensation solution according to the color compensation parameters and adjusting the color presentation of the display screen in real time includes: Decomposing the color compensation parameters to obtain at least one adjustment data set associated with screen output; Comparing the adjustment data set with the expected display requirements to generate the color compensation solution; generating an adjustment instruction according to the color compensation scheme, and controlling the color presentation content of the display screen according to the adjustment instruction; The color value of the display screen is dynamically monitored, and the adjustment instruction is corrected according to the monitoring result to complete the real-time adjustment of the color presentation of the display screen.

[0013] Optionally, after the step of generating a color compensation solution according to the color compensation parameters and adjusting the color presentation of the display screen in real time, the method further includes: Continuously monitoring changes in ambient light, generating a light fluctuation data set, and determining a fluctuation range of the light fluctuation data set; Obtaining the display screen area corresponding to the fluctuation range exceeding the preset deviation range, and obtaining the screen deviation distribution; According to the screen deviation distribution, color correction is performed layer by layer on the display screen area to complete the color deviation adjustment of the display screen.

[0014] In addition, to achieve the above-mentioned purpose, an embodiment of the present invention also provides a terminal device, including a memory, a processor, and an adaptive color deviation compensation program for a liquid crystal display screen stored in the memory and runnable on the processor. When the processor executes the adaptive color deviation compensation program for the liquid crystal display screen, the method described above is implemented.

[0015] In addition, to achieve the above-mentioned purpose, an embodiment of the present invention further provides a computer-readable storage medium, on which a program for adaptive color cast compensation for a liquid crystal display is stored. When the program for adaptive color cast compensation for a liquid crystal display is executed by a processor, the method described above is implemented.

[0016] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: (1) The present invention collects ambient light data in real time and constructs a feature data set, analyzes the mapping relationship between light parameters and screen color deviation, and thus identifies the interference pattern of ambient light on the displayed color. This solves the problem that the mixture of natural light and artificial light sources causes nonlinear changes in the color deviation pattern. The related technologies cannot effectively solve the problem of the influence of nonlinear complex light on the display screen through subjective calibration or fixed compensation. This realizes data-driven interference pattern recognition and provides a scientific basis for subsequent compensation.

[0017] (2) Based on the identified interference patterns, the present invention establishes a color regularity database and generates a real-time compensation reference matrix, thereby inferring an adaptive adjustment curve and accurately calculating color compensation parameters under different lighting conditions. Compared with static compensation solutions based on preset patterns, this dynamic compensation approach can cover more complex lighting scenarios, such as day-night switching and mixed light sources, significantly improving the flexibility of color reproduction.

[0018] (3) After calculating the color compensation parameters, the present invention adjusts the color output of the display screen in real time according to the color compensation parameters to offset the color cast and contrast reduction of the liquid crystal display screen caused by ambient light, thereby ensuring that the same content presents consistent color performance under different lighting conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a flow chart of a first embodiment of the method for adaptive color shift compensation for a liquid crystal display screen of the present application; Figure 2This is a flow chart of a second embodiment of the method for adaptive color shift compensation for a liquid crystal display screen of the present application; Figure 3 This is a flow chart of a third embodiment of the method for adaptive color shift compensation for a liquid crystal display screen of the present application; Figure 4 This is a schematic diagram of the terminal structure of the hardware operating environment involved in an embodiment of the present application. DETAILED DESCRIPTION

[0020] To address display distortion issues such as color shift and contrast loss on LCD screens in complex lighting environments where natural and artificial light are mixed, this solution collects ambient light data in real time and constructs a feature dataset. This dataset then analyzes the mapping between light parameters and screen color deviations, identifying patterns of ambient light interference on displayed colors. Based on these identified interference patterns, a color regularity database is established and a real-time compensation reference matrix is generated. This in turn infers an adaptive adjustment curve and accurately calculates color compensation parameters under different lighting conditions. Finally, the display's color output is adjusted in real time based on the color compensation parameters. This achieves color reproduction and stable display in complex lighting environments.

[0021] To better understand the above technical solutions, exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Instead, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0022] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0023] Example 1 In this embodiment, a method for adaptively compensating color cast of a liquid crystal display is provided.

[0024] Reference Figure 1 The adaptive color shift compensation method for a liquid crystal display screen of this embodiment includes the following steps: Step S100: collecting real-time ambient light change data to generate an ambient light feature data set; In this embodiment, by deploying a multi-point light sensor array, ambient light change data is collected in real time, covering light inputs of different angles and intensities, generating an ambient light feature data set including brightness, color temperature and spectral distribution, and obtaining preliminary ambient light change results.

[0025] As an optional implementation, a deployed light sensor array collects real-time ambient light data, covering light inputs of varying angles and intensities. This data sets a raw dataset containing brightness, color temperature, and spectral distribution. This dataset is then preliminarily cleaned to remove outliers, resulting in a consolidated light feature set. Based on this light feature set, the brightness and color temperature data are classified within a preset threshold range. If the brightness value within a certain time period exceeds this threshold, it is marked as an abnormal light interval. The spectral distribution data within this abnormal light interval is then collected to determine the specific characteristic distribution of the abnormal light interval.

[0026] For example, in the process of collecting real-time ambient light data using a light sensor array, assume the sensor array is deployed in various locations around the environment, covering multiple angles, and collects data every five minutes, recording brightness, color temperature, and spectral distribution. Assume that the brightness data collected during a particular session ranges from 200 to 800 lux, and the color temperature data ranges from 3000 to 6500 Kelvin. The spectral distribution is characterized by the intensity values of the red, green, and blue color channels. During initial data cleaning, it is discovered that the brightness value of a sensor suddenly reaches 1200 lux, significantly deviating from the normal range. This value can be treated as an outlier and removed, resulting in a light feature set. When classifying the brightness and color temperature data, a brightness threshold of 300 to 700 lux and a color temperature threshold of 3500 to 6000 Kelvin can be preset. If the brightness value reaches 850 lux during a certain period, it is marked as an abnormal light interval. Further extraction of the spectral distribution data for this abnormal light interval reveals an abnormally high proportion of the red channel intensity, likely due to interference from nearby red lights. The identification of this characteristic distribution helps to locate the specific source of the abnormal light.

[0027] As another optional implementation, after determining the specific characteristic distribution of the abnormal light interval, the characteristic distribution of the abnormal light interval is compared and analyzed to obtain data differences with the normal light interval. The fluctuation trend of this data difference is determined to obtain a quantitative fluctuation result of the ambient light change. Based on this quantitative fluctuation result, combined with the light input data from different angles, the light characteristics collected at multiple points are integrated and processed to determine the variation pattern of the ambient light at different time periods and spatial locations, thereby obtaining an ambient light characteristic dataset.

[0028] For example, when an abnormal light interval is detected, retrospective analysis of historical light data reveals a clear periodic fluctuation in brightness values. Color temperature parameters also consistently deviate from the baseline by approximately 500 Kelvin. This fluctuation trend is therefore clearly correlated with specific external interference sources, such as the lights of vehicles passing by the window. This fluctuation trend provides a basis for subsequent quantification of ambient light variations, which show a fluctuation amplitude of ±150 lux, with a period of approximately 10 minutes. Weights are dynamically assigned based on the spatial location and level of interference experienced by each sensor. For example, data from sensors near windows, which are more susceptible to external light, is weighted 0.6, while data from relatively stable indoor sensors is weighted 0.4. This differentiated weighting strategy preserves the characteristics of external light variations while ensuring the stability of underlying light parameters. Through real-time fusion processing, not only is the significant brightness fluctuation characteristic of the window area during the morning hours accurately captured, but also the relatively stable lighting conditions deep inside the room are observed. The resulting ambient light feature dataset not only contains precise quantitative parameters but also fully captures the spatial distribution and temporal variation patterns of the light features.

[0029] Step S200: analyzing the mapping relationship between the screen color deviation and the light parameters in the ambient light feature data set to determine the interference pattern of the ambient light on the screen color; In this embodiment, a preset light impact model is used to analyze the ambient light feature data set, and features are extracted from the mapping relationship between screen color deviation and light parameters to determine the specific interference pattern of ambient light changes on screen color. Among them, the light impact model is a model used to quantify the impact of ambient light on the color deviation of the display screen. By analyzing the mapping relationship between ambient light parameters such as ambient light intensity, color temperature, and incident angle and screen color changes, prediction rules are established to provide a basis for real-time color compensation. The light impact model identifies key interference factors from the ambient light data, classifies typical interference scenarios, and outputs compensation parameters for use in real-time color correction. For example, it identifies the key interference factor "high color temperature light causing overexposure of the blue channel" and classifies it as "diffuse weak light."

[0030] As an optional implementation, the difference value of the ambient light brightness and light intensity in the ambient light feature data set is obtained. If the difference value is not within the preset difference threshold range, the difference value is marked as an abnormal light interval, and the color temperature distribution characteristics of the abnormal light interval are extracted; the synergistic effect of the color temperature distribution characteristics and the light incident angle is analyzed, the interference pattern characteristics that cause the color distortion of the display screen are extracted, and the interference pattern is determined.

[0031] For example, a preset brightness threshold range of 200 to 700 lux is used to account for differences in ambient light brightness and light intensity. If the brightness reaches 850 lux within a specific time period, this period is marked as an abnormal lighting period. Spectral data analysis is performed within this period to obtain color temperature distribution characteristics. Assuming that the color temperature data is concentrated in the low color temperature range of 3000 to 4000 Kelvin, combined with data from a multi-angle light sensor, it is confirmed that light primarily illuminates the screen from the left floor-to-ceiling window at an incident angle of 45 to 60 degrees. Data comparison reveals that under these abnormal lighting conditions, the left side of the screen exhibits a significant red-yellow color shift. Further analysis reveals that when the incident angle is less than 50 degrees, the degree of color shift increases exponentially with decreasing angle, and the red channel gain abnormally increases by 12%. These characteristic parameters (850 lux, 3500 Kelvin, 50-degree incident angle, left-side red shift) are constructed as a "warm light oblique interference pattern," and its spatial distribution characteristics are recorded as follows: the affected area is concentrated in the left 30% of the screen area, and the color shift gradient decreases from left to right. This method of generating interference pattern characteristics by analyzing color temperature distribution characteristics and light incident angle can effectively solve the problem of related technologies being unable to adjust color deviation when there are significant differences in light angle and intensity in different areas of a large display screen.

[0032] As another optional implementation method, after determining the interference pattern, the interference pattern distribution data is obtained, and the interference pattern distribution data is integrated and processed in combination with the spatial position influence to determine the scope of influence of the ambient light change on the screen display adjustment. The interference pattern distribution data is a set of multidimensional feature sets, including the physical properties of the ambient light itself, such as light intensity, color temperature and other data, and is integrated with the spatial distortion characteristics generated by the interaction between light and the display screen, such as the red-yellow bias in the 30% area on the left and the abnormal gain of 12% in the red channel. Spatial position influence refers to the spatial dependence of ambient light when interacting with the display screen, including the change pattern of light source position, screen area and interference intensity with screen position.

[0033] For example, interference pattern distribution data is obtained and combined with spatial position effects to establish a dynamic mapping relationship. For example, when light of a specific incident angle is detected from the left, a three-dimensional compensation field is constructed. In this field, the adjustment amount of each pixel is determined by its spatial coordinates. The directly affected left core area uses the maximum compensation intensity, such as reducing the red channel by 12%. As the position moves to the right, the compensation intensity decreases smoothly according to the optical attenuation law until it returns to zero in the unaffected area. This combination is not a simple data superposition, but rather an interdisciplinary algorithm that transforms abstract interference parameters into pixel-level operation instructions on the physical coordinates of the screen through light propagation models, display material properties, and human visual perception. Ultimately, it achieves a display effect that eliminates local color casts while maintaining overall picture harmony.

[0034] For example, if the interference pattern distribution data is [850 lux, 3500K, 50-degree incident angle, left red shift, red channel +12%], the spatial position affects the light source orientation from 45 to 60 degrees to the left, the physical range of the display affected by ambient light is the left 30% of the area, and the interference intensity decreases with screen position from left to right. The interference pattern distribution data is integrated with the spatial position to create a spatial position model. A geometric correspondence is established between the sensor coordinates, such as the position [x, y] of sensor 3 on the left, and the screen partitions. The interference weight is calculated for each pixel, for example, a weight of 1.0 for the directly illuminated area and a cosine decay for the edge area. The color shift parameter "red channel +12%" in the interference pattern is converted into a compensation matrix based on the spatial weight distribution. For example, the left 15% area is compensated with -12% of the red channel, and the area between 15% and 30% is linearly reduced to -5%. A Kalman filter is then used to predict the movement of the interference area. For example, if the sun moves westward, the affected area expands to the right. Bilateral filtering is then used to eliminate jagged edges and ensure visual smoothness.

[0035] When integrating interference pattern distribution data and taking into account spatial positional influences, it's possible to consider sensor data collected at different locations around the screen. For example, if the sensor near the left side detects higher warm light intensity, while the sensor on the right side is normal, fusion processing can determine that the impact of ambient light changes on screen display adjustments is primarily concentrated in the left area. This analysis helps pinpoint the screen area requiring adjustment. By correcting color cast by region, efficiency is effectively improved, ensuring overall display harmony.

[0036] Optionally, for the relationship between light angle changes and screen color deviation, the interference pattern can be analyzed by comparing light input data at different angles. Assuming that when light is incident from a 45-degree angle on the left, the brightness of the left area of the screen increases by about 150 lux, and the color temperature decreases by about 500 Kelvin, resulting in a yellowish display. The angular interference pattern features are extracted to provide a basis for subsequent corrections. This refined analysis enables targeted adjustment of screen parameters.

[0037] Step S300: constructing a color regularity database according to the interference pattern, and generating a reference data matrix for real-time color deviation compensation; In this embodiment, by classifying the interference patterns, a color regularity database is constructed, the correlation between the ambient light change and the screen color deviation is quantified and stored, and a reference data matrix that can be used for subsequent adjustments is obtained.

[0038] As an optional implementation, the ambient light feature data set is classified based on the interference pattern to generate interference types containing color deviation rules, thereby obtaining preliminary classification data.

[0039] For example, the impact of changes in ambient light on screen deviation can be handled through classification. First, different threshold ranges are set for the characteristics of the interference pattern. Assume that in an indoor office scene, the brightness threshold range of the ambient light is set to 100 to 600 lux, and the color temperature threshold range is 4000 to 6000 Kelvin. If the brightness is monitored to be 650 lux and the color temperature is 3500 Kelvin in a certain period of time, it will be classified as an abnormal pattern category and marked as "warm light interference" in the preliminary classification data. This classification method can quickly screen out lighting conditions that may affect screen display.

[0040] Optionally, the classification of interference patterns can be further refined based on the influence of light angle. For example, if light is incident from a 30-degree angle from the left, the brightness of the left area of the screen increases significantly, while the right area changes less. In this case, the classification data will be labeled "left light interference". This refined classification can provide a more accurate basis for subsequent local adjustments.

[0041] As another optional implementation, the preliminary classification data is matched with the dynamic change parameters of the ambient light to generate a color law database; and the color law database is matched with preset association rules to generate a color cast association quantification result.

[0042] For example, when integrating and processing the preliminary classification data, the color data can be matched with the dynamic change parameters of the ambient light. Assuming that periodic changes in lighting are detected in a certain conference room during the morning hours, the collected light data is classified and the category of "intermittent warm light interference" is identified. Its characteristics are that the color temperature fluctuates between 3000 Kelvin and 3500 Kelvin, accompanied by a periodic increase of 20% in the intensity of the red light spectrum. These classification results are matched with the dynamic change parameters of the ambient light, and a record is generated in the color law database. The rule is that "when the color temperature is lower than 3500 Kelvin and the red light intensity increases by more than 15%, the red channel of the screen will show an average of 12% oversaturation." When the data recorded in the color law database matches the preset association rule of "low color temperature-red light oversaturation", the quantitative calculation engine is started. For example, if the current color temperature is detected to be 3200 Kelvin and the red light intensity is increased by 18%, the relevant data in the color law database is obtained to obtain a preliminary compensation value, which is then matched with the association rule of "low color temperature-red light oversaturation". The preliminary compensation value is corrected to obtain an accurate compensation value and the compensation rules are optimized synchronously, ultimately generating a quantitative result including compensation intensity and execution parameters.

[0043] As another optional implementation, based on the color deviation correlation quantification result, the real-time ambient light data is compared with the screen color deviation to generate the reference data matrix.

[0044] For example, after determining the associated quantification results, the correspondence between the ambient light changes and the screen deviations is sorted out. Assuming that through comparison it is found that when the color temperature is reduced to 3500 Kelvin, the blue channel value displayed on the screen decreases by about 10%, a storage matrix is generated to record this correspondence in the form of data. This matrix storage method facilitates the rapid retrieval of reference data content.

[0045] Optionally, the generation and calibration of the reference data matrix can be supplemented with data from the time dimension. For example, if light changes regularly throughout the day, the reference data matrix can record reference data for a specific time period, such as the relationship between light parameters and screen deviation at 9:00 AM. This approach improves the matrix's dynamic adaptability, ensuring appropriate adjustment references under different time conditions.

[0046] As another optional implementation, after generating the reference data matrix, the reference data content in the reference data matrix is obtained, and the deviation value between the reference data content and the actual detection value is detected; if the deviation value is greater than the preset deviation value, the historical reference data content, the actual detection value and the screen response data are fused to adjust the reference data matrix.

[0047] For example, if the reference data differs from the adjustment basis, for example, if the blue channel reduction value recorded in the reference data matrix is inconsistent with the actual measured value, calibration is performed. For example, if the blue channel is reduced by 15% in the actual measurement, while the matrix records a 10% reduction, multiple sets of test data are combined to adjust the matrix content and generate the final adjusted data matrix.

[0048] Optionally, when judging whether the adjusted reference data matrix meets the preset matching criteria, a deviation tolerance range can be set, such as an allowable deviation value of plus or minus 5%. If the deviation between the blue channel adjustment value and the target value in the adjusted matrix data is within 3%, it is considered to meet the criteria. This judgment method helps to ensure the applicability of the final adjusted data.

[0049] Step S400: generating an adaptive color adjustment curve based on the reference data matrix, and determining color compensation parameters under different ambient light conditions; In this embodiment, a regression analysis algorithm may be applied to the reference data matrix to generate an adaptive color adjustment curve, thereby dynamically determining optimal color compensation parameters according to different ambient light conditions.

[0050] As an optional implementation, the environmental variables and light conditions in the reference data matrix are classified and matched according to preset data mapping rules to generate preliminary mapping data.

[0051] For example, when constructing a reference data matrix and organizing the correspondence between environmental variables and lighting conditions, variables such as ambient light brightness and color temperature are classified and matched. Assuming that in a display application environment, the ambient light brightness ranges from 200 to 800 lux and the color temperature ranges from 3000 to 7000 Kelvin, these variables are associated with the screen color offset to generate preliminary mapping data.

[0052] Optionally, the relationship between environmental variables and lighting conditions can be organized to consider the impact of light direction. For example, if light is incident directly from the front of the screen, the overall brightness is uniform, while when it is incident from the side, the color shift is more obvious at the edge of the screen. Recording this additional variable will form more comprehensive mapping data.

[0053] As another optional implementation, the change in the light condition and the trend of color shift in the preliminary mapping data are obtained to generate the adaptive color adjustment curve.

[0054] For example, when processing preliminary mapping data, the team analyzes trends in lighting conditions and color shifts. Assuming that the red channel value of the screen exhibits a nonlinear upward trend as brightness gradually increases, an adjustment curve is drawn based on historical data, and the corresponding curve parameter combination, such as slope and inflection point value, is extracted. If these parameters are found to be inconsistent with the corresponding preset threshold ranges, such as the slope value being outside the expected range, further calibration is required to ensure the accuracy of the curve.

[0055] Optionally, the time dimension can be incorporated into the adjustment curve fitting. For example, if light conditions vary regularly throughout the day, such as the color temperature of light at 10 AM being higher, different curve parameter combinations can be generated based on the time of day. This approach makes the adjustment scheme more dynamic and adaptable, ensuring appropriate color compensation at all times.

[0056] As another optional implementation, if it is detected that the adaptive color adjustment curve deviates from the expected adjustment curve, the adaptive color adjustment curve is corrected, and a compensation parameter range corresponding to the correction is obtained to generate a compensation parameter set.

[0057] For example, when a deviation in the color adjustment curve is detected, the curve is corrected and optimized based on the actual detection data. For example, if it is detected that the offset of the screen's blue channel is 3% to 5% higher than the curve's predicted value under specific lighting conditions, the curve parameters are adjusted to generate a matching compensation parameter range, thereby generating a compensation parameter set. For example, the final compensation parameter range may require a 5% to 8% increase in the blue channel value to accommodate the current ambient light changes.

[0058] Optionally, when revising compensation parameters, we can also incorporate user feedback for optimization. For example, if a user reports a color cast on the screen under specific lighting conditions, we prioritize analyzing this feedback and adjusting the compensation parameter range to better suit actual usage scenarios. This approach significantly improves the user experience and ensures the practicality of the adjustment results.

[0059] As another optional implementation, after generating the compensation parameter set, the compensation parameter set is adaptively matched with the light conditions to determine the color compensation parameters.

[0060] For example, the adaptability of the color compensation parameter set to lighting conditions can be analyzed. Assuming that the compensation parameters behave differently under various environmental variables, such as natural light in the morning and lighting conditions in the evening, the optimal parameter combination (i.e., the final color compensation parameters) can be determined by analyzing which set of parameters is more stable under different conditions. For example, in the evening when the brightness is low, the compensation value of the blue channel may need to be adjusted to 6%, while maintaining it at 5% during the day. This combination will be used as the final basis for adjustment.

[0061] Step S500: generating a color compensation solution according to the color compensation parameters, and adjusting the color presentation of the display screen in real time.

[0062] In this embodiment, a specific color compensation solution is generated according to the color compensation parameters, and the adjustment instruction is transmitted to the display driver module to update the screen color output value in real time to determine the final color presentation effect.

[0063] As an optional implementation, the color compensation parameters are first decomposed to obtain at least one adjustment data set associated with the screen output.

[0064] For example, color compensation requirements can be decomposed, breaking down the complex effects of ambient light into multiple actionable data dimensions. By analyzing factors like light intensity and color temperature distribution, an adjustment dataset directly related to screen output can be extracted. For example, if the indoor light intensity is 600 lux and the color temperature is warm, a dataset is generated that includes a 5% brightness increase and a color temperature adjustment to 5500 Kelvin.

[0065] As another optional implementation, the adjustment data set is compared with the expected display requirements to generate the color compensation solution.

[0066] For example, when comparing the adjusted dataset to the expected display requirements, a database of historical lighting conditions can be used to find reference data that most closely matches the current environment. Assuming the current lighting conditions are similar to a high-brightness scene in the historical database, the comparison results may suggest reducing the screen contrast to meet the expected display requirements, thereby forming a preliminary color compensation solution. This approach helps ensure that the adjustment direction is consistent with the actual scene.

[0067] As another optional implementation, after a color compensation scheme is generated, an adjustment instruction is generated according to the color compensation scheme, and the color presentation content of the display screen is controlled according to the adjustment instruction.

[0068] For example, when converting a color compensation scheme into an adjustment instruction, the focus is on breaking down the abstract compensation scheme into specific operating parameters. Assuming that the color compensation scheme requires a 10% reduction in brightness, a corresponding numerical instruction is generated, and the instruction is formatted in combination with the light adaptation characteristics, such as the rate of change of ambient light, to ensure that the instruction is suitable for the display driver module. When the instruction set is transmitted to the display driver module, the real-time nature of the data needs to be ensured. If it is detected during the transmission that the light intensity suddenly rises from 600 lux to 850 lux, which exceeds the preset range, the system will correct the instruction set, such as temporarily increasing the brightness adjustment amplitude, to generate the final output control data. This dynamic correction mechanism can ensure that the instruction always fits the current environment.

[0069] As another optional implementation, the color value of the display screen is dynamically monitored, and the adjustment instruction is modified according to the monitoring result to complete the real-time adjustment of the color presentation of the display screen.

[0070] For example, the screen color value can be dynamically monitored, and the screen display data can be collected in real time through the built-in sensor, and adjusted according to the color presentation requirements. If the monitoring finds that the screen brightness is too high, the output value will be immediately lowered to ensure that the final displayed content meets the visual comfort standards. This real-time adjustment capability can effectively improve the adaptability of the screen display.

[0071] Optionally, when monitoring and adjusting the color values of the display screen, user habits can be used as auxiliary parameters. Assuming that the user prefers cool colors, this characteristic can be retained during adjustment to ensure that the final displayed content adapts to the ambient light, thereby meeting personalized needs.

[0072] It's important to note that the spatial distribution of the sensor array is physically mapped to the display's partitions, ensuring precise data acquisition. Retrospective analysis of historical illumination data is used to optimize the initial parameters of the real-time model and improve compensation efficiency. The color pattern database is iteratively updated based on the coupling between ambient light characteristics and panel properties, enabling the system to adapt and evolve. These components work together to achieve dynamic color shift suppression, a feat unattainable by single calibration methods in related technologies.

[0073] In this embodiment, by collecting real-time ambient light data and analyzing its mapping relationship to screen color shift, specific lighting interference patterns are identified. Based on this data, a color regularity database is established and a compensation matrix is generated, ultimately achieving real-time adaptive color correction based on ambient light changes. This enables real-time, adaptive, and precise color correction of the LCD display under varying ambient lighting conditions, ensuring that the displayed image maintains accurate color representation in a variety of lighting environments.

[0074] Example 2 Based on the first embodiment, another embodiment of the present application is proposed, referring to Figure 2 After the step of adaptively matching the compensation parameter set with the light conditions to determine the color compensation parameters, the following steps are included: Step S410: Dynamically monitor the real-time light conditions to obtain at least one environmental variable data set related to light intensity; Step S420: If the light intensity in the monitored environmental variable dataset exceeds a preset light intensity threshold range, the environmental variable dataset is compared with the real-time light condition to generate preliminary adjustment data corresponding to the current ambient light; Step S430: Acquire a color shift pattern matching the real-time light condition in a historical database, and modify the preliminary adjustment data according to the color shift pattern to update the compensation parameter set; Step S440: matching the updated compensation parameter set with actual display requirements to determine the color compensation parameters that match the real-time light conditions.

[0075] In this embodiment, the ambient light is continuously monitored. If the ambient light changes under complex lighting conditions exceed the preset light intensity threshold, a pre-established deep learning model is called to optimize the compensation parameters for color adjustment in real time to obtain color compensation parameters for specific scenes.

[0076] As an optional implementation, the current light conditions are dynamically monitored according to the changes in ambient light, and at least one environmental variable data set related to the light intensity is obtained therefrom to determine whether it exceeds the preset light intensity threshold range. If so, the environmental variable data set is compared with the light conditions to determine the adjustment basis adapted to the current ambient light and generate the preliminary adjustment data.

[0077] For example, when dynamically monitoring the current light conditions, the intensity and changing trends of the ambient light can be captured in real time through the built-in light sensor. The core is the ability to convert light intensity into a quantifiable environmental variable data set, such as recording the light intensity in lux. Assuming that in the environment where the display screen is used, the light intensity suddenly increases from 300 lux to 900 lux in a short period of time, exceeding the preset threshold range of 500 to 800 lux, the light intensity is matched with the light conditions in the historical data, and the color shift pattern under similar light intensities is analyzed. Assuming that the current light intensity is 900 lux, it is determined that the screen brightness needs to be reduced by a certain percentage to avoid overexposure, and at the same time, this adjustment basis is recorded to generate preliminary adjustment data.

[0078] Optionally, when dynamically monitoring light conditions, the cyclical nature of ambient light changes can be taken into account. For example, if light intensity fluctuates regularly throughout the day, such as being weak in the morning and gradually increasing in the afternoon, this additional time dimension can be recorded to form a more comprehensive dataset. This detailed processing allows for more precise adaptation to scene requirements during subsequent mapping and calibration, making adjustments more targeted.

[0079] As another optional implementation, after generating the preliminary adjustment data, the preliminary adjustment data needs to be corrected, and the curve parameters for color adjustment are updated in real time in combination with the characteristics of light intensity and ambient light changes to obtain an optimized compensation parameter set.

[0080] For example, when correcting the parameter mapping results, the focus is on combining the characteristics of light intensity and ambient light changes to update the color adjustment curve parameters in real time. The slope and offset of the curve are dynamically adjusted according to the rate of change of light intensity. For example, when the light intensity changes rapidly, priority is given to improving the response speed of the adjustment to ensure that the screen color does not cause discomfort due to delays. Assuming that the light intensity rises from 300 lux to 900 lux within 5 minutes, the color adjustment curve parameters are updated to a steeper form to generate an optimized compensation parameter set.

[0081] As another optional implementation, after updating the compensation parameter set, the compensation parameter set is matched with the actual display requirements to obtain a final adjustment basis, and a parameter strategy for real-time light conditions is determined, that is, the final color compensation parameters are determined.

[0082] For example, when matching the optimized compensation parameter set with the actual scene adaptation requirements, the goal is to determine the parameter strategy for specific lighting conditions. Assuming that in a high-brightness environment, the screen needs to reduce the overall brightness and fine-tune the color temperature to maintain visual comfort, analyze which set of data in the optimized parameter set better meets the current needs. If the final strategy is to reduce the brightness by 15% and adjust the color temperature to 5000 Kelvin, this adjustment basis can effectively alleviate visual fatigue under strong light while maintaining the natural presentation of colors.

[0083] Optionally, the distribution characteristics of ambient light can be used as a reference during parameter calibration and comparison. For example, if light primarily shines from the sides of the screen, resulting in uneven brightness around the edges, parameters can be adjusted to account for this characteristic, ensuring that color compensation around the edges remains consistent with the center. This approach can significantly improve screen display uniformity and provide users with a more comfortable visual experience.

[0084] In this embodiment, by real-time monitoring of ambient light changes, intelligent analysis of light conditions and dynamic calibration of display parameters, it is ensured that the screen color can adaptively adjust parameters in various lighting environments to ensure the best visual effect.

[0085] Example 3 Based on the first and second embodiments, another embodiment of the present application is proposed, referring to Figure 3 After the step of generating a color compensation scheme according to the color compensation parameters and adjusting the color presentation of the display screen in real time, the following steps are included: Step S510: continuously monitoring changes in ambient light, generating a light fluctuation data set, and determining a fluctuation range of the light fluctuation data set; Step S520: obtaining the display screen area corresponding to the fluctuation range exceeding the preset deviation range, and obtaining the screen deviation distribution; Step S530: performing color correction on the display screen area layer by layer according to the screen deviation distribution to complete the color deviation adjustment of the display screen.

[0086] In this embodiment, after real-time adjustment of the display screen color presentation, it is also necessary to continuously monitor the feedback data between the ambient light changes and the screen color deviation, iteratively correct the color compensation scheme, obtain more accurate light perception accuracy and visual consistency adjustment results, and update the color data rule database for the iteratively corrected color compensation scheme to ensure that the targeted adjustment scheme can be quickly matched in subsequent ambient light changes to obtain long-term stable color performance.

[0087] As an optional implementation, the light intensity of the surrounding environment is continuously captured, and the frequency of environmental changes is recorded during the capture to obtain a corresponding light fluctuation data set, and determine the specific change range of the light fluctuation data set.

[0088] For example, the built-in sensor continuously captures the ambient light intensity. The key is to accurately record the frequency of light changes. For example, in an indoor scene, the light intensity fluctuates from 500 lux to 700 lux in a short period of time. This frequency of change is recorded to form a light fluctuation dataset, which can then be analyzed to determine that the range of change is within 200 lux. This recording method facilitates subsequent adaptation to environmental changes.

[0089] As another optional implementation, when analyzing the screen deviation distribution, the color value of the current screen can be captured, and the deviation part that does not meet the preset threshold can be extracted from the captured data to obtain the deviation distribution of the screen color.

[0090] For example, if the preset brightness threshold is 100 nits and the actual captured value is 110 nits, the deviation exceeding 10 nits will be individually marked to form a deviation distribution. This extraction method provides a clear direction for subsequent corrections, especially when the deviation exceeds the threshold range, and can quickly locate the problem area.

[0091] Optionally, when capturing deviations, historical data comparison can also be introduced. Assuming that the current deviation distribution is similar to that of a certain period in the past, the historical adjustment plan can be referred to to quickly extract the deviation part. This method can shorten the analysis time and improve the adjustment efficiency.

[0092] As another optional implementation, after determining the screen deviation distribution, the system analyzes whether it is within a preset deviation range. If it is, the deviation is corrected layer by layer, combining the properties of color correction and correction accuracy, and the adjusted color values are obtained during the correction process. After the color value adjustment is completed, the adjusted color values are matched with the light fluctuation dataset based on the properties of real-time adjustment and environmental adaptation. The matching is optimized based on light perception requirements to obtain the final screen output adjustment solution.

[0093] For example, assuming that the screen display is reddish, the red channel value is gradually adjusted through color mapping, gradually reducing it from the initial too high value until it approaches the preset standard value of 5500 Kelvin color temperature. During the correction process, the adjusted color values are constantly compared to see if they meet the requirements to ensure that each layer of adjustment is close to the target. This layer-by-layer adjustment method can effectively avoid color mutations caused by one-time adjustments. For the properties of real-time adjustment and environmental adaptation, the adjusted color values are matched with the light fluctuation dataset. Assuming that the light fluctuation dataset shows that the current ambient light intensity is stable at 600 lux, and the adjusted color value tends to be high-brightness, the matching is optimized according to the light perception requirements, and the brightness output value is appropriately reduced. This matching process can ensure that the screen display is consistent with the ambient light changes and improve visual comfort.

[0094] Optionally, the frequency characteristics of light changes can also be considered during matching. If the ambient light fluctuates frequently in a short period of time, a more conservative adjustment scheme is preferred to avoid discomfort caused by frequent changes in screen output.

[0095] Optionally, data can be recorded in conjunction with the time dimension. For example, if light intensity gradually increases from 300 lux in the morning to 800 lux at noon over the course of a day, this would create a fluctuating data set that includes temporal attributes. This multi-dimensional recording method can fully reflect changes in ambient light.

[0096] As another optional embodiment, after obtaining the final screen output adjustment plan, the color adjustment records in the screen output adjustment plan are extracted. During the extraction, the color change points in the records are classified and annotated to obtain a classified color change dataset. The color change dataset is imported into a pre-established color pattern database. During the import, the dataset is grouped and stored according to the characteristics of ambient light changes, and the storage structure of the grouped data is determined.

[0097] For example, when analyzing color adjustment records in feedback data, one can start with extraction logic. Key change points within the adjustment records, such as significant fluctuations in brightness or color temperature, are identified and categorized as high-priority or low-priority changes. This categorization helps quickly identify adjustment areas that require focus. For example, if a record shows a sudden change in color temperature from 5000 Kelvin to 6000 Kelvin, this change is labeled as a high-priority change point, while a record showing a subtle adjustment in brightness from 100 nits to 105 nits is labeled as a low-priority change point. This categorization provides clear guidance for subsequent data processing. The categorized color change datasets are then grouped and stored based on ambient light variation characteristics. For example, data with ambient light intensity fluctuating between 300 lux and 500 lux is grouped together, while data above 600 lux is grouped together. This grouped storage structure makes the database more organized and facilitates quick matching of related records during subsequent searches.

[0098] Optionally, when designing a grouped storage structure, if the data volume is large, a time dimension can be introduced to aid grouping. For example, suppose the ambient light gradually increases from 200 lux in the morning to 700 lux at noon over the course of a day. Data from different time periods can be stored separately, annotated with time characteristics. This multi-dimensional grouping approach provides a more comprehensive reference for subsequent retrieval and verification, ensuring that adjustment plans align with actual light fluctuations.

[0099] As another optional implementation, if the grouped data storage structure meets the corresponding preset threshold requirements, adjustment records related to the current ambient light changes are extracted from the color pattern database. During the extraction, these records are prioritized according to dynamic monitoring requirements to obtain a sorted set of matching solutions. Based on the sorted set of matching solutions, the adjustment solutions in the set are secondary verified, and parameter adjustments are made during the verification to ensure the consistency of color performance.

[0100] For example, when performing priority sorting, assuming that the current ambient light intensity is 400 lux, historical adjustment records related to this intensity range are extracted first, and records with a frequency of light changes similar to the current time period are placed in front to form a set of sorted matching solutions. The sorted matching solution set is then verified a second time, and the continuity of color performance is optimized by fine-tuning parameters. For example, if the brightness output value in a certain solution is too high, the output parameters need to be gradually adjusted, such as fine-tuning the brightness from 110 nits to 105 nits, and observing whether the adjustment affects the overall color temperature balance. This fine-tuning process ensures the adaptability of the solution in different environments.

[0101] Optionally, the prioritization process can be personalized based on user habits. For example, if a user prefers lower brightness output in a specific lighting environment, the history records that match this preference will be prioritized. This approach improves the personalized matching of the solution and enhances the user experience.

[0102] This solution continuously monitors ambient light fluctuations and analyzes abnormal areas, then performs layered corrections for display deviations that exceed thresholds, enabling precise adaptive adjustment of screen color. This intelligent, real-time display compensates for ambient light changes, ensuring accurate color reproduction under all lighting conditions.

[0103] Example 4 In an embodiment of the present application, an adaptive color shift compensation device for a liquid crystal display is provided.

[0104] Reference Figure 4 , Figure 4 This is a schematic diagram of the terminal structure of the hardware operating environment involved in an embodiment of the present application.

[0105] like Figure 4 As shown, the control terminal may include: a processor 1001, such as a CPU, a network interface 1003, a memory 1004, and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The network interface 1003 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1004 may be a high-speed RAM memory or a non-volatile memory, such as a disk drive. The memory 1004 may also be a storage device independent of the processor 1001.

[0106] Those skilled in the art will understand that Figure 4 The terminal structure shown in the figure does not constitute a limitation to the terminal, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0107] like Figure 4 As shown, the memory 1004 as a computer storage medium may include an operating system, a network communication module, and an adaptive color shift compensation program for a liquid crystal display.

[0108] exist Figure 4 In the hardware structure of the adaptive color cast compensation device for a liquid crystal display, the processor 1001 may call the adaptive color cast compensation program for a liquid crystal display stored in the memory 1004 and perform the following operations: Collect real-time ambient light change data and generate ambient light feature data sets; Analyzing the mapping relationship between the screen color deviation and the light parameters in the ambient light feature data set to determine the interference pattern of the ambient light on the screen color; Building a color law database based on the interference pattern and generating a reference data matrix for real-time color deviation compensation; generating an adaptive color adjustment curve based on the reference data matrix and determining color compensation parameters under different ambient light conditions; A color compensation solution is generated according to the color compensation parameters, and the color presentation of the display screen is adjusted in real time.

[0109] Optionally, the processor 1001 may call an adaptive color shift compensation program for a liquid crystal display screen stored in the memory 1004, and further perform the following operations: Obtaining the difference between the ambient light brightness and the light intensity in the ambient light feature dataset; If the difference value is not within the preset difference threshold range, marking the difference value as an abnormal light interval, and extracting the color temperature distribution characteristics of the abnormal light interval; The synergistic effect between the color temperature distribution characteristics and the light incident angle is analyzed, the interference pattern characteristics that cause the color distortion of the display screen are extracted, and the interference pattern is determined.

[0110] Optionally, the processor 1001 may call an adaptive color shift compensation program for a liquid crystal display screen stored in the memory 1004, and further perform the following operations: Based on the interference pattern, the ambient light feature data set is classified to generate interference types containing color deviation rules, thereby obtaining preliminary classification data; Matching the preliminary classification data with the dynamic change parameters of the ambient light to generate the color law database; Matching the color regularity database with preset association rules to generate color deviation association quantification results; Based on the color deviation correlation quantification result, the real-time ambient light data is compared with the screen color deviation to generate the reference data matrix.

[0111] Optionally, the processor 1001 may call an adaptive color shift compensation program for a liquid crystal display screen stored in the memory 1004, and further perform the following operations: Obtaining reference data content in the reference data matrix, and detecting a deviation between the reference data content and an actual detection value; If the deviation value is greater than the preset deviation value, the historical reference data content, the actual detection value and the screen response data are fused to adjust the reference data matrix.

[0112] Optionally, the processor 1001 may call an adaptive color shift compensation program for a liquid crystal display screen stored in the memory 1004, and further perform the following operations: Classify and match the environmental variables and light conditions in the reference data matrix using preset data mapping rules to generate preliminary mapping data; Obtaining the change of the light condition and the trend of color shift in the preliminary mapping data to generate the adaptive color adjustment curve; If it is detected that the adaptive color adjustment curve deviates from the expected adjustment curve, the adaptive color adjustment curve is corrected, and a compensation parameter range corresponding to the correction is obtained to generate a compensation parameter set; Adaptively matching the compensation parameter set with the light conditions to determine the color compensation parameters.

[0113] Optionally, the processor 1001 may call an adaptive color shift compensation program for a liquid crystal display screen stored in the memory 1004, and further perform the following operations: Dynamically monitor real-time light conditions and obtain at least one environmental variable data set related to light intensity; If the light intensity in the monitored environmental variable data set exceeds a preset light intensity threshold range, the environmental variable data set is compared with the real-time light condition to generate preliminary adjustment data corresponding to the current ambient light; Obtaining a color shift pattern that matches the real-time light condition from a historical database, and correcting the preliminary adjustment data according to the color shift pattern to update the compensation parameter set; The updated compensation parameter set is matched with actual display requirements to determine the color compensation parameters that match the real-time light conditions.

[0114] Optionally, the processor 1001 may call an adaptive color shift compensation program for a liquid crystal display screen stored in the memory 1004, and further perform the following operations: Decomposing the color compensation parameters to obtain at least one adjustment data set associated with screen output; Comparing the adjustment data set with the expected display requirements to generate the color compensation solution; generating an adjustment instruction according to the color compensation scheme, and controlling the color presentation content of the display screen according to the adjustment instruction; The color value of the display screen is dynamically monitored, and the adjustment instruction is corrected according to the monitoring result to complete the real-time adjustment of the color presentation of the display screen.

[0115] Optionally, the processor 1001 may call an adaptive color shift compensation program for a liquid crystal display screen stored in the memory 1004, and further perform the following operations: Continuously monitoring changes in ambient light, generating a light fluctuation data set, and determining a fluctuation range of the light fluctuation data set; Obtaining the display screen area corresponding to the fluctuation range exceeding the preset deviation range, and obtaining the screen deviation distribution; According to the screen deviation distribution, color correction is performed layer by layer on the display screen area to complete the color deviation adjustment of the display screen.

[0116] In addition, to achieve the above-mentioned purpose, an embodiment of the present invention also provides a device, including a memory, a processor, and an adaptive color cast compensation program for a liquid crystal display screen stored in the memory and runnable on the processor. When the processor executes the adaptive color cast compensation program for the liquid crystal display screen, the adaptive color cast compensation method for the liquid crystal display screen as described above is implemented.

[0117] In addition, to achieve the above-mentioned purpose, an embodiment of the present invention further provides a computer-readable storage medium, on which a program for adaptive color cast compensation for a liquid crystal display is stored. When the program for adaptive color cast compensation for a liquid crystal display is executed by a processor, the method for adaptive color cast compensation for a liquid crystal display as described above is implemented.

[0118] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0120] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0122] It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claim. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The present application may be implemented by means of hardware comprising several distinct components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second and third etc. does not indicate any order. These words may be interpreted as names.

[0123] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0124] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present application fall within the scope of the claims and their equivalents, the present application is intended to include such modifications and variations.

Claims

1. A method for adaptive color shift compensation of a liquid crystal display, characterized in that: The steps of the adaptive color shift compensation method for a liquid crystal display screen include: Collect real-time ambient light change data and generate ambient light feature data sets; Analyzing the mapping relationship between the screen color deviation and the light parameters in the ambient light feature data set to determine the interference pattern of the ambient light on the screen color; Building a color law database based on the interference pattern and generating a reference data matrix for real-time color deviation compensation; generating an adaptive color adjustment curve based on the reference data matrix and determining color compensation parameters under different ambient light conditions; A color compensation solution is generated according to the color compensation parameters, and the color presentation of the display screen is adjusted in real time.

2. The method for adaptive color shift compensation of a liquid crystal display according to claim 1, wherein: The step of analyzing the mapping relationship between the screen color deviation and the light parameters in the ambient light feature data set to determine the interference pattern of the ambient light on the screen color includes: Obtaining the difference between the ambient light brightness and the light intensity in the ambient light feature dataset; If the difference value is not within the preset difference threshold range, marking the difference value as an abnormal light interval, and extracting the color temperature distribution characteristics of the abnormal light interval; The synergistic effect between the color temperature distribution characteristics and the light incident angle is analyzed, the interference pattern characteristics that cause the color distortion of the display screen are extracted, and the interference pattern is determined.

3. The method for adaptive color shift compensation of a liquid crystal display according to claim 1, wherein: The step of constructing a color law database according to the interference pattern and generating a reference data matrix for real-time color deviation compensation includes: Based on the interference pattern, the ambient light feature data set is classified to generate interference types containing color deviation rules, thereby obtaining preliminary classification data; Matching the preliminary classification data with the dynamic change parameters of the ambient light to generate the color law database; Matching the color regularity database with preset association rules to generate color deviation association quantification results; Based on the color deviation correlation quantification result, the real-time ambient light data is compared with the screen color deviation to generate the reference data matrix.

4. The method for adaptive color shift compensation of a liquid crystal display according to claim 3, wherein: After the step of comparing the real-time ambient light data with the screen color deviation based on the color deviation correlation quantification result to generate the reference data matrix, the method further includes: Obtaining reference data content in the reference data matrix, and detecting a deviation between the reference data content and an actual detection value; If the deviation value is greater than the preset deviation value, the historical reference data content, the actual detection value and the screen response data are fused to adjust the reference data matrix.

5. The method for adaptive color shift compensation of a liquid crystal display according to claim 1, wherein: The step of generating an adaptive color adjustment curve based on the reference data matrix and determining color compensation parameters under different ambient light conditions includes: Classify and match the environmental variables and light conditions in the reference data matrix using preset data mapping rules to generate preliminary mapping data; Obtaining the change of the light condition and the trend of color shift in the preliminary mapping data to generate the adaptive color adjustment curve; If it is detected that the adaptive color adjustment curve deviates from the expected adjustment curve, the adaptive color adjustment curve is corrected, and a compensation parameter range corresponding to the correction is obtained to generate a compensation parameter set; Adaptively matching the compensation parameter set with the light conditions to determine the color compensation parameters.

6. The method for adaptive color shift compensation of a liquid crystal display according to claim 5, wherein: After the step of adaptively matching the compensation parameter set with the light conditions to determine the color compensation parameters, the method further includes: Dynamically monitor real-time light conditions and obtain at least one environmental variable data set related to light intensity; If the light intensity in the monitored environmental variable data set exceeds a preset light intensity threshold range, the environmental variable data set is compared with the real-time light condition to generate preliminary adjustment data corresponding to the current ambient light; Obtaining a color shift pattern that matches the real-time light condition from a historical database, and correcting the preliminary adjustment data according to the color shift pattern to update the compensation parameter set; The updated compensation parameter set is matched with actual display requirements to determine the color compensation parameters that match the real-time light conditions.

7. The method for adaptive color shift compensation of a liquid crystal display according to claim 1, wherein: The step of generating a color compensation solution according to the color compensation parameters and adjusting the color presentation of the display screen in real time includes: Decomposing the color compensation parameters to obtain at least one adjustment data set associated with screen output; Comparing the adjustment data set with the expected display requirements to generate the color compensation solution; generating an adjustment instruction according to the color compensation scheme, and controlling the color presentation content of the display screen according to the adjustment instruction; The color value of the display screen is dynamically monitored, and the adjustment instruction is corrected according to the monitoring result to complete the real-time adjustment of the color presentation of the display screen.

8. The method for adaptive color shift compensation of a liquid crystal display according to claim 1, wherein: After the step of generating a color compensation solution according to the color compensation parameters and adjusting the color presentation of the display screen in real time, the method includes: Continuously monitoring changes in ambient light, generating a light fluctuation data set, and determining a fluctuation range of the light fluctuation data set; Obtaining the display screen area corresponding to the fluctuation range exceeding the preset deviation range, and obtaining the screen deviation distribution; According to the screen deviation distribution, color correction is performed layer by layer on the display screen area to complete the color deviation adjustment of the display screen.

9. A terminal device, characterized in that: The invention comprises a memory, a processor, and an adaptive color cast compensation program for a liquid crystal display screen stored in the memory and executable on the processor. When the processor executes the adaptive color cast compensation program for the liquid crystal display screen, the method described in any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores an adaptive color cast compensation program for a liquid crystal display screen. When the adaptive color cast compensation program for a liquid crystal display screen is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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