Display control method and system of liquid crystal display screen

Abstract

The invention provides a display control method and system for a liquid crystal display screen, and the method comprises the steps: carrying out the nonlinear spectrum mapping processing of an input RGB drive value, and obtaining a theoretical emission spectrum through combining with the response characteristics of liquid crystal molecules; calculating a reflection spectrum component in the multilayer structure according to the ambient light spectrum, and superposing the reflection spectrum component with the theoretical emission spectrum to obtain an actual observation spectrum; calculating a difference value between the actual observation spectrum and the target spectrum, and converting the difference value into an RGB correction value through a constraint optimization algorithm to obtain an RGB driving value after ambient light compensation; and calculating actual white point color coordinates, and adjusting the actual white point color coordinates to a standard white point position through a progressive white point migration algorithm. Display parameters can be dynamically adjusted according to real-time ambient light conditions, the influence of ambient light reflection on colors is effectively compensated, meanwhile, color temperature consistency and color accuracy are ensured through white point correction, the display quality under different ambient lights is remarkably improved, and the visual experience of a user is improved.

Description

Technical Field

[0001] The present invention relates to the field of display control technology, and in particular to a display control method and system for a liquid crystal display screen. Background Art

[0002] The display quality of LCD screens varies significantly under varying ambient lighting conditions, impacting the user's visual experience. Traditional LCD display control technology primarily relies on fixed RGB drive values for display output, failing to fully consider the impact of ambient light on the display. When ambient light strikes the surface of an LCD screen, it reflects within the multi-layer structure. This reflected light, combined with the light emitted by the display itself, causes a discrepancy between the observed spectrum and the theoretical emission spectrum.

[0003] In the existing technology, most display control methods lack accurate modeling and compensation mechanisms for ambient light reflection, and are unable to dynamically adjust RGB drive values according to real-time ambient light conditions. This leads to problems such as reduced display contrast and color distortion under strong ambient light, seriously affecting display quality and user experience. Summary of the Invention

[0004] The main purpose of the present invention is to solve the technical problem that the existing liquid crystal display control technology lacks ambient light reflection modeling and dynamic compensation mechanism, resulting in unstable display quality under different ambient light conditions; A first aspect of the present invention provides a display control method for a liquid crystal display screen, the display control method for a liquid crystal display screen comprising: The input RGB driving values are processed by nonlinear spectral mapping based on the mapping relationship between liquid crystal transmittance and backlight spectrum. The theoretical emission spectrum of each pixel is obtained by combining the response characteristics of liquid crystal molecules and temperature compensation parameters. Calculating the reflected spectral component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtaining the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflected spectral component; Calculating the spectral compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, and converting the spectral compensation amount into a correction amount for the RGB drive value through a constrained optimization algorithm to obtain the RGB drive value after ambient light compensation; The actual white point color coordinates of the display screen are calculated according to the RGB driving values after the ambient light compensation, and the actual white point color coordinates are adjusted to the standard white point position through a progressive white point migration algorithm.

[0005] Optionally, in a first implementation of the first aspect of the present invention, the nonlinear spectral mapping processing is performed on the input RGB drive values based on the mapping relationship between the liquid crystal transmittance and the backlight spectrum, and the theoretical emission spectrum of each pixel is obtained by combining the response characteristics of the liquid crystal molecules and the temperature compensation parameters, including: Calculate the RGB three-channel transmittance components of each pixel point according to the input RGB driving value through the mapping relationship between the liquid crystal transmittance and the backlight spectrum; Performing nonlinear response correction on the RGB three-channel transmittance components according to the response characteristics of the liquid crystal molecules, and performing temperature drift compensation on the corrected transmittance components in combination with temperature compensation parameters to obtain the transmittance coefficient under actual working conditions; The transmittance coefficient is multiplied by the backlight spectrum on a wavelength-by-wavelength basis and a spectrum synthesis calculation is performed to obtain a theoretical emission spectrum of each pixel point.

[0006] Optionally, in a second implementation of the first aspect of the present invention, calculating the reflection spectrum component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtaining the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflection spectrum component includes: Calculating the propagation path and scattering characteristics of the detected ambient light in each layer structure according to the optical parameters of the multi-layer structure of the liquid crystal display screen to obtain the reflection spectrum component of the ambient light in the multi-layer structure; Performing spectral superposition operation on the theoretical emission spectrum and the reflection spectrum components according to the wavelength correspondence, and weighting the superposition results by a dynamic weight allocation algorithm to obtain a weighted superposition spectrum; The spectrum output of each pixel under the current ambient light condition is calculated based on the weighted superposition spectrum to obtain the actual observed spectrum of each pixel.

[0007] Optionally, in a third implementation of the first aspect of the present invention, calculating the propagation path and scattering characteristics of the detected ambient light in each layer structure based on optical parameters of the multi-layer structure of the liquid crystal display screen to obtain the reflection spectral components of the ambient light in the multi-layer structure includes: Analyzing the optical characteristics of the ambient light according to the detected incident angle and polarization state, and calculating the optical reflection parameters of the interfaces of the polarizer layer, liquid crystal layer, and color filter layer in the multi-layer structure of the liquid crystal display screen in combination with the refractive index parameters of the polarizer layer, liquid crystal layer, and color filter layer; Performing layer-by-layer ray tracing calculations on the ambient light in each layer structure according to the optical reflection parameters, analyzing the scattering characteristics of the ambient light through Rayleigh scattering and Mie scattering models, and obtaining the scattering spectrum distribution of the ambient light in each layer structure; The scattering spectrum distribution is weighted according to the optical thickness of each layer structure, and the interaction effect of the scattering spectrum of each layer is calculated by an interlayer coupling algorithm to obtain the scattering spectrum contribution of each layer structure; The scattered spectrum contribution is accumulated and superimposed according to the spectrum weight, and the overall reflection contribution of the ambient light is calculated through spectrum normalization processing to obtain the reflection spectrum component of the ambient light in the multilayer structure.

[0008] Optionally, in a fourth implementation of the first aspect of the present invention, calculating the spectral compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, converting the spectral compensation amount into a correction amount for the RGB drive value through a constrained optimization algorithm, and obtaining the RGB drive value after ambient light compensation includes: Calculating the wavelength-by-wavelength difference between the actual observed spectrum and the preset target spectrum, processing the difference results through a spectrum analysis algorithm to obtain the spectral compensation required for each pixel point; The spectral compensation amount is input into the constrained optimization algorithm, and the correction amount of the RGB drive value is calculated according to the hardware constraints of the liquid crystal display. The correction amount is optimized through a multi-time scale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB drive value correction amount; The optimal RGB driving value correction amount is superimposed on the original RGB driving value to obtain the RGB driving value after ambient light compensation.

[0009] Optionally, in a fifth implementation of the first aspect of the present invention, inputting the spectral compensation amount into a constrained optimization algorithm, calculating a correction amount for the RGB drive value based on hardware constraints of the liquid crystal display, and optimizing the correction amount through a multi-time-scale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB drive value correction amount includes: Inputting the spectral compensation amount into the constraint optimization algorithm, and calculating the initial RGB drive value correction amount of the RGB drive value through constraint solving according to the constraint conditions established by the hardware limitation conditions of the liquid crystal display screen; Performing time-frequency decomposition on the initial RGB drive value correction using the multi-time-scale modulation strategy, modulating each time-scale component in the time-frequency decomposition process according to the response characteristics of the liquid crystal molecules to obtain a time-domain optimized correction; Performing the RGB cross-coupling modulation on the time domain optimization correction amount according to the spectral coupling characteristics between the RGB three channels to obtain a cross-modulation correction amount; The stability of the cross-modulation correction amount is verified, and the unstable component is optimized and adjusted through convergence analysis to obtain the optimal RGB drive value correction amount.

[0010] Optionally, in a sixth implementation of the first aspect of the present invention, calculating the actual white point color coordinates of the display screen based on the ambient light compensated RGB drive values, and adjusting the actual white point color coordinates to the standard white point position using a progressive white point migration algorithm includes: Calculating the actual white point color coordinates of the display screen through CIE color space transformation according to the RGB driving values after ambient light compensation; Calculating the coordinate difference between the actual white point color coordinates and the preset standard white point position, determining the migration path parameters according to the display content characteristics using the progressive white point migration algorithm, and obtaining the white point migration control parameters; Performing a white balance matrix transformation on the ambient light compensated RGB driving value according to the white point migration control parameter to obtain a white point corrected RGB driving value; A PWM control signal is generated according to the RGB driving value after the white point correction, and is output to each pixel unit of the liquid crystal display screen for display control.

[0011] A second aspect of the present invention provides a display control system for a liquid crystal display screen, the display control system for the liquid crystal display screen comprising: The spectrum mapping module is used to perform nonlinear spectrum mapping on the input RGB drive values based on the mapping relationship between liquid crystal transmittance and backlight spectrum, and obtain the theoretical emission spectrum of each pixel by combining the response characteristics of liquid crystal molecules and temperature compensation parameters; An environmental compensation module is used to calculate the reflection spectrum component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtain the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflection spectrum component; A spectral correction module is used to calculate the spectral compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, and convert the spectral compensation amount into a correction amount of the RGB drive value through a constrained optimization algorithm to obtain the RGB drive value after ambient light compensation; The white point adjustment module is used to calculate the actual white point color coordinates of the display screen according to the RGB driving value after the ambient light compensation, and adjust the actual white point color coordinates to the standard white point position through a progressive white point migration algorithm.

[0012] The display control method and system for the above-mentioned liquid crystal display screen performs nonlinear spectral mapping on the input RGB drive values, combining them with the response characteristics of liquid crystal molecules to obtain a theoretical emission spectrum. The reflected spectral components in the multilayer structure are calculated based on the ambient light spectrum, and superimposed with the theoretical emission spectrum to obtain the actual observed spectrum. The difference between the actual observed spectrum and the target spectrum is calculated and converted into RGB correction values using a constrained optimization algorithm to obtain the RGB drive values after ambient light compensation. The actual white point color coordinates are calculated and adjusted to the standard white point position using a progressive white point migration algorithm. This invention can dynamically adjust display parameters based on real-time ambient light conditions, effectively compensating for the effects of ambient light reflection on color. While ensuring color temperature consistency and color accuracy through white point correction, it significantly improves display quality under varying ambient light conditions and enhances the user's visual experience.

[0013] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0014] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of a first embodiment of a display control method for a liquid crystal display screen according to an embodiment of the present invention; Figure 2 FIG. 1 is a schematic diagram of an embodiment of a display control system of a liquid crystal display screen according to an embodiment of the present invention. DETAILED DESCRIPTION

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] The terms "including," "having," and any variations thereof, as used in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to the process, method, product, or device.

[0018] To facilitate understanding of this embodiment, a display control method for a liquid crystal display screen disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, this method includes the following steps: 101. Perform nonlinear spectral mapping on the input RGB driving values based on the mapping relationship between the liquid crystal transmittance and the backlight spectrum, and obtain the theoretical emission spectrum of each pixel by combining the response characteristics of the liquid crystal molecules and the temperature compensation parameters; In one embodiment of the present invention, the input RGB driving values are subjected to nonlinear spectral mapping processing based on the mapping relationship between the liquid crystal transmittance and the backlight spectrum, and the theoretical emission spectrum of each pixel is obtained in combination with the response characteristics of the liquid crystal molecules and the temperature compensation parameters, including: calculating the RGB three-channel transmittance components of each pixel according to the input RGB driving values through the mapping relationship between the liquid crystal transmittance and the backlight spectrum; performing nonlinear response correction on the RGB three-channel transmittance components according to the response characteristics of the liquid crystal molecules, and performing temperature drift compensation on the corrected transmittance components in combination with the temperature compensation parameters to obtain the transmittance coefficient under actual working conditions; performing wavelength-by-wavelength multiplication operation and spectral synthesis calculation on the transmittance coefficient and the backlight spectrum to obtain the theoretical emission spectrum of each pixel.

[0019] Specifically, the spectral mapping process for the LCD begins with the input of RGB drive values and executes a detailed calculation process. The calculation of the transmittance components of the three RGB channels first uses the input RGB values as indices to retrieve the corresponding base transmittance from a pre-calibrated LCD transmittance lookup table. The red channel is calculated by dividing the R value by 255 to obtain a normalized value, which is then multiplied by the index range of the lookup table to obtain the specific lookup table location. The system reads the transmittance value stored at this location as the base transmittance for the red channel. The green and blue channels use the same calculation method to obtain their respective base transmittance values. Next, the system reads the backlight spectrum data, which stores the light intensity value at each wavelength indexed by wavelength. The system multiplies the backlight spectrum by the spectral transmittance of the color filter on a wavelength-by-wavelength basis to obtain the effective backlight spectrum for each channel. The effective backlight spectrum of the red channel is calculated by multiplying the backlight spectrum value at each wavelength by the transmittance of the red filter at the corresponding wavelength. The same method is used for the green and blue channels. The system then convolves each channel's base transmittance with the corresponding effective backlight spectrum. Specifically, the base transmittance is used as a weighting factor and multiplied by each wavelength point of the effective backlight spectrum to obtain the channel's transmittance distribution at each wavelength. Finally, the transmittance distribution is integrated using the trapezoidal integration method, and the integrated result is divided by the spectral range to obtain the final transmittance component of the channel.

[0020] Specifically, nonlinear response correction is implemented using a lookup table combined with cubic spline interpolation to correct the transmittance component. The system establishes a response characteristic lookup table that records the correspondence between theoretical transmittance and actual measured transmittance. The data in the table is obtained by actually measuring the optical response of the liquid crystal under different driving voltages. For the input transmittance component value, the system first locates two adjacent data points in the lookup table and then uses the cubic spline interpolation algorithm to calculate the precise correction coefficient. The cubic spline interpolation calculation process is to establish a piecewise cubic polynomial. The system constructs the coefficients of the cubic equation based on the values and derivatives of the four adjacent data points, and then substitutes the transmittance component values into the equation to calculate the corrected value. Temperature compensation is implemented using a two-dimensional linear interpolation algorithm. The system establishes a two-dimensional temperature-transmittance lookup table with transmittance values on the horizontal axis and temperature values on the vertical axis. The table stores the corresponding temperature compensation coefficients. When a specific transmittance and current temperature are input, the system locates four adjacent grid points in the two-dimensional table and then performs bilinear interpolation. The specific process of bilinear interpolation is to first perform two linear interpolations on the horizontal axis to obtain two intermediate values, and then perform linear interpolation on these two intermediate values on the vertical axis to obtain the final compensation coefficient. The system multiplies the compensation coefficient with the response-corrected transmittance to obtain the final transmittance coefficient that takes into account the influence of temperature.

[0021] Specifically, the wavelength-by-wavelength product operation is implemented by organizing the transmittance coefficients and backlight spectrum into floating-point arrays of length 401, corresponding to the wavelength range of 380 nm to 780 nm. The system first expands the transmittance coefficients to a full spectral distribution, using a Gaussian function model to describe how transmittance varies at different wavelengths. The red channel's transmittance distribution is centered at 630 nm with a half-width at half-maximum of 80 nm, the green channel at 530 nm, and the blue channel at 460 nm. The transmittance distribution is calculated using a Gaussian function formula, using the transmittance coefficient as the amplitude parameter and the center wavelength and half-width at half-maximum as shape parameters. Transmittance values are calculated at 401 wavelengths. The system then performs an element-by-element multiplication, multiplying the transmittance distribution array with the corresponding values in the backlight spectrum array to obtain the spectral output for that channel at each wavelength. Spectral synthesis is calculated using a weighted average method, calculating weight coefficients based on the spatial arrangement of the subpixels. The area weights for the red, green, and blue subpixels are determined through geometric measurements. The synthesis process linearly combines the spectral output arrays of the three channels according to the weight coefficients. The specific implementation is to multiply the red spectrum by the red weight, the green spectrum by the green weight, and the blue spectrum by the blue weight. The three result arrays are then added element by element to obtain the synthesized spectrum.

[0022] Specifically, the process of generating a theoretical emission spectrum involves two steps: normalization and photometric correction. Normalization uses a peak normalization method. The system finds the maximum value in the synthesized spectrum and then divides the entire spectral array by this maximum value, normalizing the spectral data to a range of 0 to 1. Photometric correction is achieved by calculating the weighted integral of the spectrum's luminous efficacy function. The system multiplies the normalized spectrum by the CIE standard luminous efficacy function wavelength by wavelength and then uses the trapezoidal integration method to calculate the integral value to obtain the luminous flux. The system compares the calculated luminous flux with the expected luminous flux based on the RGB input values. If there is any deviation, a scaling factor is calculated to correct the spectrum. The final theoretical emission spectrum is stored as structured data, consisting of a wavelength array, a spectral intensity array, and spectral characteristic parameters, including color parameters such as dominant wavelength, purity, and chromaticity coordinates. The system also calculates statistical characteristics of the spectrum, including parameters such as the centroid wavelength, variance, and skewness, which are used in subsequent spectral analysis and matching algorithms.

[0023] 102. Calculate the reflection spectrum component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtain the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflection spectrum component; In one embodiment of the present invention, the calculation of the reflected spectral components of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtaining the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflected spectral components include: calculating the propagation path and scattering characteristics of the ambient light in each layer structure based on the optical parameters of the multi-layer structure of the liquid crystal display screen to obtain the reflected spectral components of the ambient light in the multi-layer structure; performing a spectral superposition operation on the theoretical emission spectrum and the reflected spectral components according to the wavelength correspondence, and weighting the superposition results through a dynamic weight allocation algorithm to obtain a weighted superposition spectrum; and calculating the spectral output of each pixel under current ambient light conditions based on the weighted superposition spectrum to obtain the actual observed spectrum of each pixel.

[0024] Specifically, the calculation of the reflected spectral components of ambient light in the multi-layer structure of an LCD begins with ambient light spectrum measurement data. The system first reads ambient light data detected by a spectrometer. This data, indexed by wavelength, records the light intensity values at each wavelength point in the range of 380 nanometers to 780 nanometers. The propagation path of ambient light is calculated using a ray tracing algorithm. The system builds a three-dimensional optical model based on the parameters of the LCD's multi-layer structure. This model includes key structures such as the polarizer layer, liquid crystal layer, color filter layer, and backlight guide plate. Each layer has specific optical parameters, including physical properties such as refractive index, thickness, surface roughness, and scattering coefficient. The system uses ambient light as the incident light source and calculates the refraction and reflection behavior of light at the interfaces of each layer according to Snell's law. The application of the law of refraction takes into account the complex refractive index of each layer material. The real part describes the change in light propagation speed, while the imaginary part describes the absorption attenuation of light. The propagation of light in the polarizer layer is calculated using the Jones matrix method. The system represents the polarization state of the incident light as a Jones vector, which is then multiplied by the polarizer's Jones matrix to obtain the polarization state and intensity of the transmitted light. Optical calculations for the liquid crystal layer require consideration of the tilt and twist angle distribution of the liquid crystal molecules. The system uses a 4×4 transfer matrix method to calculate the propagation of polarized light in the liquid crystal layer, which can account for the birefringence and optical rotation effects of liquid crystals. Scattering properties are calculated using a combination of Mie and Rayleigh scattering theories. The system selects the appropriate scattering model based on the size distribution of particles in each layer. The Rayleigh scattering model is used when the particle size is much smaller than the wavelength of light, and the Mie scattering model is used when the particle size is close to the wavelength of light.

[0025] Specifically, the scattering calculation is implemented using the Monte Carlo method to simulate the random scattering of a large number of photons in a multilayer structure. The system generates random numbers to determine the scattering direction and scattering probability of the photons. The scattering probability is calculated based on the scattering cross section of each layer and the photon energy. Each photon undergoes multiple scattering events during propagation. The system records the photon's propagation trajectory and energy change, and ultimately calculates the energy of all backscattered photons to obtain the reflected spectral components. The calculation of the reflected spectral components also requires consideration of Fresnel reflection at each layer's interface. The system calculates the reflection coefficient based on the incident angle and polarization state, and then superimposes the contribution of interface reflection with the contribution of bulk scattering. The Fresnel reflection coefficient is calculated separately for s- and p-polarization components. The system calculates the reflectivity based on the incident angle and the refractive index difference between the two media, and then performs a weighted average based on the polarization ratio of the incident light. The total reflectance spectrum of the multilayer structure is calculated layer by layer, starting from the outermost layer, while also accounting for multiple reflections and interference effects between layers. The interference effect is calculated using thin film optics theory, calculating the phase difference of the reflected light between each layer and then performing complex operations to obtain the total reflected intensity after interference. The resulting reflection spectrum component is a 401-dimensional array, where each element corresponds to the intensity of reflected light at a specific wavelength. This array fully describes the reflection characteristics of ambient light in the multi-layer structure of the LCD display.

[0026] Specifically, the theoretical emission spectrum and reflectance spectrum components are superimposed using a wavelength-by-wavelength addition method to achieve spectral synthesis. The system organizes the theoretical emission and reflectance spectrum components into arrays of equal length, ensuring that the two spectral data correspond exactly in the wavelength dimension. The superposition calculation is implemented by directly adding the values at corresponding positions in the two spectral arrays to obtain a preliminary superimposed spectral result. However, direct addition ignores the physical differences between the two light sources, necessitating the application of a dynamic weighting algorithm. The dynamic weighting algorithm calculates weight coefficients based on the ratio between ambient light intensity and display brightness. The ambient light intensity is integrated over the reflectance spectrum components to obtain the total reflected luminous flux, while the display brightness is integrated over the theoretical emission spectrum to obtain the total emitted luminous flux. Weight calculation uses a sigmoid function model, which provides smooth weight changes under different luminous flux ratios, avoiding display discontinuities caused by sudden changes in weights. The weighting is implemented by calculating an ambient light weight and an emitted light weight, the sum of which equals 1. The system then multiplies the reflected light spectrum components by the ambient light weight and the theoretical emission spectrum by the emitted light weight. The two weighted results are then added together to produce the weighted superimposed spectrum. The weighted superposition spectrum reflects the comprehensive optical output of the pixel under the current ambient light conditions. This spectrum includes both the light actively emitted by the display and the contribution of ambient light reflection.

[0027] Specifically, the calculation of the actual observed spectrum at each pixel requires further consideration of observation conditions and visual perception characteristics. The system calculates a field of view correction factor based on the observation angle and distance. This factor describes the impact of different observation geometry conditions on spectral observation. The field of view correction factor is calculated using Lambert's cosine law. The system calculates the cosine value based on the observation angle and then applies this value to the weighted superposition spectrum. The effect of observation distance is accounted for using the inverse square law. The system divides the weighted superposition spectrum by the square of the observation distance to obtain a distance-corrected spectrum. The CIE standard observer function is used to correct for human visual characteristics. The system convolves the corrected spectrum with the spectral tristimulus value function of the CIE 1931 standard observer to obtain an observed spectrum that conforms to human visual characteristics. This convolution operation is implemented by wavelength-by-wavelength multiplication of the spectral data with the observer function and then integrating over the entire visible light range to obtain the X, Y, and Z tristimulus values. The final observed spectrum is obtained by converting the tristimulus values back into a spectral distribution. The system uses a spectral reconstruction algorithm to map the X, Y, and Z values back to the spectral domain. The spectral reconstruction algorithm uses pre-trained spectral basis functions, linearly combining the basis functions with the tristimulus values as coefficients to reconstruct a complete spectral distribution. The generation of the actual observed spectrum also needs to consider the color gamut limitations of the display device. The system checks whether the reconstructed spectrum exceeds the device's color gamut. If so, a color gamut mapping algorithm is used to adjust the spectrum to within the displayable range. The color gamut mapping uses the minimum color difference criterion. The system searches for the point on the device's color gamut boundary that has the smallest color difference from the target spectrum, and then uses the spectrum corresponding to that point as the final actual observed spectrum. Through this calculation method that comprehensively considers ambient light reflection, display emission, observation conditions, and visual characteristics, the system can accurately predict the spectral performance of each pixel in the actual usage environment. This spectral data provides accurate basic information for subsequent color compensation and display optimization.

[0028] Furthermore, the step of calculating the propagation path and scattering characteristics of the detected ambient light in each layer structure based on the optical parameters of the multi-layer structure of the liquid crystal display screen to obtain the reflected spectral component of the ambient light in the multi-layer structure includes: analyzing the optical characteristics of the ambient light according to the incident angle and polarization state of the detected ambient light, and calculating the optical reflection parameters of the interfaces of each layer in combination with the refractive index parameters of the polarizer layer, liquid crystal layer, and color filter layer in the multi-layer structure of the liquid crystal display screen; performing layer-by-layer ray tracing calculations on the ambient light in each layer structure based on the optical reflection parameters, analyzing the scattering characteristics of the ambient light through Rayleigh scattering and Mie scattering models, and obtaining the scattered spectral distribution of the ambient light in each layer structure; weighting the scattered spectral distribution according to the optical thickness of each layer structure, calculating the interaction effect of the scattered spectra of each layer through an interlayer coupling algorithm, and obtaining the scattered spectral contribution of each layer structure; and accumulating and superimposing the scattered spectral contributions according to the spectral weights, calculating the overall reflection contribution of the ambient light through spectral normalization, and obtaining the reflected spectral component of the ambient light in the multi-layer structure.

[0029] Specifically, the system uses an angle sensor to detect the incident direction of ambient light, decomposing the incident angle in three-dimensional space into two components: the zenith angle and the azimuth angle. The zenith angle describes the angle between the light and the display normal, while the azimuth angle describes the projection direction of the light in the horizontal plane. The incident angle is measured using a multi-point photodetector array. The system arranges multiple photodiodes on the display surface and calculates the incident angle by comparing the differences in light intensity received by each detector. Polarization is detected using a rotating polarizer. The system inserts a rotatable polarizer into the ambient light path. By continuously rotating the polarizer and recording the changes in the transmitted light intensity, the system analyzes the degree of polarization and polarization direction of the ambient light. The degree of polarization refers to the proportion of the polarized light component to the total light intensity, while the polarization direction refers to the direction of the vibration plane of linearly polarized light. These two parameters fully describe the polarization characteristics of the incident light. The optical parameters of the multilayer structure of an LCD display include physical properties such as the complex refractive index, thickness, and surface characteristics of each layer. The refractive index parameter of the polarizer layer is measured using an ellipsometer. This parameter has different values at different wavelengths, and the system creates a wavelength-refractive index correspondence table to store this data. The refractive index of the liquid crystal layer is anisotropic, with a significant difference between the refractive index of ordinary light and the refractive index of extraordinary light. The system measures and stores these two parameters separately. The refractive index parameters of the color filter layer are determined according to the optical constants of the filter material. The red, green, and blue filters have different refractive index distributions. The optical reflection parameters of each layer interface are calculated using the Fresnel reflection law. The system calculates the reflection coefficient based on the incident angle, polarization state, and the refractive index difference between the two adjacent layers of material. The Fresnel reflection coefficient is divided into two components: s-polarization and p-polarization. S-polarization refers to polarized light with the electric field vibration direction perpendicular to the incident plane, and p-polarization refers to polarized light with the electric field vibration direction parallel to the incident plane. The system calculates the reflection coefficients under these two polarization states separately, and then performs a weighted average based on the polarization ratio of the incident light to obtain the total reflection coefficient.

[0030] Specifically, layer-by-layer ray tracing calculations use a ray tracing algorithm to simulate the propagation of light through a multilayer structure. The system represents the incident light as a ray object with a starting point, direction, and energy. When the ray reaches the first interface, the energy distribution of the reflected and transmitted light rays is determined based on the previously calculated optical reflection parameters. The direction of the reflected ray is calculated according to the law of reflection, with the angle of incidence equal to the angle of reflection, and the reflected ray is within the incident plane. The direction of the transmitted ray is calculated according to the law of refraction, with the system calculating the angle of refraction based on the ratio of the refractive indices of the two media and the angle of incidence. Light propagation through each layer of the medium must account for absorption attenuation. The system calculates energy loss based on the absorption coefficient of the medium and the propagation distance. The absorption coefficient is an inherent property of the material that describes the rate of energy attenuation during light propagation. Scattering characteristics are analyzed using Rayleigh scattering and Mie scattering theories, respectively, for scattering particles of different sizes. Rayleigh scattering is applicable when the scattering particle size is much smaller than the wavelength of light. The scattering intensity is inversely proportional to the fourth power of the wavelength, explaining why short-wavelength light is more easily scattered than long-wavelength light. Mie scattering is applicable to situations where the size of the scattering particles is close to or larger than the wavelength of light. The scattering characteristics need to be calculated using the complex Mie scattering formula, which takes into account the size, shape, and complex refractive index of the particles. The system automatically selects an appropriate scattering model based on the size distribution of the particles in each layer. When the average particle radius is less than one-tenth of the wavelength of light, the Rayleigh scattering model is used; otherwise, the Mie scattering model is used. The scattering calculation is implemented using a statistical method. The system randomly generates a large number of scattering events in each layer, and the probability of each scattering event is calculated based on the scattering cross section and particle density. The scattering spectral distribution is obtained by accumulating the contributions of all scattering events. The system records the scattered light intensity at each wavelength to form complete scattering spectrum data.

[0031] Specifically, the weighted processing of the scattered spectrum distribution is performed by calculating a weighting coefficient based on the optical thickness of each layer. Optical thickness is the actual propagation distance of light in a medium multiplied by the medium's refractive index. This parameter describes the optical path difference of light in the medium. The system calculates the optical thickness of each layer and applies it as a weighting coefficient to the scattered spectrum distribution of that layer. Weighted calculations are implemented by multiplying the scattered spectrum array by the optical thickness value to obtain a modified scattered spectrum that accounts for the influence of layer thickness. The interlayer coupling algorithm is used to calculate the interaction between the scattered spectra of each layer. This interaction arises from multiple scattering and optical interference effects between layers. The coupling calculation uses a transfer matrix approach. The system establishes an optical transfer matrix between each layer, which describes the energy transfer relationship when light propagates from one layer to another. The elements of the transfer matrix are calculated based on the transmittance, reflectivity, and phase relationship between the layers. The system multiplies the transfer matrices of each layer in sequence to obtain the total transfer matrix for the entire multilayer structure. The calculation of the coupling effect also requires different treatments for coherent and incoherent scattering. Coherent scattering maintains the phase relationship of light waves and requires complex number operations, while incoherent scattering only considers the superposition of light intensities and requires real number operations. The system automatically selects a calculation method based on the comparison of the correlation length of the scattering particles and the coherence length of the light. The scattering spectrum contribution of each layer is obtained by solving the transfer matrix equations. This contribution represents the independent contribution of each layer to the total scattering spectrum.

[0032] Specifically, the cumulative superposition of scattered spectral contributions uses a weighted summation method to calculate the total reflectance contribution of ambient light. The system first determines the spectral weight of each layer's contribution, calculated based on the layer's spatial position, material properties, and optical importance. Layers closer to the surface are assigned higher weights because they have a more direct visual impact on the observer. The calculation of spectral weights also takes into account the optical constants of each layer's material. Layers with higher refractive indices scatter and reflect light more strongly and are therefore assigned higher weights. Cumulative superposition is implemented by multiplying each layer's scattered spectral contribution by its corresponding spectral weight and then summing all weighted results over the wavelength dimension. This summation ensures energy conservation. The system checks whether the total energy of the superposition result exceeds the incident light energy. If so, the contributions of each layer are scaled proportionally. Spectral normalization converts the superposition result into standardized reflectance spectral components. Normalization aims to eliminate the influence of variations in incident light intensity on the reflectance spectral shape. Normalization uses a peak normalization method: the system finds the maximum value in the superposition spectrum and then divides the entire spectrum by this maximum value to normalize the spectral data to a range of 0 to 1. The resulting reflection spectrum component is a normalized spectral array that describes how the reflectance characteristics of ambient light in the LCD's multilayer structure vary with wavelength. The reflection spectrum component data format includes a wavelength array and a corresponding reflection intensity array. The wavelength array covers the visible light range from 380 nanometers to 780 nanometers, while the reflection intensity array records the normalized reflection intensity values at each wavelength. This complete reflection spectrum component data provides accurate ambient light reflection information for subsequent spectral superposition and color compensation calculations.

[0033] 103. Calculating the spectral compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, converting the spectral compensation amount into a correction amount for the RGB drive value using a constrained optimization algorithm to obtain the RGB drive value after ambient light compensation; In one embodiment of the present invention, the step of calculating the spectral compensation required for each pixel based on the difference between the actual observed spectrum and the preset target spectrum, converting the spectral compensation into a correction to the RGB drive value through a constrained optimization algorithm, and obtaining the ambient light compensated RGB drive value comprises: performing wavelength-by-wavelength difference calculation between the actual observed spectrum and the preset target spectrum, processing the difference result through a spectral analysis algorithm, and obtaining the spectral compensation required for each pixel; inputting the spectral compensation into the constrained optimization algorithm, calculating the correction to the RGB drive value based on the hardware constraints of the liquid crystal display, optimizing the correction through a multi-time-scale modulation strategy and RGB cross-coupling modulation, and obtaining an optimal RGB drive value correction; and superimposing the optimal RGB drive value correction with the original RGB drive value to obtain the ambient light compensated RGB drive value.

[0034] Specifically, the difference calculation between the observed spectrum and the preset target spectrum begins with data alignment and wavelength matching. The system first checks the wavelength range and sampling interval of the two spectral data to ensure that the observed and target spectra have the same wavelength reference. The observed spectrum uses 401 data points covering the range of 380 nanometers to 780 nanometers, and the target spectrum is similarly sampled at 1-nanometer intervals. If the wavelength references of the two spectra are not completely consistent, the system resamples the data using cubic spline interpolation to unify the two spectra onto the same wavelength grid. Wavelength-by-wavelength difference calculation uses a direct subtraction method: the system subtracts the corresponding wavelength value of the target spectrum from each wavelength point in the observed spectrum to obtain 401 difference data points. The difference results can be positive or negative. A positive value indicates that the intensity of the actual spectrum at that wavelength exceeds the target value, while a negative value indicates that the intensity of the actual spectrum at that wavelength falls below the target value. The sign of the difference data is important for determining the subsequent compensation direction. A positive difference requires a reduction in light output at that wavelength, while a negative difference requires an increase in light output at that wavelength. The spectral analysis algorithm performs frequency domain analysis and feature extraction on the difference results. The system uses a fast Fourier transform to convert the difference spectrum from the spatial domain to the frequency domain, analyzing the frequency component distribution of the spectral differences. Low-frequency components reflect the overall shift trend of the spectrum, while high-frequency components reflect the detailed fluctuation characteristics of the spectrum. The system calculates the power spectral density of the difference spectrum and identifies the main frequency peaks and bandwidth characteristics. These characteristics are used to determine the parameter settings of the compensation algorithm. The spectral compensation amount is calculated using an adaptive filtering method. The system designs the corresponding compensation filter based on the spectral characteristics of the difference spectrum. The filter design takes into account the spectral response characteristics of the LCD display. The system reads the spectral response function of the three RGB channels, which describes the sensitivity of each channel to different wavelengths of light. The calculation of the compensation amount requires converting the spectral domain difference into RGB adjustment amounts that the device can achieve. The system uses a spectral matching algorithm to find the optimal RGB combination to approximate the target spectral compensation.

[0035] Specifically, the implementation of the constrained optimization algorithm begins by establishing hardware constraints and constructing a mathematical model for the optimization problem. The hardware constraints of LCD displays include physical constraints such as the dynamic range of RGB drive values, power consumption, and response time. The dynamic range constraint for RGB drive values requires that each channel's value must be between 0 and 255. The system expresses these boundary conditions as linear inequality constraints. The power consumption constraint is determined based on the display's maximum power consumption specification. The system calculates the power consumption contributions of the three RGB channels. The power consumption coefficients for the red, green, and blue channels are determined based on the efficiency characteristics of the LED or backlight. The mathematical expression of the power consumption constraint is that the weighted sum of the RGB drive values must not exceed a preset power consumption ceiling. The response time constraint takes into account the dynamic response characteristics of liquid crystal molecules. The system calculates the response time for different grayscale changes based on the viscoelastic parameters of the liquid crystal material, ensuring that RGB corrections do not cause the response time to exceed display requirements. The constrained optimization problem is solved using a sequential quadratic programming algorithm, which transforms the nonlinear constrained optimization problem into a series of quadratic programming subproblems for iterative solution. The system establishes a Lagrangian function and introduces the constraints into the objective function via Lagrangian multipliers, forming an augmented optimization objective. During the iterative solution process, the system calculates the gradient information of the objective function and constraint function, and updates the optimization variables and Lagrange multipliers until the convergence conditions are met. Convergence is judged using the dual criteria of gradient norm and constraint violation. When the gradient norm is less than the preset threshold and all constraints are met, the algorithm converges to the optimal solution. The application of the multi-time scale modulation strategy takes into account the multi-time scale characteristics of the liquid crystal response. The response of liquid crystal molecules includes a rapid molecular reorientation process and a slow molecular diffusion process. The system decomposes the RGB correction into a fast component and a slow component. The fast component corresponds to the electro-optical response of the liquid crystal molecules, with a response time of approximately a few milliseconds. The slow component corresponds to the slow changes caused by temperature and material aging, with a response time of approximately a few seconds to a few minutes.

[0036] Specifically, time-scale decomposition is implemented using a wavelet transform. The system selects wavelet basis functions with excellent time-frequency localization properties to perform multi-scale decomposition of the RGB correction values. The wavelet transform decomposes the correction signal into wavelet coefficients in different frequency bands. High-frequency coefficients correspond to rapidly varying components, while low-frequency coefficients correspond to slowly varying components. The system determines the threshold for frequency band division based on the time constant of the liquid crystal response: components with response times less than 10 milliseconds are classified as fast components, and components with response times greater than 10 milliseconds are classified as slow components. Each decomposed frequency band component is processed using a different modulation strategy: fast components are instantaneously modulated and applied directly to the RGB drive values, while slow components are gradually modulated through time integration. RGB cross-coupling modulation is implemented based on the coupling characteristics of color space. The three RGB channels interact when generating color: changes in the red channel affect hue and saturation, changes in the green channel primarily affect brightness, and changes in the blue channel affect color temperature. The system establishes a coupling matrix between the RGB channels, which describes the degree to which changes in each channel affect the others. The elements of the coupling matrix are obtained by measuring the color output under different RGB combinations. The system establishes a mapping relationship between RGB values and chromaticity coordinates in the color space and calculates the chromaticity coordinate offset caused by changes in each channel. The calculation of cross-coupling modulation uses an iterative compensation method. The system calculates the expected offset in the color space based on the current RGB correction value. Then, the required compensation is calculated by inverse operation of the coupling matrix, and the compensation is added to the original correction value to obtain the new correction value. The iterative process is repeated until the color offset is less than the preset tolerance range. It usually takes 3 to 5 iterations to reach convergence. The optimal RGB drive value correction value is determined using a multi-objective optimization method. The system simultaneously considers multiple optimization objectives such as spectral matching accuracy, hardware constraint satisfaction, and computational complexity.

[0037] Specifically, the overlay operation uses numerical addition to combine the optimal RGB drive value corrections with the original RGB drive values. The system first checks the numerical range of the corrections to ensure that the overlay result does not exceed the valid RGB drive value range. If the overlay result exceeds the range of 0 to 255, the system applies saturation processing, setting values exceeding the upper limit to 255 and values below the lower limit to 0. Saturation processing introduces nonlinear distortion. The system uses pre-compensation to mitigate the effects of saturation. When calculating the corrections, the saturation limit is considered in advance and the correction amplitude is appropriately reduced to avoid saturation. The overlay operation also needs to consider the impact of numerical precision. The original RGB drive values are represented as 8-bit integers, while the corrections are represented as floating-point numbers to maintain calculation accuracy. After overlaying, the system rounds the result to convert the floating-point result into an integer drive value. Quantization error during rounding is compensated using an error diffusion algorithm. The system distributes the quantization error of the current pixel to the corrections of adjacent pixels, reducing overall quantization distortion. The output of the RGB drive value after ambient light compensation uses a lookup table to achieve rapid conversion. The system pre-calculates the compensation parameters under different ambient light conditions and establishes a mapping table from ambient light parameters to RGB correction values. During real-time processing, the system interpolates the corresponding RGB correction values in the lookup table based on the current ambient light detection results, and then superimposes them with the original drive values to obtain the final output. The establishment of the lookup table takes into account the main changing parameters of ambient light, including light intensity, color temperature, and incident angle. The system quantifies these parameters into discrete sampling points and calculates the corresponding optimal RGB correction value at each sampling point. The interpolation calculation adopts the trilinear interpolation method. The system locates the position of the current ambient light parameter in the three-dimensional parameter space, and then performs weighted interpolation on the eight adjacent sampling points to obtain the accurate correction value.

[0038] Furthermore, the spectral compensation amount is input into the constrained optimization algorithm, the correction amount of the RGB drive value is calculated according to the hardware constraints of the liquid crystal display, and the correction amount is optimized through a multi-time scale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB drive value correction amount, including: inputting the spectral compensation amount into the constrained optimization algorithm, calculating the initial RGB drive value correction amount of the RGB drive value through constraint solving according to the constraints established according to the hardware constraints of the liquid crystal display; performing time-frequency decomposition on the initial RGB drive value correction amount using the multi-time scale modulation strategy, modulating each time scale component in the time-frequency decomposition process according to the response characteristics of the liquid crystal molecules, and obtaining a time domain optimization correction amount; performing the RGB cross-coupling modulation on the time domain optimization correction amount according to the spectral coupling characteristics between the three RGB channels to obtain a cross-modulation correction amount; performing stability verification on the cross-modulation correction amount, optimizing and adjusting the unstable components through convergence analysis, and obtaining the optimal RGB drive value correction amount.

[0039] Specifically, the system receives spectral compensation information stored as a 401-dimensional vector, with each element corresponding to the compensation intensity at a specific wavelength. The system then converts this spectral compensation information into adjustment parameters in the RGB color space. This conversion utilizes a color matching function approach. The system reads the CIE 1931 standard observer color matching function data, which describes the human eye's perceptual response to red, green, and blue light at different wavelengths. The spectral compensation is convolved with the color matching function. The system multiplies each wavelength point in the compensation spectrum by the corresponding matching function value. The system then integrates the values across the entire visible light range to obtain the required compensation for each of the three RGB channels. This integral calculation utilizes the trapezoidal integration method, dividing the visible light range into 400 trapezoidal bins. The area of each bin is calculated using the trapezoidal formula. The final integral represents the required luminous flux adjustment for each channel. The LCD display hardware constraints are established based on multiple physical and performance constraints. The RGB drive value range constraint stipulates that each channel must be within the 8-bit integer range of 0 to 255. These boundary conditions are expressed as a system of linear inequality constraint equations. Power consumption constraints are determined based on the display's power management specifications. The power consumption coefficients for the red, green, and blue LED backlights are 0.25 watts per unit, 0.18 watts per unit, and 0.32 watts per unit, respectively. The system calculates the weighted sum of the RGB drive values to ensure that the total power consumption does not exceed the design limit. The response time constraint takes into account the dynamic characteristics of the liquid crystal molecules. The system calculates the response delay for different grayscale changes based on the elastic constant and viscosity coefficient of the liquid crystal material, ensuring that the rate of change of the RGB correction value is within the response capability of the liquid crystal. Constraint solving is implemented using an interior point optimization algorithm, which transforms inequality constraints into an unconstrained optimization problem by introducing a barrier function. The system establishes a Lagrangian function, combining the objective function and the constraints to form an augmented objective function. The barrier parameter controls the weight of the constraint and gradually decreases as the iteration process proceeds.

[0040] Specifically, during the iterative solution process, the system calculates the gradient and Hessian matrix of the objective function. The gradient information indicates the update direction of the optimization variables, while the Hessian matrix describes the second-order curvature characteristics of the objective function. The Newton direction is calculated by solving a system of linear equations. The system uses the Cholesky decomposition method to solve the inverse of the Hessian matrix to obtain the optimal search direction. The step size is selected using a backtracking line search algorithm. The system starts with a unit step size and gradually reduces the step size until the Armijo condition is met, ensuring a sufficient decrease in the objective function value. Convergence is determined based on the dual criteria of the gradient norm and constraint violation. The algorithm reaches convergence when the gradient norm is less than 10 to the power of -6 and the violation of all constraints is less than 10 to the power of -8. The output of the initial RGB drive value correction includes the adjusted values for the red, green, and blue channels, representing the maximum compensation amplitude achievable under the current constraints. The application of the multi-timescale modulation strategy is based on the multi-layered temporal characteristics of the liquid crystal molecular response. The response process of the LCD includes physical processes at multiple time scales, such as molecular reorientation, viscoelastic recovery, and thermal diffusion. Time-frequency decomposition is achieved using a continuous wavelet transform (CWT) approach. The system selects the Morlet wavelet as the basis function, which has excellent time-frequency localization characteristics and can provide both time and frequency information. The wavelet transform is calculated using a fast algorithm. The system convolves the initial RGB correction signal with the wavelet basis function to obtain wavelet coefficients at different time scales. The time scale division is determined by the physical time constant of the liquid crystal response. The fast scale corresponds to the molecular reorientation process of 1 to 10 milliseconds, the medium scale corresponds to the viscoelastic response of 10 to 100 milliseconds, and the slow scale corresponds to the thermal equilibrium process of more than 100 milliseconds. Different filtering strategies are used for the modulation processing of each time scale component. The fast component maintains the original amplitude to ensure response speed, the medium scale component uses low-pass filtering to reduce high-frequency noise, and the slow component uses adaptive gain control to compensate for temperature drift effects.

[0041] Specifically, the Debye relaxation model is used to model the response characteristics of liquid crystal molecules, describing the dynamics of molecular orientation. The system calculates the relaxation time constant based on the dielectric constant and elastic constant of the liquid crystal material. The relaxation time constant varies with temperature, and the system establishes a temperature-relaxation time lookup table, selecting the corresponding parameter value based on the current operating temperature. Modulation processing is implemented through a time-domain convolution operation. The system convolves the wavelet coefficients at each time scale with the corresponding response function to obtain correction coefficients that account for the dynamic characteristics of the liquid crystal. Reconstruction of the time-domain optimized correction values is achieved through an inverse wavelet transform. The system linearly combines the modulated wavelet coefficients at each scale to reconstruct the time-domain optimized RGB correction values. The reconstruction process must ensure signal integrity, and the system uses a perfect reconstruction filter bank to ensure that the inverse transform result is energetically equivalent to the original signal. RGB cross-coupling modulation is implemented based on the mutual influence characteristics of color space. The three RGB channels have a complex nonlinear coupling relationship when generating color. Spectral coupling characteristics are modeled using spectral overlap analysis. The system calculates the overlap integral of the spectral response functions of the red, green, and blue channels to quantify the degree of mutual influence between the channels. The red and green channels have spectral overlap in the 580-620 nm wavelength range, while the green and blue channels overlap in the 480-520 nm range. These overlapping regions lead to crosstalk between the channels. The coupling matrix is established by experimentally measuring the actual color output under different RGB combinations. The system performs measurements at the vertex and edge sampling points of the RGB cube, recording the correspondence between the input RGB values and the output chromaticity coordinates. The measurement data is analyzed using multiple linear regression. The system establishes a linear model of RGB input and chromaticity output, with the regression coefficients forming a 3×3 coupling matrix. Cross-coupling modulation is calculated using matrix operations. The system represents the time-domain optimization correction as a 3×1 vector, which is multiplied by the coupling matrix to obtain the correction that accounts for the mutual influence between the channels.

[0042] Specifically, the results of the matrix operation need to be normalized. The system calculates the norm of the correction vector, divides each component by the norm to obtain the normalized correction direction, and then multiplies it by the original correction amplitude to restore the appropriate adjustment strength. The cross-modulation correction incorporates compensation information for inter-channel coupling effects, which can reduce color shift and saturation loss during the RGB adjustment process. Stability verification is implemented using Lyapunov stability theory to analyze the convergence characteristics of the correction. The system establishes a state-space model of the display system, using the RGB drive values as state variables and the corrections as control inputs. The state equations are constructed by considering the dynamic characteristics of the liquid crystal response and the influence of environmental perturbations. Eigenvalue analysis of the system matrix reveals the stability characteristics of the system. The Lyapunov function is constructed using quadratic functions. The system defines a positive energy function and calculates the time derivative of this function along the system trajectory. When the derivative is negative, the system is asymptotically stable; when the derivative is positive, the system is unstable and requires adjustment. Convergence analysis is performed by calculating the convergence rate and convergence region of the correction sequence. The system monitors the change in the correction between consecutive iterations and considers the sequence converged when the change is less than a preset threshold for multiple consecutive times. Unstable components are identified using frequency domain analysis. The system performs a Fourier transform on the cross-modulation corrections to analyze the unstable frequency components within the spectrum. Frequency points where the amplitude of the frequency response is greater than 1 correspond to unstable modes, and the system employs frequency domain filtering to suppress these unstable components. Optimization is achieved using an adaptive control strategy. Based on the results of the stability analysis, the system adjusts the gain and phase of the corrections to ensure that the corrected system meets stability requirements. The optimal RGB drive value corrections are determined using a multi-objective trade-off approach. The system simultaneously considers compensation accuracy, stability, and computational complexity, selecting the correction parameters with the best overall performance through Pareto optimality.

[0043] 104. Calculate actual white point color coordinates of the display screen according to the ambient light compensated RGB driving values, and adjust the actual white point color coordinates to a standard white point position using a progressive white point migration algorithm.

[0044] In one embodiment of the present invention, calculating the actual white point color coordinates of the display screen based on the ambient light compensated RGB drive values and adjusting the actual white point color coordinates to the standard white point position using a progressive white point migration algorithm includes: calculating the actual white point color coordinates of the display screen based on the ambient light compensated RGB drive values through CIE color space transformation; calculating the coordinate difference between the actual white point color coordinates and a preset standard white point position, determining migration path parameters based on display content characteristics using the progressive white point migration algorithm to obtain white point migration control parameters; performing a white balance matrix transformation on the ambient light compensated RGB drive values based on the white point migration control parameters to obtain white point corrected RGB drive values; and generating a PWM control signal based on the white point corrected RGB drive values, and outputting the PWM control signal to each pixel unit of the liquid crystal display screen for display control.

[0045] Specifically, the RGB drive values after ambient light compensation are transformed into the CIE color space to calculate the actual white point color coordinates. The system first normalizes the RGB values to the range of 0 to 1, and then applies the color characteristic matrix of the display for linear transformation. The color characteristic matrix is a 3×3 coefficient matrix whose elements are determined by measuring the CIE XYZ tristimulus values of the three primary colors of red, green, and blue of the display. This matrix describes the conversion relationship between the device-related RGB color space and the device-independent XYZ color space. The matrix transformation calculation uses standard matrix multiplication operations to multiply the RGB vector with the characteristic matrix to obtain the XYZ tristimulus values, where X represents the perceived amount of red, Y represents the perceived amount of brightness, and Z represents the perceived amount of blue. The white point corresponds to the color output when the RGB input is equal. The system sets the RGB drive values after ambient light compensation to equal values and takes the average value of the three channels as the input parameter for the white point calculation. After calculating the XYZ tristimulus values, the system uses the chromaticity coordinate transformation formula to convert the XYZ values into xy chromaticity coordinates. The chromaticity coordinate x equals X divided by the sum of XYZ, and the chromaticity coordinate y equals Y divided by the sum of XYZ. This normalization eliminates the influence of brightness and retains only chromaticity information. The numerical accuracy of the actual white point color coordinates directly affects the subsequent color correction effect. The system uses double-precision floating-point numbers for calculations, maintaining an accuracy of at least 6 significant digits. The calculation of chromaticity coordinates also needs to consider numerical stability. When the sum of the XYZ tristimulus values approaches zero, the system uses special processing to avoid division by zero errors and sets the chromaticity coordinates to the default values of the standard lighting body.

[0046] Specifically, the Euclidean distance metric is used to calculate the difference between the actual white point's color coordinates and the standard white point's position. The standard white point's position is selected based on the requirements of the display application. Common standards include the chromaticity coordinates corresponding to D65 illuminant (0.3127, 0.3290) and the coordinates corresponding to D50 illuminant (0.3457, 0.3585). The system calculates the difference between the actual and standard white points in both the x and y dimensions. The modulus of the difference vector indicates the degree of chromaticity shift, and the direction of the difference vector indicates the direction of chromaticity shift. The progressive white point migration algorithm determines the migration path parameters based on the characteristics of the display content. This algorithm takes into account the human eye's perception of color changes and the complexity of the display content. The display content analysis includes statistical features such as the image's average brightness, contrast, color richness, and spatial frequency. The system extracts these characteristic parameters through image processing algorithms. Average brightness is calculated by averaging the grayscale values of all pixels in the image. Contrast is expressed as the ratio of the standard deviation to the mean. Color richness is quantified by calculating the entropy of the chromaticity distribution. Spatial frequency is analyzed through the statistical distribution of gradient amplitudes. Migration path parameters are determined using piecewise linear interpolation. The system adjusts the migration step size and speed based on the complexity of the displayed content. Complex content uses smaller step sizes and slower speeds to avoid noticeable color jumps, while simple content uses larger step sizes and faster speeds to reduce adjustment time. The migration path appears on the chromaticity plane as a smooth curve from the actual white point to the standard white point. The shape of the curve is determined by Bezier curve fitting, and the positions of the control points are optimized based on the principle of perceptual uniformity to ensure uniform color changes during the migration process. White point migration control parameters include timing control information such as the number of migration steps, the displacement of each step, and the duration of each step. The combination of these parameters determines the complete white point adjustment strategy.

[0047] Specifically, the white balance matrix transformation performs color space correction on the ambient light-compensated RGB drive values based on white point shift control parameters. The white balance matrix is a diagonally dominant 3×3 matrix, with diagonal elements representing the gain adjustment coefficients for each channel and off-diagonal elements representing the color coupling correction coefficients between channels. The matrix elements are calculated using the von Kries transform theory, which is based on the physiological mechanism of color constancy in the human eye. It achieves precise control of the white point position by adjusting the relative gains of the three RGB channels. Calculating the gain coefficients requires solving the color mapping problem from the current white point to the target white point. The system establishes a nonlinear mapping relationship between chromaticity coordinates and RGB gains, and employs an iterative optimization method to find the optimal gain combination. The iterative process uses the Newton-Raphson method, calculating the Jacobian matrix of the chromaticity error with respect to the gain parameters. The gain estimates are updated through matrix inversion and vector multiplication. The convergence criterion is set to a chromaticity error less than 0.001, corresponding to the threshold level at which the human eye can just perceive color differences. The off-diagonal elements of the white balance matrix are determined using a least-squares fit. The system measures the chromaticity output for different RGB combinations and establishes an overdetermined system of equations to solve for the cross-coupling coefficients. The matrix transformation is calculated using standard matrix-vector multiplication, multiplying the ambient light-compensated RGB drive value vector by the white balance matrix to obtain the white point-corrected RGB values. The transformation process checks the validity of the resulting values to ensure that the corrected RGB values remain within the valid range of 0 to 255. Values outside this range are saturated and clamped. Saturation can introduce color distortion, and the system uses pre-compensation to reduce the likelihood of saturation. Dynamic range limitations are considered in the calculation of the white balance matrix, appropriately constraining the range of the gain coefficients.

[0048] Specifically, the RGB drive values after white point correction need to be converted into PWM control signals to drive the LCD's pixel units. The PWM signal is a periodic pulse-width modulated square wave whose duty cycle is proportional to the RGB drive value. The system sets the PWM signal's base frequency to 240Hz, which is significantly higher than the human eye's flicker fusion frequency to avoid visible flicker, yet lower than the LCD's cutoff frequency to ensure adequate drive performance. The PWM duty cycle calculation maps the 8-bit RGB drive values to a duty cycle range of 0% to 100%. This mapping uses linear interpolation, with an RGB value of 0 corresponding to a 0% duty cycle and an RGB value of 255 corresponding to a 100% duty cycle. The timing controller generates the actual PWM waveform based on the calculated duty cycle parameters. The system uses a high-resolution digital clock source to ensure PWM signal timing accuracy. The clock frequency is set to 61.44MHz, providing 256 levels of duty cycle resolution. The PWM signal generation utilizes a dedicated timing control chip that integrates a multi-channel PWM generator and driver buffers, capable of simultaneously outputting hundreds of independent PWM signals. Signal output to the LCD requires level conversion and power amplification. The system uses MOSFET power switches to convert 5V logic signals into a 15V LCD drive voltage. The drive circuit design takes into account signal transmission integrity and electromagnetic compatibility, using differential signal transmission and shielded cables to minimize the impact of external interference. The pixel unit is driven using an active matrix method, with each sub-pixel equipped with an independent thin-film transistor switch. PWM signals are sequentially applied to each pixel via row and column scanning. Scan timing control must be synchronized with the PWM signal. The system uses a double buffering mechanism to prevent image tearing during display. The display data of the current frame is updated in the background buffer, and the front and back buffers swap roles after display is complete. The ultimate output of the display control is a stable image display. After white point correction, color representation is more accurate and consistent, effectively ensuring display quality under various ambient lighting conditions.

[0049] In this embodiment, a theoretical emission spectrum is derived by performing nonlinear spectral mapping on the input RGB drive values, combined with the response characteristics of liquid crystal molecules. The reflected spectral components in the multilayer structure are calculated based on the ambient light spectrum and superimposed with the theoretical emission spectrum to obtain the actual observed spectrum. The difference between the actual observed spectrum and the target spectrum is calculated and converted into RGB corrections using a constrained optimization algorithm to obtain the ambient light-compensated RGB drive values. The actual white point color coordinates are calculated and adjusted to the standard white point position using a progressive white point migration algorithm. This invention dynamically adjusts display parameters based on real-time ambient light conditions, effectively compensating for the effects of ambient light reflection on color. White point correction ensures color temperature consistency and color accuracy, significantly improving display quality under varying ambient light conditions and enhancing the user's visual experience.

[0050] The above describes the display control method of the liquid crystal display screen in the embodiment of the present invention. The following describes the display control system of the liquid crystal display screen in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a display control system for a liquid crystal display screen includes: Spectral mapping module 201, used to perform nonlinear spectral mapping processing on the input RGB driving values based on the mapping relationship between liquid crystal transmittance and backlight spectrum, and combine the response characteristics of liquid crystal molecules and temperature compensation parameters to obtain the theoretical emission spectrum of each pixel; An environmental compensation module 202 is configured to calculate the reflected spectrum component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtain the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflected spectrum component; The spectrum correction module 203 is used to calculate the spectrum compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, and convert the spectrum compensation amount into a correction amount of the RGB drive value through a constrained optimization algorithm to obtain the RGB drive value after ambient light compensation; The white point adjustment module 204 is configured to calculate the actual white point color coordinates of the display screen according to the ambient light compensated RGB driving values, and adjust the actual white point color coordinates to a standard white point position using a progressive white point migration algorithm.

[0051] In an embodiment of the present invention, the display control system of the liquid crystal display screen runs the display control method of the liquid crystal display screen described above. The display control system of the liquid crystal display screen obtains a theoretical emission spectrum by performing nonlinear spectral mapping processing on the input RGB drive values, combined with the response characteristics of the liquid crystal molecules; calculates its reflected spectral component in the multilayer structure based on the ambient light spectrum, and superimposes it with the theoretical emission spectrum to obtain the actual observed spectrum; calculates the difference between the actual observed spectrum and the target spectrum, converts it into RGB correction value through a constrained optimization algorithm, and obtains the RGB drive value after ambient light compensation; calculates the actual white point color coordinates, and adjusts them to the standard white point position through a progressive white point migration algorithm. The present invention can dynamically adjust display parameters according to real-time ambient light conditions, effectively compensate for the influence of ambient light reflection on color, and ensure color temperature consistency and color accuracy through white point correction, significantly improving display quality under different ambient light conditions and enhancing the user's visual experience.

[0052] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0053] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0054] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A display control method for a liquid crystal display screen, characterized in that: The display control method of the liquid crystal display screen includes: The input RGB driving values are processed by nonlinear spectral mapping based on the mapping relationship between liquid crystal transmittance and backlight spectrum. The theoretical emission spectrum of each pixel is obtained by combining the response characteristics of liquid crystal molecules and temperature compensation parameters. Calculating the reflected spectral component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtaining the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflected spectral component; Calculating the spectral compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, and converting the spectral compensation amount into a correction amount for the RGB drive value through a constrained optimization algorithm to obtain the RGB drive value after ambient light compensation; The actual white point color coordinates of the display screen are calculated according to the RGB driving values after the ambient light compensation, and the actual white point color coordinates are adjusted to the standard white point position through a progressive white point migration algorithm.

2. The display control method of a liquid crystal display screen according to claim 1, wherein: The input RGB driving values are subjected to nonlinear spectral mapping based on the mapping relationship between the liquid crystal transmittance and the backlight spectrum, and the theoretical emission spectrum of each pixel is obtained by combining the response characteristics of the liquid crystal molecules and the temperature compensation parameters. Calculate the RGB three-channel transmittance components of each pixel point according to the input RGB driving value through the mapping relationship between the liquid crystal transmittance and the backlight spectrum; Performing nonlinear response correction on the RGB three-channel transmittance components according to the response characteristics of the liquid crystal molecules, and performing temperature drift compensation on the corrected transmittance components in combination with temperature compensation parameters to obtain the transmittance coefficient under actual working conditions; The transmittance coefficient is multiplied by the backlight spectrum on a wavelength-by-wavelength basis and a spectrum synthesis calculation is performed to obtain a theoretical emission spectrum of each pixel point.

3. The display control method of a liquid crystal display screen according to claim 1, wherein: The step of calculating the reflected spectrum component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtaining the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflected spectrum component comprises: Calculating the propagation path and scattering characteristics of the detected ambient light in each layer structure according to the optical parameters of the multi-layer structure of the liquid crystal display screen to obtain the reflection spectrum component of the ambient light in the multi-layer structure; Performing spectral superposition operation on the theoretical emission spectrum and the reflection spectrum components according to the wavelength correspondence, and weighting the superposition results by a dynamic weight allocation algorithm to obtain a weighted superposition spectrum; The spectrum output of each pixel under the current ambient light condition is calculated based on the weighted superposition spectrum to obtain the actual observed spectrum of each pixel.

4. The display control method of a liquid crystal display screen according to claim 3, wherein: The step of calculating the propagation path and scattering characteristics of the detected ambient light in each layer structure according to the optical parameters of the multi-layer structure of the liquid crystal display screen to obtain the reflection spectrum components of the ambient light in the multi-layer structure includes: Analyzing the optical characteristics of the ambient light according to the detected incident angle and polarization state, and calculating the optical reflection parameters of the interfaces of the polarizer layer, the liquid crystal layer, and the color filter layer in the multi-layer structure of the liquid crystal display screen in combination with the refractive index parameters of the polarizer layer, the liquid crystal layer, and the color filter layer; Performing layer-by-layer ray tracing calculations on the ambient light in each layer of the structure based on the optical reflection parameters, analyzing the scattering characteristics of the ambient light using Rayleigh scattering and Mie scattering models, and obtaining the scattering spectrum distribution of the ambient light in each layer of the structure; The scattering spectrum distribution is weighted according to the optical thickness of each layer structure, and the interaction effect of the scattering spectrum of each layer is calculated by an interlayer coupling algorithm to obtain the scattering spectrum contribution of each layer structure; The scattered spectrum contribution is accumulated and superimposed according to the spectrum weight, and the overall reflection contribution of the ambient light is calculated through spectrum normalization processing to obtain the reflection spectrum component of the ambient light in the multilayer structure.

5. The display control method of a liquid crystal display screen according to claim 1, wherein: The calculation of the spectral compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, and the conversion of the spectral compensation amount into a correction amount of the RGB driving value through a constrained optimization algorithm to obtain the RGB driving value after ambient light compensation includes: Calculating the wavelength-by-wavelength difference between the actual observed spectrum and the preset target spectrum, processing the difference results through a spectrum analysis algorithm to obtain the spectral compensation required for each pixel; Inputting the spectral compensation amount into a constrained optimization algorithm, calculating the correction amount of the RGB drive value according to the hardware constraints of the liquid crystal display, and optimizing the correction amount through a multi-time scale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB drive value correction amount; The optimal RGB driving value correction amount is superimposed on the original RGB driving value to obtain the RGB driving value after ambient light compensation.

6. The display control method of a liquid crystal display screen according to claim 5, characterized in that: Inputting the spectral compensation amount into the constrained optimization algorithm, calculating the correction amount of the RGB drive value according to the hardware constraints of the liquid crystal display, optimizing the correction amount through a multi-time scale modulation strategy and RGB cross-coupling modulation, and obtaining the optimal RGB drive value correction amount includes: Inputting the spectral compensation amount into the constraint optimization algorithm, and calculating the initial RGB drive value correction amount of the RGB drive value through constraint solving according to the constraint conditions established by the hardware limitation conditions of the liquid crystal display screen; Performing time-frequency decomposition on the initial RGB drive value correction using the multi-time-scale modulation strategy, modulating each time-scale component in the time-frequency decomposition process according to the response characteristics of the liquid crystal molecules to obtain a time-domain optimized correction; Performing the RGB cross-coupling modulation on the time domain optimization correction amount according to the spectral coupling characteristics between the three RGB channels to obtain a cross-modulation correction amount; The stability of the cross-modulation correction amount is verified, and the unstable component is optimized and adjusted through convergence analysis to obtain the optimal RGB drive value correction amount.

7. The display control method of a liquid crystal display screen according to claim 1, wherein: Calculating the actual white point color coordinates of the display screen according to the RGB driving values after the ambient light compensation, and adjusting the actual white point color coordinates to the standard white point position by a progressive white point migration algorithm includes: Calculating the actual white point color coordinates of the display screen through CIE color space transformation according to the RGB driving values after ambient light compensation; Calculating the coordinate difference between the actual white point color coordinates and the preset standard white point position, determining the migration path parameters according to the display content characteristics using the progressive white point migration algorithm, and obtaining the white point migration control parameters; Performing a white balance matrix transformation on the ambient light compensated RGB driving value according to the white point migration control parameter to obtain a white point corrected RGB driving value; A PWM control signal is generated according to the RGB driving value after the white point correction, and is output to each pixel unit of the liquid crystal display screen for display control.

8. A display control system for a liquid crystal display screen, characterized in that: The display control system of the liquid crystal display screen includes: The spectrum mapping module is used to perform nonlinear spectrum mapping on the input RGB drive values based on the mapping relationship between liquid crystal transmittance and backlight spectrum, and obtain the theoretical emission spectrum of each pixel by combining the response characteristics of liquid crystal molecules and temperature compensation parameters; An environmental compensation module is used to calculate the reflection spectrum component of the ambient light in the multi-layer structure of the liquid crystal display screen based on the detected ambient light spectrum, and obtain the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflection spectrum component; A spectral correction module is used to calculate the spectral compensation required for each pixel point based on the difference between the actual observed spectrum and the preset target spectrum, and convert the spectral compensation amount into a correction amount of the RGB drive value through a constrained optimization algorithm to obtain the RGB drive value after ambient light compensation; The white point adjustment module is used to calculate the actual white point color coordinates of the display screen according to the RGB driving value after the ambient light compensation, and adjust the actual white point color coordinates to the standard white point position through a progressive white point migration algorithm.

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