LCD Display Control Method and System

Abstract

This invention provides a display control method and system for a liquid crystal display (LCD). The method includes: performing nonlinear spectral mapping processing on the input RGB driving values ​​and combining this with the response characteristics of liquid crystal molecules to obtain the theoretical emission spectrum; calculating the reflection spectral components in the multilayer structure based on the ambient light spectrum and superimposing them with the theoretical emission spectrum to obtain the actual observed spectrum; calculating the difference between the actual observed spectrum and the target spectrum, converting it into an RGB correction value through a constraint optimization algorithm to obtain the ambient light compensated RGB driving value; and calculating the actual white point color coordinates and adjusting them to the standard white point position through a progressive white point migration algorithm. This 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.

Description

Technical Field

[0001] This 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 Technology

[0002] The display effect of LCD screens varies significantly under different ambient light conditions, affecting the user's visual experience. Traditional LCD control technology mainly relies on fixed RGB drive values ​​for display output, failing to fully consider the impact of ambient light on display performance. When ambient light shines on the surface of an LCD screen, reflections occur within its multi-layered structure. These reflected lights superimpose with the light emitted by the screen itself, resulting in a difference between the observed spectrum and the theoretical emission spectrum.

[0003] In existing technologies, most display control methods lack accurate modeling and compensation mechanisms for ambient light reflection, and cannot 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, which seriously affects display quality and user experience. Summary of the Invention

[0004] The main objective of this invention is to solve the technical problem that the lack of ambient light reflection modeling and dynamic compensation mechanisms in existing liquid crystal display control technology leads to unstable display quality under different ambient light conditions.

[0005] The first aspect of the present invention provides a display control method for a liquid crystal display screen, the display control method for the liquid crystal display screen comprising:

[0006] The input RGB driving values ​​are processed by nonlinear spectral mapping based on the mapping relationship between liquid crystal transmittance and backlight spectrum. Combined with the response characteristics of liquid crystal molecules and temperature compensation parameters, the theoretical emission spectrum of each pixel is obtained.

[0007] The reflected spectral components of ambient light in the multilayer structure of the liquid crystal display are calculated based on the detected ambient light spectrum. The actual observed spectrum of each pixel is obtained by superimposing the theoretical emission spectrum and the reflected spectral components.

[0008] The required spectral compensation amount for each pixel is calculated based on the difference between the actual observed spectrum and the preset target spectrum. The spectral compensation amount is then converted into the correction amount of the RGB driving value through a constraint optimization algorithm to obtain the RGB driving value after ambient light compensation.

[0009] The actual white point color coordinates of the display screen are calculated based on the RGB driving values ​​after ambient light compensation, and the actual white point color coordinates are adjusted to the standard white point position using a progressive white point migration algorithm.

[0010] Optionally, in a first implementation of the first aspect of the present invention, the nonlinear spectral mapping processing of the input RGB driving value based on the mapping relationship between liquid crystal transmittance and backlight spectrum, combined with the liquid crystal molecule response characteristics and temperature compensation parameters, to obtain the theoretical emission spectrum of each pixel includes:

[0011] The RGB three-channel transmittance components of each pixel are calculated based on the input RGB driving value through the mapping relationship between the liquid crystal transmittance and the backlight spectrum.

[0012] The nonlinear response of the RGB three-channel transmittance components is corrected based on the liquid crystal molecule response characteristics, and the temperature drift of the corrected transmittance components is compensated by temperature compensation parameters to obtain the transmittance coefficient under actual working conditions.

[0013] The theoretical emission spectrum of each pixel is obtained by performing wavelength-by-wavelength multiplication and spectral synthesis calculations on the transmittance coefficient and the backlight spectrum.

[0014] Optionally, in a second implementation of the first aspect of the present invention, the step of calculating the reflection spectral component of ambient light in the multilayer 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 spectral component, includes:

[0015] Based on the optical parameters of the multilayer structure of the liquid crystal display screen, the propagation path and scattering characteristics of the ambient light in each layer are calculated to obtain the reflection spectral components of the ambient light in the multilayer structure.

[0016] The theoretical emission spectrum and the reflection spectrum components are superimposed according to the wavelength correspondence. The superposition result is then weighted using a dynamic weight allocation algorithm to obtain a weighted superimposed spectrum.

[0017] The spectral output of each pixel under the current ambient light conditions is calculated based on the weighted superimposed spectrum to obtain the actual observed spectrum of each pixel.

[0018] Optionally, in a third implementation of the first aspect of the present invention, the step of calculating the propagation path and scattering characteristics of the detected ambient light in each layer of the liquid crystal display screen based on the optical parameters of the multilayer structure, and obtaining the reflection spectral components of the ambient light in the multilayer structure, includes:

[0019] The optical characteristics of the ambient light are analyzed based on the incident angle and polarization state of the detected ambient light. The optical reflection parameters of each layer interface are calculated by combining the refractive index parameters of the polarizer layer, liquid crystal layer and color filter layer in the multilayer structure of the liquid crystal display screen.

[0020] Based on the optical reflection parameters, the ambient light is traced layer by layer in each layer of the structure. The scattering characteristics of the ambient light are analyzed by Rayleigh scattering and Mie scattering models to obtain the scattering spectral distribution of the ambient light in each layer of the structure.

[0021] The scattering spectrum distribution is weighted according to the optical thickness of each layer, and the interaction effect of the scattering spectrum of each layer is calculated by the interlayer coupling algorithm to obtain the scattering spectrum contribution of each layer.

[0022] The scattering spectral contribution is accumulated and superimposed according to the spectral weight, and the overall reflection contribution of ambient light is calculated through spectral normalization to obtain the reflection spectral components of ambient light in the multilayer structure.

[0023] Optionally, in a fourth implementation of the first aspect of the present invention, the step of calculating the required spectral compensation amount for each pixel 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 driving value through a constraint optimization algorithm to obtain the ambient light compensated RGB driving value includes:

[0024] The wavelength-by-wavelength difference between the actual observed spectrum and the preset target spectrum is calculated, and the difference results are processed by a spectral analysis algorithm to obtain the spectral compensation amount required for each pixel.

[0025] The spectral compensation amount is input into the constraint optimization algorithm. The correction amount of the RGB driving value is calculated according to the hardware constraints of the liquid crystal display screen. The correction amount is optimized by multi-time scale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB driving value correction amount.

[0026] The optimal RGB drive value correction is superimposed on the original RGB drive value to obtain the ambient light compensated RGB drive value.

[0027] Optionally, in the fifth implementation of the first aspect of the present invention, the step of inputting the spectral compensation amount into the constraint optimization algorithm, calculating the correction amount of the RGB driving value according to the hardware constraints of the liquid crystal display screen, and optimizing the correction amount through a multi-timescale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB driving value correction amount includes:

[0028] The spectral compensation amount is input into the constraint optimization algorithm. Based on the constraints established by the hardware limitations of the LCD screen, the initial RGB driving value correction amount of the RGB driving value is calculated through constraint solving.

[0029] The initial RGB driving value correction amount is decomposed into time and frequency using the multi-time-scale modulation strategy. Based on the liquid crystal molecule response characteristics, the time-scale components in the time-frequency decomposition process are modulated to obtain the time-domain optimized correction amount.

[0030] Based on the spectral coupling characteristics between the three RGB channels, the time-domain optimization correction amount is subjected to RGB cross-coupling modulation to obtain the cross-modulation correction amount;

[0031] The stability of the cross-modulation correction amount is verified, and the unstable components are optimized and adjusted through convergence analysis to obtain the optimal RGB driving value correction amount.

[0032] Optionally, in a sixth implementation of the first aspect of the present invention, the step of calculating the actual white point color coordinates of the display screen based on the ambient light compensated RGB driving value, and adjusting the actual white point color coordinates to the standard white point position using a progressive white point migration algorithm includes:

[0033] The actual white point coordinates of the display screen are calculated using the CIE color space transformation based on the RGB drive values ​​after ambient light compensation.

[0034] The coordinate difference between the actual white point color coordinates and the preset standard white point position is calculated, and the migration path parameters are determined according to the characteristics of the displayed content through the progressive white point migration algorithm to obtain the white point migration control parameters.

[0035] Based on the white point migration control parameters, the RGB driving value after ambient light compensation is transformed by a white balance matrix to obtain the RGB driving value after white point correction.

[0036] A PWM control signal is generated based on the RGB driving value after white point correction and output to each pixel unit of the LCD screen for display control.

[0037] A second aspect of the present invention provides a display control system for a liquid crystal display screen, the display control system comprising:

[0038] The spectral mapping module is 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. Combined with the response characteristics of liquid crystal molecules and temperature compensation parameters, the theoretical emission spectrum of each pixel is obtained.

[0039] An environmental compensation module is used to calculate the reflection spectral components of ambient light in the multilayer structure of the liquid crystal display screen based on the detected ambient light spectrum, and to obtain the actual observed spectrum of each pixel by superimposing the theoretical emission spectrum and the reflection spectral components.

[0040] The spectral correction module is used to calculate the required spectral compensation amount for each pixel based on the difference between the actual observed spectrum and the preset target spectrum, and convert the spectral compensation amount into the correction amount of the RGB driving value through a constraint optimization algorithm to obtain the RGB driving value after ambient light compensation.

[0041] The white point adjustment module is used to calculate the actual white point color coordinates of the display screen based on the RGB driving value after ambient light compensation, and adjust the actual white point color coordinates to the standard white point position through a progressive white point migration algorithm.

[0042] The aforementioned display control method and system for a liquid crystal display screen obtains a theoretical emission spectrum by performing nonlinear spectral mapping processing on the input RGB driving values ​​and combining this with the response characteristics of liquid crystal molecules. It then calculates the reflection spectral components in the multilayer structure based on the ambient light spectrum and superimposes them 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 an RGB correction value using a constrained optimization algorithm, resulting in the ambient light-compensated RGB driving value. Finally, 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 according to real-time ambient light conditions, effectively compensating for the influence of ambient light reflection on color. Simultaneously, white point correction ensures color temperature consistency and color accuracy, significantly improving display quality under different ambient light conditions and enhancing the user's visual experience.

[0043] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0044] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the first embodiment of the display control method for a liquid crystal display screen in this invention;

[0046] Figure 2 This is a schematic diagram of one embodiment of the display control system for a liquid crystal display screen in this invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] The terms "comprising" and "having," and any variations thereof, used in the embodiments of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0049] To facilitate understanding of this embodiment, a display control method for a liquid crystal display screen disclosed in this embodiment of the invention will first be described in detail. For example... Figure 1 As shown, this method includes the following steps:

[0050] 101. The input RGB driving values ​​are processed by nonlinear spectral mapping based on the mapping relationship between liquid crystal transmittance and backlight spectrum. Combined with the liquid crystal molecule response characteristics and temperature compensation parameters, the theoretical emission spectrum of each pixel is obtained.

[0051] In one embodiment of the present invention, the step of performing nonlinear spectral mapping processing on the input RGB driving value based on the mapping relationship between liquid crystal transmittance and backlight spectrum, and combining the liquid crystal molecule response characteristics and temperature compensation parameters to obtain the theoretical emission spectrum of each pixel includes: calculating the RGB three-channel transmittance components of each pixel based on the input RGB driving value through the mapping relationship between liquid crystal transmittance and backlight spectrum; performing nonlinear response correction on the RGB three-channel transmittance components based on the liquid crystal molecule response characteristics, 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; and performing wavelength-wise multiplication and spectral synthesis calculation on the transmittance coefficient and backlight spectrum to obtain the theoretical emission spectrum of each pixel.

[0052] Specifically, the spectral mapping processing of the LCD screen begins with the input RGB drive values ​​and executes a specific calculation process. The calculation of the RGB three-channel transmittance components first uses the input RGB values ​​as indices to retrieve the corresponding basic transmittance from a pre-calibrated LCD transmittance lookup table. The calculation process for the red channel involves dividing the R value by 255 to obtain a normalized value, then multiplying it by the index range of the lookup table to obtain the specific lookup position. The system reads the transmittance value stored at that position as the basic transmittance for the red channel. The green and blue channels use the same calculation method to obtain their respective basic transmittance values. Next, the system reads the backlight spectral data, which stores the light intensity value at each wavelength index. The system performs wavelength-wise multiplication of the backlight spectrum with the spectral transmittance of the color filter to obtain the effective backlight spectrum for each channel. The effective backlight spectrum calculation for the red channel involves multiplying the value at each wavelength of the backlight spectrum with the transmittance of the red filter at the corresponding wavelength. The green and blue channels are calculated using the same method. The system then performs a convolution operation between the base transmittance of each channel and the corresponding effective backlight spectrum. Specifically, the base transmittance is used as a weighting coefficient and multiplied by each wavelength point of the effective backlight spectrum to obtain the transmittance distribution of that channel at each wavelength. Finally, the transmittance distribution is integrated using the trapezoidal integral method, and the integral result is divided by the spectral range to obtain the final transmittance component of that channel.

[0053] Specifically, the nonlinear response correction employs a lookup table combined with cubic spline interpolation to correct the transmittance component. The system establishes a response characteristic lookup table, recording the correspondence between theoretical and actual measured transmittance. The data in the table is obtained by 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 a cubic spline interpolation algorithm to calculate the precise correction coefficients. The cubic spline interpolation calculation process involves establishing a piecewise cubic polynomial. The system constructs the coefficients of the cubic equation based on the values ​​and derivative information of four adjacent data points, and then substitutes the transmittance component value into the equation to calculate the corrected value. Temperature compensation is implemented using a two-dimensional linear interpolation algorithm. The system establishes a temperature-transmittance two-dimensional lookup table, with the horizontal axis representing the transmittance value and the vertical axis representing the temperature value. 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 calculations. The specific process of bilinear interpolation is as follows: first, two linear interpolations are performed in the horizontal direction to obtain two intermediate values; then, linear interpolation is performed in the vertical direction on these two intermediate values ​​to obtain the final compensation coefficient. The system multiplies the compensation coefficient by the transmittance after response correction to obtain the final transmittance coefficient considering the effect of temperature.

[0054] Specifically, the wavelength-wise multiplication operation organizes the transmittance coefficient and backlight spectrum into a 401-dimensional floating-point array, corresponding to wavelengths from 380 nm to 780 nm. The system first expands the transmittance coefficient to a full-spectrum distribution, using a Gaussian function model to describe the transmittance variation at different wavelengths. The transmittance distribution for the red channel is centered at 630 nm with a half-peak width of 80 nm, for the green channel at 530 nm, and for the blue channel at 460 nm. The transmittance distribution is calculated using a Gaussian function formula, with the transmittance coefficient as the amplitude parameter and the center wavelength and half-peak width as the shape parameters, yielding transmittance values ​​at 401 wavelength points. Then, the system performs element-wise multiplication, multiplying the transmittance distribution array with the corresponding values ​​in the backlight spectrum array to obtain the spectral output for each channel at each wavelength. The spectral synthesis calculation uses a weighted average method. The system calculates weight coefficients based on the spatial arrangement of sub-pixels, with the area weights of the red, green, and blue sub-pixels determined through geometric measurements. The synthesis process linearly combines the spectral output arrays of the three channels according to the weighting coefficients. Specifically, the red spectrum is multiplied by the red weight, the green spectrum by the green weight, and the blue spectrum by the blue weight. Then, the three result arrays are added element by element to obtain the synthesized spectrum.

[0055] Specifically, the generation process of the theoretical emission spectrum includes two steps: normalization and photometric correction. Normalization employs 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 the range of 0 to 1. Photometric correction is achieved by calculating the weighted integral of the luminous efficacy function of the spectrum. The system multiplies the normalized spectrum by the CIE standard luminous efficacy function wavelength by wavelength and then uses the trapezoidal integral 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 a deviation exists, a scaling factor is calculated to correct the spectrum. The final theoretical emission spectrum is stored in the form of structured data, including a wavelength array, a spectral intensity array, and spectral feature parameters, such as dominant wavelength, purity, and chromaticity coordinates. The system also calculates the statistical characteristics of the spectrum, including parameters such as barycentric wavelength, variance, and skewness. These parameters are used in subsequent spectral analysis and matching algorithms.

[0056] 102. Calculate the reflection spectral component of ambient light in the multilayer 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 spectral component.

[0057] In one embodiment of the present invention, the step of calculating the reflection spectral component of ambient light in the multilayer 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 spectral component, includes: calculating the propagation path and scattering characteristics of ambient light in each layer structure based on the optical parameters of the multilayer structure of the liquid crystal display screen to obtain the reflection spectral component of ambient light in the multilayer structure; performing spectral superposition operation on the theoretical emission spectrum and the reflection spectral component according to the wavelength correspondence, and weighting the superposition result through a dynamic weight allocation algorithm to obtain a weighted superimposed spectrum; calculating the spectral output of each pixel under the current ambient light conditions based on the weighted superimposed spectrum to obtain the actual observed spectrum of each pixel.

[0058] Specifically, the calculation of the reflected spectral components of ambient light in the multi-layer structure of the liquid crystal display (LCD) begins with the ambient light spectral detection data. The system first reads the ambient light data detected by the spectrometer, which records the light intensity values ​​at each wavelength point within the range of 380 nm to 780 nm, indexed by wavelength. The propagation path of the ambient light is calculated using a ray tracing algorithm. The system establishes a three-dimensional optical model based on the multi-layer structure parameters of the LCD, including 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 each layer interface according to Snell's law. The application of the refraction law requires consideration of the complex refractive index of each layer material; the real part describes the change in light propagation speed, and the imaginary part describes the absorption and attenuation of light. The propagation calculation of light in the polarizer layer uses the Jones matrix method. The system represents the polarization state of the incident light as a Jones vector, and then multiplies it with the Jones matrix of the polarizer to obtain the polarization state and intensity of the transmitted light. The optical calculations for the liquid crystal layer need to consider the tilt and twist angle distribution of the liquid crystal molecules. The system uses the 4×4 transfer matrix method to calculate the propagation of polarized light in the liquid crystal layer, which can handle the birefringence and optical rotation effects of liquid crystals. The calculation of scattering characteristics adopts a combined model of Mie scattering theory and Rayleigh scattering theory. The system selects the appropriate scattering model according to the size distribution of particles in each layer structure. When the particle size is much smaller than the wavelength of light, the Rayleigh scattering model is used, and when the particle size is close to the wavelength of light, the Mie scattering model is used.

[0059] Specifically, the scattering calculation is implemented using the Monte Carlo method to simulate the random scattering process of a large number of photons in a multilayer structure. The system generates random numbers to determine the scattering direction and probability of photons, with the scattering probability calculated based on the scattering cross-section of each layer and the photon energy. Each photon undergoes multiple scattering events during propagation, and the system records the photon's propagation trajectory and energy changes. Finally, the energy of all backscattered photons is statistically analyzed to obtain the reflection spectral components. The calculation of the reflection spectral components also needs to consider Fresnel reflection at each layer interface. The system calculates the reflection coefficient based on the incident angle and polarization state, and then superimposes the contributions of interface reflection and volume scattering. The Fresnel reflection coefficient is calculated separately for s-polarization and p-polarization components. The system calculates the reflectivity based on the incident angle and the difference in refractive index between the two media, and then performs a weighted average according to the polarization ratio of the incident light. The total reflection spectrum of the multilayer structure is obtained through layer-by-layer cumulative calculation. The system calculates the reflection contribution of each layer starting from the outermost layer, while considering multiple reflections and interference effects between layers. The interference effect is calculated using thin-film optics theory. The system calculates the phase difference of the reflected light between layers and then performs complex number operations to obtain the total reflection intensity after interference. The final reflection spectral components are a 401-dimensional array, with each element corresponding to the intensity of reflected light at a specific wavelength. This array fully describes the reflection characteristics of ambient light in the multilayer structure of the liquid crystal display.

[0060] Specifically, the superposition of the theoretical emission and reflection spectral components is achieved through wavelength-wise addition. The system organizes the theoretical emission and reflection spectral components into arrays of the same length, ensuring complete correspondence between the two spectral data 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, so a dynamic weight allocation algorithm is needed for correction. The dynamic weight allocation algorithm calculates weight coefficients based on the ratio between ambient light intensity and display brightness. Ambient light intensity is obtained by integrating the reflection spectral component to obtain the total reflected luminous flux, and display brightness is obtained by integrating the theoretical emission spectrum to obtain the total emitted luminous flux. The weight calculation uses a sigmoid function model, which provides smooth weight changes under different luminous flux ratios, avoiding display discontinuities caused by abrupt weight changes. The specific implementation of weight allocation involves calculating the ambient light weight and the emitted light weight, the sum of which equals 1. The system multiplies the reflection spectral component by the ambient light weight and the theoretical emission spectrum by the emitted light weight, then adds the two weighted results to obtain the weighted superimposed spectrum. The weighted superimposed spectrum reflects the overall optical output of the pixels under the current ambient light conditions. This spectrum includes both the light actively emitted by the display and the contribution of ambient light reflection.

[0061] Specifically, the calculation of the actual observed spectrum for 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, which describes the impact of different observation geometry 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 correct the weighted superimposed spectrum. The influence of observation distance is calculated using the inverse square law; the system divides the weighted superimposed spectrum by the square of the observation distance to obtain the distance-corrected spectrum. Consideration of human visual characteristics is achieved using the CIE standard observer function. The system convolves the corrected spectrum with the CIE 1931 standard observer's spectral tristimulus value function to obtain an observed spectrum that conforms to human visual characteristics. The convolution operation is implemented by multiplying the spectral data with the observer function wavelength by wavelength and then integrating over the entire visible light range to obtain the X, Y, and Z tristimulus values. The final actual observed spectrum is obtained by converting the tristimulus values ​​back into a spectral distribution; the system uses a spectral reconstruction algorithm to map the XYZ values ​​back to the spectral domain. The spectral reconstruction algorithm uses pre-trained spectral basis functions, linearly combining the tristimulus values ​​as coefficients to reconstruct the 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 range; if so, a color gamut mapping algorithm is used to adjust the spectrum to the displayable range. Color gamut mapping employs the minimum color difference criterion. The system finds the point on the device's color gamut boundary with 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.

[0062] Furthermore, the step of calculating the propagation path and scattering characteristics of the detected ambient light in each layer of the liquid crystal display screen based on the optical parameters of the multilayer structure to obtain the reflection spectral components of the ambient light in the multilayer structure includes: analyzing the optical characteristics of the ambient light based on the incident angle and polarization state of the detected ambient light; calculating the optical reflection parameters of each layer interface based on the refractive index parameters of the polarizer layer, liquid crystal layer, and color filter layer in the multilayer 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 using Rayleigh scattering and Mie scattering models to obtain the scattering spectral distribution of the ambient light in each layer structure; weighting the scattering spectral distribution according to the optical thickness of each layer structure; calculating the interaction influence of the scattering spectra of each layer using an interlayer coupling algorithm to obtain the scattering spectral contribution of each layer structure; accumulating and superimposing the scattering spectral contributions according to the spectral weights; and calculating the overall reflection contribution of the ambient light through spectral normalization to obtain the reflection spectral components of the ambient light in the multilayer structure.

[0063] Specifically, the system detects the incident direction of ambient light using an angle sensor, 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 ray and the normal to the display screen, while the azimuth angle describes the projection direction of the ray onto the horizontal plane. The incident angle is measured using a multi-point photodetector array. The system places multiple photodiodes on the display screen surface and calculates the incident angle by comparing the differences in light intensity received by each detector. Polarization state detection employs a rotating polarizer method. The system inserts a rotatable polarizer into the ambient light path, continuously rotates the polarizer, and records the change curve of transmitted light intensity to analyze and obtain the degree of polarization and polarization direction of the ambient light. The degree of polarization refers to the proportion of polarized light components to the total light intensity, and the polarization direction refers to the direction of the vibration plane of linearly polarized light. These two parameters completely describe the polarization characteristics of the incident light. The optical parameters of the multilayer structure of the liquid crystal display include the complex refractive index, thickness, and surface properties of each layer material. The refractive index parameter of the polarizer layer is measured using an ellipsometer. This parameter has different values ​​at different wavelengths, and the system establishes a wavelength-refractive index correspondence table to store these data. The refractive index of the liquid crystal layer exhibits anisotropic characteristics, with a significant difference between the ordinary and extraordinary refractive indices. The system measures and stores these two parameters separately. The refractive index parameters of the color filter layers are determined based on the optical constants of the filter material, with red, green, and blue filters having different refractive index distributions. The optical reflection parameters at each layer interface are calculated using Fresnel's reflection law. The system calculates the reflection coefficient based on the incident angle, polarization state, and the refractive index difference between adjacent layers. The Fresnel reflection coefficient has two components: s-polarization and p-polarization. S-polarization refers to polarized light with the electric field vibration direction perpendicular to the incident plane, while p-polarization refers to polarized light with the electric field vibration direction parallel to the incident plane. The system calculates the reflection coefficient 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.

[0064] Specifically, layer-by-layer ray tracing calculations employ ray tracing algorithms to simulate the propagation of light in a multi-layered structure. The system represents incident rays as ray objects with a starting point, direction, and energy. When a ray reaches the first interface, the energy distribution of the reflected and transmitted rays is determined based on previously calculated optical reflection parameters. The direction of the reflected ray is calculated according to the law of reflection, the angle of incidence equals the angle of reflection, and the reflected ray lies within the incident plane. The direction of the transmitted ray is calculated according to the law of refraction; the system calculates the angle of refraction based on the ratio of the refractive indices of the two media and the angle of incidence. The propagation of light in each layer of media needs to consider 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, describing the rate of energy attenuation during light propagation. The analysis of scattering characteristics uses Rayleigh scattering and Mie scattering theories to handle scattering particles of different sizes. Rayleigh scattering is applicable when the size of the scattering particles is much smaller than the wavelength of light; the scattering intensity is inversely proportional to the fourth power of the wavelength, which explains why shorter wavelength light is more easily scattered than longer wavelength light. Mie scattering is suitable for situations where the size of the scattering particles is close to or larger than the wavelength of light. The scattering characteristics require calculation using the complex Mie scattering formula, which considers the particle size, shape, and complex refractive index. The system automatically selects an appropriate scattering model based on the particle size distribution in each layer. Rayleigh scattering is used when the average particle radius is less than one-tenth of the light wavelength; otherwise, the Mie scattering model is used. The scattering calculations are implemented using statistical methods. The system randomly generates a large number of scattering events in each layer, and the probability of each 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 intensity of scattered light at each wavelength, forming complete scattering spectral data.

[0065] Specifically, the weighted processing of the scattering spectrum distribution calculates weighting coefficients based on the optical thickness of each layer. Optical thickness refers to the actual propagation distance of light in the medium multiplied by the refractive index of the medium; this parameter describes the optical path difference of light in the medium. The system calculates the optical thickness of each layer and then applies it as a weighting coefficient to the scattering spectrum distribution of the corresponding layer. The weighted calculation is implemented by multiplying the scattering spectrum array with the optical thickness value to obtain a corrected scattering spectrum that considers the influence of layer thickness. The interlayer coupling algorithm is used to calculate the interaction between the scattering spectra of each layer. This interaction originates from multiple scattering and optical interference effects between layers. The coupling calculation uses the transfer matrix method. 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 interlayer transmittance, reflectance, and phase relationship. The system multiplies the transfer matrices of each layer sequentially to obtain the total transfer matrix of the entire multilayer structure. The calculation of the coupling effect also needs to consider the different processing methods of coherent and incoherent scattering. Coherent scattering maintains the phase relationship of the light wave and requires complex number operations, while incoherent scattering only considers the superposition of light intensity and performs real number operations. The system automatically selects the calculation method based on the comparison results 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, and this contribution represents the degree of independent contribution of each layer to the total scattering spectrum.

[0066] Specifically, the cumulative superposition of scattering spectral contributions uses a weighted summation method to calculate the overall reflection contribution of ambient light. The system first determines the spectral weight of each layer's contribution, calculated based on the layer's spatial location, material properties, and optical importance. Layers closer to the surface have higher weights because they have a more direct visual impact on the observer. The calculation of spectral weights also considers the optical constants of each layer's material; layers with higher refractive indices have stronger scattering and reflection effects, thus receiving higher weights. The cumulative superposition is achieved by multiplying the scattering spectral contribution of each layer by its corresponding spectral weight, and then summing all weighted results along the wavelength dimension. The summation process ensures energy conservation; the system checks if the total energy of the superposition result exceeds the incident light energy. If it does, the contribution of each layer is scaled proportionally. Spectral normalization converts the superposition result into standardized reflection spectral components. Normalization aims to eliminate the influence of incident light intensity variations on the shape of the reflection spectrum. The normalization calculation uses a peak normalization method. The system finds the maximum value in the superimposed spectrum and then divides the entire spectrum by this maximum value, normalizing the spectral data to the range of 0 to 1. The resulting reflectance spectral components are a normalized spectral array that describes the variation of ambient light reflection characteristics with wavelength in the multilayer structure of the liquid crystal display. The data format of the reflectance spectral components includes a wavelength array and a corresponding reflectance intensity array. The wavelength array covers the visible light range from 380 nm to 780 nm, and the reflectance intensity array records the normalized reflectance intensity values ​​for each wavelength. This complete reflectance spectral component data provides accurate ambient light reflection information for subsequent spectral overlay and color compensation calculations.

[0067] 103. Calculate the required spectral compensation amount for each pixel based on the difference between the actual observed spectrum and the preset target spectrum, and convert the spectral compensation amount into the correction amount of the RGB driving value through a constraint optimization algorithm to obtain the RGB driving value after ambient light compensation.

[0068] In one embodiment of the present invention, the step of calculating the required spectral compensation amount for each pixel 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 driving value through a constraint optimization algorithm to obtain the ambient light compensated RGB driving value includes: calculating the wavelength-by-wavelength difference between the actual observed spectrum and the preset target spectrum, processing the difference result through a spectral analysis algorithm to obtain the required spectral compensation amount for each pixel; inputting the spectral compensation amount into the constraint optimization algorithm, calculating the correction amount for the RGB driving value according to the hardware constraints of the liquid crystal display screen, optimizing the correction amount through a multi-timescale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB driving value correction amount; and superimposing the optimal RGB driving value correction amount with the original RGB driving value to obtain the ambient light compensated RGB driving value.

[0069] Specifically, the calculation of the difference between the actual 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 actual observed spectrum and the target spectrum have the same wavelength reference. The actual observed spectrum uses 401 data points covering the range of 380 nm to 780 nm, and the target spectrum is also sampled at 1 nm intervals. When the wavelength references of the two spectra are not completely consistent, the system uses a cubic spline interpolation method to resample the data, unifying the two spectra onto the same wavelength grid. The wavelength-by-wavelength difference calculation uses a direct subtraction method. The system subtracts the value of the corresponding wavelength point of the target spectrum from the value of each wavelength point of the actual observed spectrum, resulting in 401 difference data points. The difference results include positive and negative values. A positive value indicates that the intensity of the actual spectrum at that wavelength exceeds the target value, and a negative value indicates that the intensity of the actual spectrum at that wavelength is lower than the target value. The sign information of the difference data is important for subsequent compensation direction determination; a positive difference requires a reduction in the light output at that wavelength, and a negative difference requires an increase in the light output at that wavelength. The spectral analysis algorithm performs frequency domain analysis and feature extraction on the difference results. The system uses Fast Fourier Transform (FFT) to transform 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 spectral shift trend, while high-frequency components reflect the detailed fluctuations in the spectrum. The system calculates the power spectral density of the difference spectrum, identifies the main frequency peaks and bandwidth characteristics, and these characteristics are used to determine the parameter settings of the compensation algorithm. The calculation of the spectral compensation amount adopts an adaptive filtering method. The system designs a corresponding compensation filter based on the spectral characteristics of the difference spectrum. The filter design considers the spectral response characteristics of the LCD display. The system reads the spectral response functions of the three RGB channels, which describe the sensitivity of each channel to different wavelengths of light. The calculation of the compensation amount requires converting the spectral difference into an RGB adjustment amount that the device can achieve. The system uses a spectral matching algorithm to find the optimal RGB combination to approximate the target spectral compensation.

[0070] Specifically, the implementation of the constrained optimization algorithm begins with establishing hardware constraints and constructing a mathematical model of the optimization problem. The hardware constraints of the LCD screen include physical constraints such as the dynamic range limit of RGB driving values, power consumption limits, and response time limits. The dynamic range limit of RGB driving values ​​stipulates that the value of each channel must be between 0 and 255; the system expresses these boundary conditions as linear inequality constraints. The power consumption limit is determined based on the maximum power consumption specification of the display screen. The system calculates the power consumption contribution of the three RGB channels, and the power consumption coefficients of the red, green, and blue channels are determined based on the efficiency characteristics of the LEDs or backlight, respectively. The mathematical expression of the power consumption constraint is that the weighted sum of the RGB driving values ​​does not exceed a preset power consumption upper limit. The response time limit considers the dynamic response characteristics of the 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 the RGB correction amount does not cause the response time to exceed the 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 Lagrange function, and the constraints are introduced into the objective function through Lagrange multipliers to form an augmented optimization objective. During the iterative solution process, the system calculates the gradient information of the objective function and constraint functions, updates the optimization variables and Lagrange multipliers, until the convergence condition is met. Convergence is determined using a dual criterion of gradient norm and constraint violation degree. When the gradient norm is less than a preset threshold and all constraints are satisfied, the algorithm converges to the optimal solution. The application of the multi-timescale modulation strategy considers the multi-timescale characteristics of the liquid crystal response. The response of liquid crystal molecules includes a fast molecular reorientation process and a slow molecular diffusion process. The system decomposes the RGB correction into fast and slow components. The fast component corresponds to the electro-optic 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.

[0071] Specifically, the time-scale decomposition is implemented using wavelet transform. The system selects wavelet basis functions with good time-frequency localization characteristics to perform multi-scale decomposition of the RGB correction values. Wavelet transform decomposes the correction signal into wavelet coefficients of different frequency bands. High-frequency coefficients correspond to rapidly changing components, and low-frequency coefficients correspond to slowly changing components. The system determines the threshold for frequency band division based on the liquid crystal response time constant; components with a response time less than 10 milliseconds are classified as fast components, and those with a response time greater than 10 milliseconds are classified as slow components. Different modulation strategies are used to process each frequency band component after decomposition. Fast components are instantaneously modulated and directly applied to the RGB driving values, while slow components are progressively modulated and gradually applied to the driving values ​​through time integration. The implementation of RGB cross-coupling modulation is based on the coupling characteristics of the color space. The three RGB channels influence each other when generating colors; changes in the red channel affect hue and saturation, changes in the green channel mainly 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 of influence of changes in each channel on other channels. 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 shift caused by changes in each channel. Cross-coupling modulation is calculated using an iterative compensation method. The system calculates the expected shift in the color space based on the current RGB correction, then calculates the required compensation amount through the inverse operation of the coupling matrix, and adds the compensation amount to the original correction amount to obtain a new correction amount. The iterative process is repeated until the color shift is less than a preset tolerance range, typically requiring 3 to 5 iterations to achieve convergence. The optimal RGB driving value correction is determined using a multi-objective optimization method, where the system simultaneously considers multiple optimization objectives such as spectral matching accuracy, hardware constraint satisfaction, and computational complexity.

[0072] Specifically, the superposition operation is implemented by merging the optimal RGB driving value correction with the original RGB driving value using numerical addition. The system first checks the range of the correction values ​​to ensure the superimposed result does not exceed the valid range of the RGB driving values. When the superposition result exceeds the range of 0 to 255, the system uses a saturation processing method, setting values ​​exceeding the upper limit to 255 and values ​​below the lower limit to 0. Saturation processing introduces non-linear distortion; the system reduces the impact of saturation through a pre-compensation method, considering saturation limits in advance when calculating the correction value and appropriately reducing the correction amplitude to avoid saturation. The superposition operation also needs to consider the impact of numerical precision; the original RGB driving value is represented using an 8-bit integer, while the correction value is represented using a floating-point number to maintain calculation precision. After superposition, the system rounds the result, converting the floating-point result into an integer driving value. Quantization errors during rounding are compensated for using an error diffusion algorithm; the system distributes the quantization error of the current pixel to the correction values ​​of adjacent pixels, reducing overall quantization distortion. After ambient light compensation, the output of the RGB driving value is quickly converted using a lookup table. 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 value from the lookup table based on the current ambient light detection result, and then superimposes it with the original driving value to obtain the final output. The lookup table is established considering the main changing parameters of ambient light, including light intensity, color temperature, and incident angle. The system quantizes these parameters into discrete sampling points and calculates the corresponding optimal RGB correction value at each sampling point. The interpolation calculation uses a 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 an accurate correction value.

[0073] Furthermore, the step of inputting the spectral compensation amount into the constraint optimization algorithm, calculating the correction amount of the RGB driving value according to the hardware constraints of the liquid crystal display screen, and optimizing the correction amount through a multi-timescale modulation strategy and RGB cross-coupling modulation to obtain the optimal RGB driving value correction amount includes: inputting the spectral compensation amount into the constraint optimization algorithm, calculating the initial RGB driving value correction amount through constraint solving based on the constraints established by the hardware constraints of the liquid crystal display screen; performing time-frequency decomposition on the initial RGB driving value correction amount using the multi-timescale modulation strategy, modulating each timescale component in the time-frequency decomposition process according to the liquid crystal molecule response characteristics to obtain the time-domain optimized correction amount; performing RGB cross-coupling modulation on the time-domain optimized correction amount according to the spectral coupling characteristics between the three RGB channels to obtain the cross-modulation correction amount; verifying the stability of the cross-modulation correction amount, optimizing and adjusting the unstable components through convergence analysis to obtain the optimal RGB driving value correction amount.

[0074] Specifically, the spectral compensation received by the system is stored as a 401-dimensional vector, with each element corresponding to the compensation intensity at a specific wavelength. The system needs to convert this spectral domain compensation information into adjustment parameters for the RGB color space. The conversion process uses a color matching function method. 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 of the compensation spectrum by the corresponding matching function value, and then performs integration across the entire visible light range to obtain the compensation requirements for each of the three RGB channels. The integration calculation uses the trapezoidal integral method to achieve numerical integration. The system divides the visible light range into 400 trapezoidal intervals, and the area of ​​each interval is calculated using the trapezoidal formula. The final integration result represents the required luminous flux adjustment for each channel. The establishment of hardware constraints for the LCD display encompasses multiple physical and performance limitations. The range constraint of the RGB drive values ​​stipulates that the value of each channel must be within the range of 0 to 255 (8-bit integers). The system expresses these boundary conditions 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 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 RGB driving values ​​to ensure that the total power consumption does not exceed the design limit. Response time constraints consider the dynamic characteristics of 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 is within the liquid crystal's response capability range. The constraint solution employs an interior-point optimization algorithm. This algorithm transforms inequality constraints into an unconstrained optimization problem by introducing a barrier function. The system establishes a Lagrangian function, combining the objective function and constraints to form an augmented objective function. The barrier parameter controls the weight of the constraints, gradually decreasing as the iteration process progresses.

[0075] 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, and the Hessian matrix describes the second-order curvature characteristics of the objective function. The calculation of the Newton direction is achieved by solving a system of linear equations. The system uses the Cholesky decomposition method to solve for the inverse of the Hessian matrix to obtain the optimal search direction. The step size selection adopts a backtracking search algorithm. The system starts with a unit step size and gradually decreases the step size until the Armijo condition is met, ensuring that the objective function value decreases sufficiently. Convergence is judged based on the dual criteria of 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 driving value correction includes the adjustment values ​​of the red, green, and blue channels. These values ​​represent the maximum compensation amplitude that can be achieved under the current constraints. The application of the multi-timescale modulation strategy is based on the multi-level time characteristics of the liquid crystal molecule response. The response process of the liquid crystal display includes physical processes at multiple timescales, such as molecular reorientation, viscoelastic recovery, and thermal diffusion. The time-frequency decomposition is implemented using the continuous wavelet transform method. The system selects the Morlet wavelet as the basis function, which has good time-frequency localization characteristics and can provide time and frequency information simultaneously. The wavelet transform calculation is implemented through 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 based on 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 its 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.

[0076] Specifically, the modeling of the liquid crystal molecule response characteristics uses the Debye relaxation model to describe the dynamic process of molecular orientation. The system calculates the relaxation time constant based on the dielectric constant and elastic constant of the liquid crystal material. Since the relaxation time constant varies with temperature, the system establishes a temperature-relaxation time lookup table and selects the appropriate parameter value based on the current operating temperature. Modulation processing is achieved through time-domain convolution operations. The system convolves the wavelet coefficients at each time scale with the corresponding response function to obtain correction coefficients that consider the dynamic characteristics of the liquid crystal. The reconstruction of the time-domain optimized correction is achieved using inverse wavelet transform. The system linearly combines the wavelet coefficients at each scale after modulation processing to reconstruct the time-domain optimized RGB correction. The reconstruction process needs to ensure signal integrity; the system uses a perfect reconstruction filter bank to ensure that the inverse transform result is energy equivalent to the original signal. The implementation of RGB cross-coupling modulation is based on the mutual influence characteristics of the color space. The three RGB channels have complex nonlinear coupling relationships when generating colors. The modeling of spectral coupling characteristics uses spectral overlap analysis. The system calculates the overlap integral between 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 exhibit 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 effects between channels. The coupling matrix was established by experimentally measuring the actual color output under different RGB combinations. The system performed measurements at the vertices and edges of the RGB cube, recording the correspondence between input RGB values ​​and output chromaticity coordinates. The measurement data was analyzed using a multiple linear regression method. The system established a linear model between RGB input and chromaticity output, with the regression coefficients forming a 3×3 coupling matrix. Cross-coupling modulation was calculated using matrix operations. The system represented the temporal optimization correction as a 3×1 vector, which was multiplied by the coupling matrix to obtain the correction considering the mutual influence between channels.

[0077] Specifically, the results of matrix operations 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 amplitude of the original correction to restore a suitable adjustment intensity. The cross-modulation correction contains compensation information for inter-channel coupling effects, which can reduce color shift and saturation loss during RGB adjustment. Stability verification is achieved by analyzing the convergence characteristics of the correction using Lyapunov stability theory. The system establishes a state-space model of the display system, using RGB driving values ​​as state variables and the correction as control input. The establishment of the state equation considers the dynamic characteristics of the liquid crystal response and the influence of environmental disturbances. Eigenvalue analysis of the system matrix reveals the stability characteristics of the system. The Lyapunov function is constructed using a quadratic form function. The system defines a positive definite 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 achieved by calculating the convergence rate and convergence region of the correction sequence. The system monitors the change amplitude of the correction between consecutive iterations, and considers the sequence to converge when the change amplitude is less than a preset threshold multiple times consecutively. Unstable components are identified using frequency domain analysis. The system performs a Fourier transform on the cross-modulation correction to analyze unstable frequency components in the spectrum. Frequency points with an amplitude greater than 1 correspond to unstable modes, and the system uses frequency domain filtering to suppress these unstable components. Optimization is achieved using an adaptive control strategy. The system adjusts the gain and phase of the correction based on the stability analysis results to ensure the corrected system meets stability requirements. The optimal RGB drive value correction is determined using a multi-objective trade-off method. The system simultaneously considers compensation accuracy, stability, and computational complexity, obtaining the correction parameter with the best overall performance through Pareto optimal selection.

[0078] 104. Calculate the actual white point color coordinates of the display screen based on the RGB driving value after ambient light compensation, and adjust the actual white point color coordinates to the standard white point position using a progressive white point migration algorithm.

[0079] In one embodiment of the present invention, the step of calculating the actual white point color coordinates of the display screen based on the ambient light-compensated RGB driving 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 driving values ​​through CIE color space transformation; calculating the coordinate difference between the actual white point color coordinates and the preset standard white point position; determining migration path parameters based on the characteristics of the display content 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 driving values ​​based on the white point migration control parameters to obtain white point corrected RGB driving values; and generating a PWM control signal based on the white point corrected RGB driving values ​​and outputting it to each pixel unit of the liquid crystal display screen for display control.

[0080] Specifically, the ambient light-compensated RGB drive values ​​are used to calculate the actual white point color coordinates through CIE color space transformation. The system first normalizes the RGB values ​​to the range of 0 to 1, and then applies the display's color feature matrix for linear transformation. The color feature matrix is ​​a 3×3 coefficient matrix, whose elements are determined by measuring the CIE XYZ tristimulus values ​​of the display's three primary colors: red, green, and blue. This matrix describes the conversion relationship between the device-dependent RGB color space and the device-independent XYZ color space. The matrix transformation calculation uses standard matrix multiplication, multiplying the RGB vectors by the feature matrix to obtain the XYZ tristimulus values, where X represents the perceived red, Y represents the perceived luminance, and Z represents the perceived blue. The white point corresponds to the color output when there is an equal amount of RGB input. The system sets the ambient light-compensated RGB drive values ​​to equal values ​​and takes the average of the three channels as the input parameter for white point calculation. After calculating the XYZ tristimulus values, the system uses a chromaticity coordinate transformation formula to convert the XYZ values ​​into xy chromaticity coordinates. The chromaticity coordinate x equals X divided by the sum of X, Y, and Z, and the chromaticity coordinate y equals Y divided by the sum of X, Y, and Z. This normalization process eliminates the influence of luminance, retaining only chromaticity information. The numerical precision of the actual white point chromaticity coordinates directly affects the subsequent color correction effect. The system uses double-precision floating-point numbers for calculation, maintaining at least 6 significant digits of precision. The calculation of chromaticity coordinates also needs to consider numerical stability. When the sum of the XYZ tristimulus values ​​is close to zero, the system uses special handling to avoid division by zero errors, setting the chromaticity coordinates to the default values ​​of the standard illuminant.

[0081] Specifically, the difference between the actual white point chromatic coordinates and the standard white point position is calculated using the Euclidean distance metric. The standard white point position is selected based on the requirements of the display application; commonly used standards include the chromaticity coordinates (0.3127, 0.3290) for the D65 illuminator and (0.3457, 0.3585) for the D50 illuminator. The system calculates the difference between the actual white point and the standard white point in both the x and y dimensions. The magnitude of the difference vector represents the degree of chromaticity shift, and the direction of the difference vector represents the direction of the chromaticity shift. The progressive white point migration algorithm determines the migration path parameters based on the characteristics of the display content. This algorithm considers the perceptual characteristics of human eyes to color changes and the complexity of the display content. The display content characteristic analysis includes statistical features such as the image's average brightness, contrast, color richness, and spatial frequency. The system extracts these feature parameters through image processing algorithms. Average brightness is obtained by calculating the mean of the grayscale values ​​of all pixels in the image. Contrast ratio is represented by the ratio of standard deviation to mean. Color richness is quantified by calculating the entropy value of the chromaticity distribution, and spatial frequency is analyzed through the statistical distribution of gradient amplitude. The migration path parameters are determined using a piecewise linear interpolation method. The system adjusts the migration step size and migration speed according to the complexity of the displayed content. Complex content uses a smaller step size and slower speed to avoid perceptible color jumps, while simple content uses a larger step size and faster speed to reduce adjustment time. The migration path is represented 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 Bézier curve fitting, and the position of the control point is optimized based on the principle of perceptual uniformity to ensure the uniformity of color difference changes during migration. 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.

[0082] Specifically, the white balance matrix transformation performs color space correction on the RGB driving values ​​after ambient light compensation based on white point migration control parameters. The white balance matrix is ​​a diagonally dominant 3×3 matrix, where diagonal elements represent the gain adjustment coefficients of each channel, and off-diagonal elements represent the color coupling correction coefficients between channels. The calculation of matrix elements adopts the von Klee 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. The calculation of 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 uses an iterative optimization method to solve for the optimal gain combination. The iteration process adopts the Newton-Raphson method. The system calculates the Jacobian matrix of chromaticity error with respect to the gain parameters, and updates the gain estimate through matrix inversion and vector multiplication. The convergence criterion is set as a chromaticity error of less than 0.001, corresponding to the threshold level at which the human eye can just perceive color difference. The off-diagonal elements of the white balance matrix are determined by least squares fitting. The system measures the chromaticity output under different RGB combinations and establishes an overdetermined system of equations to solve for the cross-coupling coefficients. Matrix transformation is calculated using standard matrix-vector multiplication, multiplying the ambient light-compensated RGB driving value vector with the white balance matrix to obtain the RGB values ​​after white point correction. The transformation process requires checking 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 subject to saturation limiting. Saturation can introduce color distortion; the system reduces the probability of saturation through pre-compensation methods, pre-considering dynamic range limitations when calculating the white balance matrix and appropriately constraining the range of gain coefficient values.

[0083] Specifically, the RGB driving values ​​after white point correction need to be converted into PWM control signals to drive the pixel units of the LCD screen. The PWM signal is a periodic pulse width modulation square wave, and its duty cycle is proportional to the RGB driving value. The system sets the base frequency of the PWM signal to 240Hz, which is much higher than the flicker fusion frequency of the human eye to avoid visible flickering, while being lower than the cutoff frequency of the LCD response to ensure sufficient driving effect. The PWM duty cycle calculation maps the 8-bit RGB driving value to a duty cycle range of 0% to 100%, using a linear interpolation method. An RGB value of 0 corresponds to a 0% duty cycle, and an RGB value of 255 corresponds 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 the timing accuracy of the PWM signal, with the clock frequency set to 61.44MHz to provide 256 levels of duty cycle resolution. The PWM signal is generated using a dedicated timing control chip, which integrates a multi-channel PWM generator and a drive buffer, capable of simultaneously outputting hundreds of independent PWM signals. The signal output to the LCD screen requires level conversion and power amplification. The system uses MOSFET power switches to convert the 5V logic signal into a 15V LCD driving voltage. The drive circuit design considers signal transmission integrity and electromagnetic compatibility, employing differential signal transmission and shielded cables to reduce the impact of external interference. Pixel unit driving adopts an active matrix method, with each sub-pixel equipped with an independent thin-film transistor switch. The PWM signal is sequentially applied to each pixel through row and column scanning. The scanning timing control needs to be synchronized with the PWM signal. The system uses a double buffering mechanism to avoid image tearing during display. The display data of the current frame is updated in the background buffer, and the front and background buffers switch roles after display is completed. The final output of the display control is a stable image display effect. The color performance after white point correction is more accurate and consistent, and the display quality under different ambient light conditions is effectively guaranteed.

[0084] In this embodiment, the theoretical emission spectrum is obtained by performing nonlinear spectral mapping processing on the input RGB driving value and combining it with the response characteristics of liquid crystal molecules. The reflection 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 an RGB correction value using a constrained optimization algorithm, resulting in the ambient light-compensated RGB driving value. 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 according to real-time ambient light conditions, effectively compensating for the influence of ambient light reflection on color. Simultaneously, white point correction ensures color temperature consistency and color accuracy, significantly improving display quality under different ambient light conditions and enhancing the user's visual experience.

[0085] The display control method of the liquid crystal display screen in the embodiments of the present invention has been described above. The display control system of the liquid crystal display screen in the embodiments of the present invention will be described below. Please refer to [link / reference]. Figure 2 One embodiment of the display control system for the liquid crystal display screen in this invention includes:

[0086] The spectral mapping module 201 is 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 to obtain the theoretical emission spectrum of each pixel by combining the liquid crystal molecule response characteristics and temperature compensation parameters.

[0087] The environmental compensation module 202 is used to calculate the reflection spectral component of ambient light in the multilayer 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 spectral component.

[0088] The spectral correction module 203 is used to calculate the required spectral compensation amount for each pixel based on the difference between the actual observed spectrum and the preset target spectrum, and convert the spectral compensation amount into the correction amount of the RGB driving value through a constraint optimization algorithm to obtain the RGB driving value after ambient light compensation.

[0089] The white point adjustment module 204 is used to calculate the actual white point color coordinates of the display screen based on the RGB driving value after ambient light compensation, and adjust the actual white point color coordinates to the standard white point position through a progressive white point migration algorithm.

[0090] In this embodiment of the invention, the display control system of the liquid crystal display screen operates the aforementioned display control method. The display control system performs nonlinear spectral mapping processing on the input RGB driving values ​​and combines this with the response characteristics of liquid crystal molecules to obtain the theoretical emission spectrum. It calculates the reflection spectral components in the multilayer structure based on the ambient light spectrum and superimposes them with the theoretical emission spectrum to obtain the actual observed spectrum. It calculates the difference between the actual observed spectrum and the target spectrum and converts it into an RGB correction value using a constraint optimization algorithm to obtain the ambient light compensated RGB driving value. Finally, it calculates the actual white point color coordinates and adjusts them to the standard white point position using a progressive white point migration algorithm. This invention can dynamically adjust display parameters according to real-time ambient light conditions, effectively compensating for the influence of ambient light reflection on color. Simultaneously, it ensures 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.

[0091] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system, device, or unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0092] 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, in essence, or the part 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0093] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A display control method of a liquid crystal display, characterized by, The display control method of the liquid crystal display screen comprises: The input RGB drive value is subjected to nonlinear spectral mapping processing based on the mapping relationship of liquid crystal transmittance and backlight spectrum, and the theoretical emission spectrum of each pixel point is obtained by combining the liquid crystal molecule response characteristic and the temperature compensation parameter; The reflection spectrum component of ambient light in the multi-layer structure of the liquid crystal display screen is calculated according to the detected ambient light spectrum, and the actual observation spectrum of each pixel point is obtained by superimposing the theoretical emission spectrum and the reflection spectrum component; The actual observation spectrum and the preset target spectrum are subjected to wavelength-by-wavelength difference calculation, the difference result is processed by a spectral analysis algorithm, and the required spectral compensation amount of each pixel point is obtained; the spectral compensation amount is input into a constraint optimization algorithm, the initial RGB drive value correction amount of the RGB drive value is calculated by constraint solving according to the constraint condition established based on the hardware limitation condition of the liquid crystal display screen; the initial RGB drive value correction amount is subjected to time-frequency decomposition by using a multi-time scale modulation strategy, the time scale components in the time-frequency decomposition process are modulated according to the liquid crystal molecule response characteristic, and the time domain optimization correction amount is obtained; the time domain optimization correction amount is subjected to RGB cross-coupling modulation according to the spectral coupling characteristic among the RGB three channels, and the cross-modulation correction amount is obtained; the cross-modulation correction amount is subjected to stability verification, and the unstable components are optimized and adjusted through convergence analysis, and the optimal RGB drive value correction amount is obtained; the optimal RGB drive value correction amount and the original RGB drive value are subjected to superposition operation, and the RGB drive value after ambient light compensation is obtained; The actual white point color coordinate of the display screen is calculated according to the RGB drive value after ambient light compensation, and the actual white point color coordinate is adjusted to the standard white point position by using a gradual white point migration algorithm.

2. The display control method of a liquid crystal display according to claim 1, wherein The nonlinear spectral mapping processing of the input RGB drive value based on the mapping relationship of liquid crystal transmittance and backlight spectrum, and the theoretical emission spectrum of each pixel point obtained by combining the liquid crystal molecule response characteristic and the temperature compensation parameter comprise: The RGB three-channel transmittance components of each pixel point are calculated by the mapping relationship of the liquid crystal transmittance and the backlight spectrum according to the input RGB drive value; The RGB three-channel transmittance components are subjected to nonlinear response correction according to the liquid crystal molecule response characteristic, and the transmittance coefficient under the actual working condition is obtained by combining the temperature compensation parameter for temperature drift compensation of the corrected transmittance component; The transmittance coefficient and the backlight spectrum are subjected to wavelength-by-wavelength product operation and spectral synthesis calculation, and the theoretical emission spectrum of each pixel point is obtained.

3. The display control method of the liquid crystal display according to claim 1, wherein The reflection spectrum component of ambient light in the multi-layer structure of the liquid crystal display screen is calculated according to the detected ambient light spectrum, and the actual observation spectrum of each pixel point is obtained by superimposing the theoretical emission spectrum and the reflection spectrum component; The propagation path and scattering characteristic of ambient light in each layer structure are calculated according to the optical parameters of the multi-layer structure of the liquid crystal display screen, and the reflection spectrum component of ambient light in the multi-layer structure is obtained; The theoretical emission spectrum is superimposed on the reflection spectrum component according to a wavelength correspondence relationship, a superimposed result is weighted by using a dynamic weight distribution algorithm, and a weighted superimposed spectrum is obtained; A spectral output of each pixel point under a current ambient light condition is calculated according to the weighted superimposed spectrum, and an actual observation spectrum of each pixel point is obtained.

4. The display control method of the liquid crystal display according to claim 3, wherein The reflection spectrum component of the ambient light in the multi-layer structure is obtained by calculating the propagation path and scattering characteristics of the ambient light in each layer structure of the multi-layer structure of the liquid crystal display screen according to the optical parameters of the multi-layer structure of the liquid crystal display screen, including: The optical reflection parameters of each layer interface are calculated according to the refractive index parameters of the polarizer layer, the liquid crystal layer and the color filter layer in the multi-layer structure of the liquid crystal display screen by analyzing the optical characteristics of the ambient light according to the incident angle and the polarization state of the detected ambient light; The scattering spectrum distribution of the ambient light in each layer structure is obtained by performing layer-by-layer ray tracing calculation on the ambient light in each layer structure according to the optical reflection parameters, and analyzing the scattering characteristics of the ambient light by using Rayleigh scattering and Mie scattering models; The scattering spectrum contribution of each layer structure is obtained by weighting the scattering spectrum distribution according to the optical thickness of each layer structure, and calculating the interaction influence of the scattering spectrum of each layer by using a layer coupling algorithm. The reflection spectrum component of the ambient light in the multi-layer structure is obtained by cumulatively superimposing the scattering spectrum contribution according to the spectral weight, and calculating the overall reflection contribution of the ambient light by using spectral normalization processing.

5. The display control method of the liquid crystal display according to claim 1, wherein The actual white point color coordinates of the display screen are calculated according to the RGB drive values compensated by the ambient light, and the actual white point color coordinates are adjusted to a standard white point position by using a gradual white point migration algorithm, including: The actual white point color coordinates of the display screen are calculated according to the RGB drive values compensated by the ambient light by using CIE color space conversion; The white point migration control parameters are obtained by 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 by using the gradual white point migration algorithm, and performing white balance matrix conversion on the RGB drive values compensated by the ambient light according to the white point migration control parameters. The white point corrected RGB drive values are obtained by performing white balance matrix conversion on the RGB drive values compensated by the ambient light according to the white point migration control parameters. The PWM control signal is generated according to the white point corrected RGB drive values, and is output to each pixel unit of the liquid crystal display screen for display control.

6. A display control system for a liquid crystal display panel, characterized by comprising: The display control system of the liquid crystal display screen includes: A spectrum mapping module is configured to perform nonlinear spectrum mapping processing on input RGB drive values based on a mapping relationship between liquid crystal transmittance and backlight spectrum, and obtain a theoretical emission spectrum of each pixel point by combining liquid crystal molecule response characteristics and temperature compensation parameters; An ambient compensation module is configured to calculate a reflection spectrum component of ambient light in a multi-layer structure of a liquid crystal display screen according to a spectrum of detected ambient light, and obtain an actual observation spectrum of each pixel point by superimposing the theoretical emission spectrum and the reflection spectrum component. An ambient compensation module is configured to calculate a reflection spectrum component of ambient light in a multi-layer structure of a liquid crystal display screen according to a spectrum of detected ambient light, and obtain an actual observation spectrum of each pixel point by superimposing the theoretical emission spectrum and the reflection spectrum component. The spectrum correction module is configured to calculate a wavelength-by-wavelength difference between the actual observation spectrum and a preset target spectrum, process a difference result by a spectrum analysis algorithm, and obtain a required spectrum compensation amount of each pixel point; input the spectrum compensation amount into a constraint optimization algorithm, establish a constraint condition according to a hardware limitation condition of the liquid crystal display screen, calculate an initial RGB drive value correction amount of an RGB drive value by constraint solving, adopt a multi-time scale modulation strategy for time-frequency decomposition on the initial RGB drive value correction amount, modulate each time scale component in the time-frequency decomposition process according to a liquid crystal molecule response characteristic, obtain a time domain optimization correction amount, modulate the time domain optimization correction amount according to a spectrum coupling characteristic among RGB three channels to obtain a cross-modulation correction amount, verify stability of the cross-modulation correction amount, optimize and adjust unstable components by convergence analysis, and obtain an optimal RGB drive value correction amount; and superimpose the optimal RGB drive value correction amount and an original RGB drive value to obtain an ambient light compensated RGB drive value. The white point adjustment module is configured to calculate an actual white point color coordinate of the display screen according to the ambient light compensated RGB drive value, and adjust the actual white point color coordinate to a standard white point position by a gradual white point migration algorithm.

Images