2967 results about "Ambilight" patented technology

The invention discloses a high-precision image processing method and system based on illumination adaptive compensation, and relates to the technical field of computer vision and image processing, and the method comprises the steps: inputting an original image, and dividing the image into a high-frequency edge layer, an intermediate-frequency texture layer and a low-frequency illumination layer through a multi-scale residual network; acquiring illumination intensity, color temperature and scene categories in real time by using an ambient light sensor and a scene semantic segmentation model, and generating dynamic compensation parameters; carrying out dynamic range expansion on a low-frequency illumination layer based on a physical illumination model, and adjusting the weight of highlight suppression and dark area enhancement through a self-adaptive S-shaped exposure curve; a double-branch generative adversarial network is adopted, noise suppression and super-resolution reconstruction are carried out on the high-frequency layer, and texture detail enhancement is carried out on the intermediate-frequency layer; aligning the data of the depth camera and the infrared sensor with the visible light image through a cross-modal fusion module; and performing tone mapping on the fused image based on human visual characteristics, and outputting an enhanced image with a high dynamic range and reserved details.

The invention provides a scene reconstruction method based on delayed rendering and three-dimensional Gaussian. The method comprises the following steps: S1, generating initial three-dimensional point cloud data based on a multi-view image; s2, constructing a trainable structural body for three-dimensional Gaussian modeling; s3, normal initialization and residual optimization are carried out on the Gaussian ellipsoid primitives, depth consistency constraint is combined, and a differentiable and learnable normal reconstruction mechanism is realized, so that the geometric expression ability of illumination modeling is enhanced; s4, introducing a reflection training mechanism based on ambient light and a reflection direction, and generating a Gaussian attribute based on a visual angle; and S5, a final image is generated through a differentiable Gaussian sputtering rendering algorithm, and optimization is carried out through pixel loss of the final image and a real image. According to the method, the reality sense and geometric consistency of the Gaussian sputtering model under the complex illumination condition are remarkably improved, and the technical problems of unreal rendering effect, inaccurate surface normal estimation, weak propagation capability and the like of the existing three-dimensional Gaussian sputtering model under the complex illumination condition are solved.

The invention provides an intelligent event identification method and system based on a high-speed camera, and the method comprises the steps: setting the collection parameters of the high-speed camera, and triggering the camera to collect a target scene video stream. And hardware acceleration decoding processing is carried out on the collected original video data stream, real-time environment illumination information of the environment illumination sensor is obtained, and dynamic brightness equalization processing is executed. And performing motion adaptive denoising processing on the video sequence. Geometric distortion correction is carried out on the image sequence through camera calibration parameters, sub-pixel-level displacement vectors and dense optical flow field data of a moving object are extracted, and multi-scale morphological features are extracted. And the features are fused to generate motion feature data, the data are processed through a spatio-temporal joint event classification model, an event identification result is output, the result is bound with a high-precision timestamp, and event identification information is output to an industrial control system display device in real time. According to the invention, the accuracy and real-time performance of event identification can be improved.

The invention relates to a light control method and system based on AI model analysis, and the method comprises the steps: obtaining environment illumination data of a target scene and user interaction input, and carrying out the semantic demand analysis, and obtaining semantic description information; performing illumination demand analysis on the semantic description information through a pre-trained light driving model to obtain illumination demand parameters; performing light field demand analysis on the illumination demand parameters according to the environment illumination data and the user interaction input, and generating light field control information; and acquiring power load data, performing instruction construction on the light field control information, and generating a light control instruction. According to the invention, dynamic self-adaptive regulation and control of the light environment can be realized, and the limitation that the existing method only depends on static compensation and cannot adapt to complex scene changes is overcome.

The invention discloses an end-to-end automatic driving method based on dynamic multi-modal fusion in a complex scene, and belongs to the technical field of automatic driving. In order to solve the problems of sensor perception deficiency, cross-modal feature mismatching, unstable trajectory planning and the like easily occurring in night, low-illumination and complex dynamic environments in the existing end-to-end automatic driving method, texture details of a camera mode and geometric structure features of a laser radar mode are respectively enhanced through a double-flow feature refining mechanism; the characteristic difference between different modes is relieved; an information-driven dynamic fusion strategy is designed, the fusion weight is adaptively adjusted according to scene factors such as environment illumination and obstacle density, and the scene sensitivity and discrimination ability of the model are improved; asymmetric convolution and a low-rank-sparse decoupling technology are introduced, multi-order reconstruction of key channels is carried out on the multi-modal features, and the path change modeling capability is enhanced; and in combination with time sequence dependence of waypoints, outputting a future trajectory through an autoregression decoder to realize high-precision trajectory prediction and stable decision control.

The invention relates to the technical field of display, and particularly discloses a dynamic ambient light adaptive OLED display optimization method and system, and the method comprises the steps: obtaining an ambient light time sequence data set of an environment where an OLED display screen is located, and synchronously obtaining real-time display parameters and historical brightness adjustment data of the display screen; acquiring ambient light sensing features according to the ambient light time sequence data set; obtaining photo-thermal structure coverage area data of the OLED display screen according to the real-time display parameters; and acquiring preliminary optimization parameters according to the ambient light sensing characteristics and the photo-thermal structure coverage area data. According to the invention, illumination intensity, spectrum drift and contrast change are captured in real time in combination with ambient light perception characteristics, the one-sidedness of adjustment only according to brightness traditionally is solved, reflection can be reduced through photothermal structure deformation under strong light, brightness can be improved to offset interference, and human visual characteristics can be matched under weak light. And the display definition and the visual comfort in different environments are effectively improved.

The invention relates to the field of commodity visualization, in particular to a commodity display interaction visualization method and device. The method comprises the following steps: collecting a multi-azimuth image of a commodity, carrying out three-dimensional texture modeling, and constructing a three-dimensional texture mapping model; performing material light rendering on the three-dimensional texture mapping model to generate a material rendering result; collecting an environment detection image of a commodity display environment, and performing environment illumination adaptation compensation on a material rendering result to obtain an illumination compensation rendering commodity; carrying out attribute information visual layout on the illumination compensation rendering commodity to obtain a commodity visual space; and carrying out interaction response animation analysis according to the commodity visualization space, carrying out multi-target parallel rendering, and executing commodity interaction visualization operation. The form and surface details of the commodity in the real world are accurately restored, the visual reality sense is improved, and the interactive experience feeling of browsing the commodity by a user is enhanced.

The invention relates to the technical field of optical lens defect detection, and particularly discloses an optical lens laser-induced damage on-line detection method and system, a linear polarizer and a narrow-band filter are connected in series in a detection laser light path, non-target polarized light is filtered through polarization direction matching, meanwhile, interference of the environment and scattered light is inhibited through the narrow-band filter, and the laser-induced damage on-line detection system is obtained. According to the method, external source noise such as ambient light and non-target polarized light is reduced through polarization matching and narrow-band filtering, randomness of speckle noise is offset through multi-angle collection and signal fusion in a visual detection mode, exposure is dynamically adjusted, an image is fused to improve the signal-to-noise ratio, noise and real signals are decoupled through self-supervised learning, and the real-time performance of the system is improved. Dust interference is removed in combination with morphological operation; a deep learning reasoning model enhances the damage identification capability in a noise environment, defocusing blur caused by mechanical vibration is eliminated through phase conjugate correction, and the influence of photoelectric conversion noise, dust interference and the like on the detection efficiency and accuracy is remarkably reduced through multi-link linkage.

The invention discloses a virtual-real fusion exhibition display interaction system and a multi-mode perception method, and belongs to the technical field of exhibition display interaction. The system collects audience eyeball fixation points, gesture actions and ambient light data through AR / VR equipment, analyzes coordinates of a region of interest through an eyeball fixation point attention mechanism, a gesture space-time encoder and a multi-modal fusion unit, triggers holographic projection explanation and virtual exhibition stand light and shadow dynamic adjustment (including illumination intensity, color, Gaussian blur and the like) based on a threshold value, and performs real-time display on the virtual exhibition stand. And multi-user collaborative interaction is realized through federal learning. According to the method, reinforcement learning is adopted to optimize an event-driven threshold value, and virtual and real visual splitting is eliminated in combination with ambient light adaptive mapping. The problems of low participation degree, insufficient single-mode interaction information and multi-user cooperation of traditional exhibition are solved, interest analysis accuracy is improved through multi-mode fusion, personalized experience is enhanced through dynamic interaction, the method is suitable for multiple scenes such as museums and science and technology museums, and exhibition intellectualization, immersion and group interaction efficiency are effectively improved.

The invention discloses a BIM-based process simulation and consultation service support system and method, and relates to the technical field of three-dimensional modeling and visualization. The system comprises a BIM holographic data acquisition module, a process logic intelligent deconstruction module, a dynamic process simulation engine module, a physical field real-time monitoring module, an expert knowledge decision module and a visual scheme generation module. And multi-dimensional deviation early warning thresholds are set for different construction stages, the accuracy of conflict detection of various processes is ensured, meanwhile, environment illumination parameters collected by a sensor are linked with a BIM rendering engine in real time, the problem of light and shadow distortion in a digital twinning scene can be dynamically corrected, material texture misjudgment caused by illumination color temperature deviation is avoided, and the working efficiency of the digital twinning scene is improved. The accuracy of process conflict early warning is improved, and the construction safety risk and the resource scheduling error are reduced.

The invention relates to the technical field of LED dimming control, in particular to an LED ceiling lamp control system based on dynamic light source adjustment, which comprises a brightness sensing module, a dimming decision module, a light source regulation and control module, an anomaly detection module and a brightness optimization module. According to the invention, the operation load of the lamp is dynamically measured and calculated by combining ambient light and thermal radiation data, the collaborative perception of illumination intensity and thermal energy distribution is realized, the response sensitivity to weak brightness change is improved by comparing the brightness demand with the real-time output deviation and accurately identifying the dimming trigger condition, and the response sensitivity to weak brightness change is improved by comparing the initial brightness with the feedback difference value. The brightness of a plurality of lamps can be adjusted coordinately, the spatial light environment is kept stable and consistent, overload and temperature rise abnormity can be checked and abnormal lamps can be identified by combining current fluctuation and temperature abrupt change analysis, an intervention record and reaction duration comparison mechanism is introduced into a regulation and control instruction, the response efficiency is improved, and the efficiency is improved. And brightness priority adjustment and overall illumination balance control of the key area are realized.

The invention discloses a monitoring image processing method and system for high-precision target tracking, and belongs to the technical field of monitoring processing, and the method specifically comprises the steps: collecting polarization data of incident light in a monitoring scene, and generating a physical attribute signature of a light source; carrying out space-time clustering analysis on pixel points of which the variable quantity exceeds an environment illumination baseline in the monitoring scene to form a physical boundary of an illumination mutation region; obtaining motion trail data of the target vehicle, and generating a motion trail space area of the target vehicle; marking an overlapping region of the physical boundary of the illumination abrupt change region and the motion trail space region as a dynamic interference source influence region; if the predicted position of the target vehicle is located in the dynamic interference source influence area, calling an exposure control parameter and a gain control parameter corresponding to the physical attribute signature, calculating a focusing control parameter according to the scene depth of the predicted position, and loading the focusing control parameter to a sensor control unit; according to the method, the problem of target key frame loss caused by AE / AF delay under dynamic illumination is effectively solved.

The invention discloses a naked-eye 3D display optimization method based on real-time eyeball tracking, and particularly relates to the technical field of naked-eye 3D display, and the method comprises the steps: capturing eyeball movement data in real time through a visual angle tracking sensor, and collecting illumination information in combination with an ambient light sensor; depth perception parameters are calculated based on pupil diameter variation and frequency, and a time sequence prediction type dynamic compensation coefficient is generated in combination with eyeball movement acceleration; acquiring an initial fixation point coordinate by using an improved spherical projection mapping model, and performing compensation coefficient correction to obtain a real-time coordinate; and finally, according to the real-time coordinates, dynamically adjusting the refractive index distribution of the nanostructure layer, the rotation angle of the polarizer, the focal length of the optical lens and other optical modulation parameters. The real-time distance is calculated through the binocular parallax algorithm, the depth mapping value is generated by combining the focal length of the camera and the baseline distance, the method can adapt to the illumination change and the user view angle, and the 3D display effect is optimized.

The invention relates to the technical field of display, and particularly discloses an intelligent self-adaptive eye protection display system which sequentially comprises a content analysis module, an ambient light detection module, an eye protection parameter calculation module, a display parameter adjustment module and a user feedback module. The system identifies the screen content type and the dynamic degree in real time, synchronously detects the ambient light intensity and the color temperature, obtains the optimal combination of the blue light proportion, the brightness, the contrast ratio, the color temperature and the sharpness through a multi-target optimization model, and smoothly adjusts the display through driving; a user can score, finely adjust and mark a scene, and feedback data enters a self-learning engine to iteratively update a parameter weight so as to form a content-environment-user closed loop. The system can significantly reduce blue light harm and improve visual comfort without external hardware.

A light absorber 10 has a transmission spectrum satisfying the following requirements (I), (II), (III), (IV), and (V) at an incident angle of 0°. The light absorber 10 has a haze less than 0.20%. (I) An average transmittance TA0deg(460-600) is 75% or more. (II) A shorter cut-off wavelength λH0deg(s) is in a range of 390 nm to 450 nm. (III) A longer cut-off wavelength λH0deg(L) is in a range of 600 nm to 680 nm. (IV) An average TA0deg(300-380) is 1.2% or less. (V) An average TA0deg(750-1000) is 1.2% or less.

The invention provides a multi-scene-oriented intelligent light adaptive control method and system, and the method comprises the steps: recognizing the current behavior state of a user based on visual sensor data, predicting the behavior state of the user, and outputting a light control behavior tag; combining the behavior label with a scene type and ambient light intensity to generate a target illumination intention vector; according to the target illumination intention vector, in combination with an illumination control conflict situation, real-time lamp parameters and user space state data, calculating an illumination weight of each lamp to a user, distributing brightness and color temperature parameters, and in combination with the target dimming process duration, generating a lamp control parameter set; and converting the lamp control parameter set into a dimming instruction sequence, performing time synchronization and delay compensation, and issuing the dimming instruction sequence to each lamp for execution. According to the method, accurate mapping from behavior intention to physical illumination is realized, and the method has extremely high universality, deployability and engineering controllability.

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

The invention relates to the technical field of liquid crystal display, in particular to a liquid crystal display driving control method and system. Comprising the following steps: SS01, multi-modal sensing and state triggering: fusing a user distance, a fixation point coordinate and ambient light illumination in real time by using an integrated sensor, and triggering an eye protection mode or a self-adaptive sleep mechanism according to the user distance, the fixation point coordinate and the ambient light illumination, SS02, image partitioning and strategy generation: dividing a screen into N * M partitions, and SS03, distinguishing a dynamic region from a static region according to the brightness histogram and the motion vector of each partition, and outputting differentiated refresh rates and backlight strategies, and SS03, performing big data learning and model optimization, and collecting user behaviors. The system has the advantages that the infrared proximity sensor, the eyeball tracking sensor, the distance sensor and the ambient light sensor are integrated through the multi-mode sensing and state triggering module, multi-dimensional data such as user distance, fixation point coordinates and ambient light illuminance are fused in real time, and active intelligent sensing of the user state and the environment is achieved.

The invention relates to the technical field of camera control, and discloses a megapixel camera control method based on multifunctional fusion. The method comprises the following steps: acquiring original image data of an image sensor, and preprocessing to generate an initial brightness distribution diagram; and calculating a scene dynamic range to determine a target exposure parameter set containing exposure time, a gain coefficient and an aperture value, synchronously analyzing color temperature information, matching a preset white balance model to output a correction coefficient, and combining the two to generate a first control instruction to be sent to the image sensor. Receiving a touch screen focusing signal, and extracting a focus area coordinate to adjust a stroke parameter of a focusing motor; ambient light intensity is monitored in real time, and when the ambient light intensity is lower than a preset threshold, a flash lamp compensation module is activated and a compensation light quantity value is calculated. In the photographing mode, the output power of the flash lamp is adjusted according to the compensation light quantity value, the target exposure parameter set is recalibrated based on the focus area coordinates, and the camera complex scene adaptation and imaging quality are improved.

The invention provides a visual fatigue relieving method based on ambient light self-adaption and an AI algorithm, and relates to the technical field of visual health protection. The visual fatigue relieving method based on ambient light self-adaption and the AI algorithm comprises the following specific steps: S1, data acquisition: acquiring a user eye image sequence in real time through a high-frame-rate camera; and S2, parameter extraction: when the user uses the eye for the first time, testing the eyes by combining the adjustable light source with ambient light. Multi-dimensional features (such as eyeball movement, blinking mode, pupil function and the like) of eyes are collected in real time through a high-frame-rate camera, an individualized base line is established and a fatigue rate value is dynamically calculated in combination with data of an ambient light sensor, and conversion from passive response to active prevention is realized. Through a hierarchical intervention strategy (such as brightness adjustment, blue light control and forced rest), the visual load is remarkably reduced, the intervention efficiency is improved, and the problem of insufficient adjustment hysteresis and individual adaptability in the prior art is solved.

The invention relates to a light sensation self-adaption and white balance cooperative adjustment method and device for an LED display screen, and the method comprises the steps: collecting the illumination value of current ambient light and the spectral distribution of the ambient light, and calculating the color temperature value of the ambient light; according to the color temperature value, inquiring a pre-stored color temperature-gain parameter corresponding relation library to determine a corresponding white balance gain parameter; according to the illumination value, a backlight brightness adjustment amount is calculated through a pre-constructed logarithm compensation model; associating and binding the white balance gain parameter and the backlight brightness adjustment amount, and outputting the white balance gain parameter and the backlight brightness adjustment amount to a pulse width modulation signal generation unit and a digital-to-analog converter through a microcontroller; and outputting the white balance gain parameter to a digital-to-analog converter, outputting the backlight brightness adjustment amount to a pulse width modulation signal generation unit, generating a synchronous adjustment signal to drive an LED display unit, and carrying out cooperative adjustment of backlight brightness and white balance so as to achieve the purpose of unified regulation and control of visual comfort and color rendition authenticity.

The invention relates to the technical field of vehicle vision calibration, and discloses a DMS camera calibration method based on computer vision. The method comprises the following steps: acquiring a multi-view original image sequence in a target vehicle cockpit, and synchronously acquiring a camera mounting position, a view angle, an inclination angle and an environment illumination intensity parameter; after distortion correction is carried out on the original image sequence, edge features of a calibration reference object in each frame of image are extracted through image recognition, and an initial calibration matrix containing a mapping relation between pixel coordinates and physical coordinates is generated; constructing a three-dimensional space projection model based on the initial calibration matrix, and adjusting rotation and translation parameters of the model by using an iterative optimization algorithm to enable the error between a virtual imaging position and an actual edge feature to be minimum; and extracting an internal parameter matrix and an external parameter matrix of the optimized model, fusing the internal parameter matrix and the external parameter matrix into a final calibration parameter, and writing the final calibration parameter into a DMS camera firmware storage area. According to the method, the DMS camera calibration accuracy and environmental adaptability are improved, and stable technical support is provided for driver state monitoring.

The invention discloses a target object targeting agent monitoring method and device based on AI visual identification, belongs to the technical field of termite monitoring, and aims to solve the problems of high manual dependence degree, high misjudgment rate, low data transmission efficiency and the like in traditional target object monitoring. A slow-release targeting agent and a solar hybrid power supply system are arranged in the device, and low-power-consumption endurance is supported. According to the core scheme, vibration and infrared sensor signals are fused, and image acquisition is triggered through feature analysis; recognizing a target object through background difference, a multi-scale image and feature matching, and dynamically optimizing a detection threshold value; after video acquisition, activity intensity is calculated in combination with target tracking and gridding analysis, and transmission is optimized based on intensity and quota; light supplement is automatically adjusted according to ambient light, and image quality is ensured through pixel compensation and brightness adjustment. According to the scheme, a closed-loop system with multi-mode accurate triggering and intelligent identification is constructed, and the intelligence and efficiency of termite monitoring are improved.

The invention relates to an office intelligent control method and device based on multi-source data fusion and electronic equipment. The method comprises the steps that station use state data, environment illumination intensity data, personnel movement data and current lamp state data are acquired; based on the station use state data, the station use state is judged, and a corresponding illumination control strategy is generated; according to the illumination control strategy, the lamp brightness of the corresponding station is controlled; controlling to turn off the lamp in response to judging that no person is at the target station; calculating and outputting a target brightness value based on the environment illumination intensity data in response to the judgment that the current station is provided with the person; in the presence of a person, receiving a manual adjustment instruction sent by a user for the target brightness value, and performing adaptive optimization on the brightness calculation logic of the target brightness value; and in response to the lamp failure, controlling to lighten the lamps near the failed lamp and generating maintenance alarm information. According to the invention, the problems of high misjudgment rate, single control strategy, waste of energy consumption and poor user experience are solved.

The invention relates to the technical field of energy-saving management, in particular to a touch screen power consumption monitoring and energy-saving control method, which comprises the following steps of: based on a real-time power consumption state of a touch screen, detecting matching between brightness and ambient light intensity, acquiring brightness optimization parameters, monitoring association between refresh frequency and user behaviors, and analyzing pixel distribution; identifying an inactive area and reducing energy consumption; detecting screen resource allocation in a multi-task scene; balancing screen power consumption and equipment performance; monitoring power consumption fluctuation; according to the invention, by acquiring the matching degree of the screen brightness and the ambient light intensity, energy waste is avoided, the refresh frequency of an invalid area is reduced, the image processing load is reduced, screen pixel distribution is identified, the energy consumption output of an inactive area is reduced, screen resource allocation and energy consumption configuration are optimized in a multi-task scene, the scheduling accuracy is improved, and the user experience is improved. Performance and power consumption are balanced, screen sensitivity and stability are ensured, and efficient screen power consumption regulation and control are achieved.

The invention relates to the field of intelligent table lamps, and discloses an LED personalized eye protection lighting method based on AI learning, and the method comprises the steps: fusing the myopia degree manually input by a user, real-time ambient light intensity and desktop reflection characteristics, and generating an eye load adaptation matrix; performing cross-domain convolution recursion modeling on the eye load adaptation matrix, and constructing a user personalized visual tolerance tensor; based on the visual tolerance tensor, utilizing an adaptive threshold drift model to extract an illumination comfort trajectory, and identifying potential visual fatigue risk candidate points; mapping the potential asthenopia risk candidate points to an LED dimmable unit cluster, and performing iterative coupling optimization on brightness gradient, color temperature offset and an illumination incident angle to obtain light field adjustment solutions facing different myopia degrees; generating a non-uniform distributed control instruction among the brightness, the color temperature and the refresh frequency based on the light field adjustment solution; the method has the advantage of intelligently adjusting the light brightness and the color temperature by combining the myopia degree of the user and the ambient brightness.

The invention relates to the technical field of photovoltaic power generation systems, and discloses a liftable BIPV photovoltaic roof power system based on intelligent control, which comprises a panoramic light field sensing module, a multi-modal data fusion prediction module, an ambient light contribution analysis module, a self-adaptive angle optimization module and a partition cooperative control module. According to the invention, through omnibearing light field perception, multi-modal data fusion prediction, ambient light contribution analysis, adaptive angle optimization and partition cooperative control, intelligent optimization control of the angle of the photovoltaic roof assembly is realized, the light energy capture efficiency can be comprehensively improved, and the system has a prospective control capability and is suitable for popularization and application. The problems that in the prior art, response to rapid change illumination conditions is lagged in consideration of direct light of a single sun track, and illumination differences of different areas in a large system exist are solved.

A system for automatically adjusting the lighting parameters of a space is disclosed herein. The control module sets the target lighting parameters in the space and drive the smart lamp groups to illuminate by using the preset light recipe and to control the smart lamp groups to perform the illumination. The control module compares an ambient light detection value in the actual environment with the target value. When the ambient light detection value is not the same as the target value, the control module drives the ambient light sensor module performs a dimming procedure to the smart lamp groups. Wherein, the dimming procedure includes the step of adjusting an illuminance uniformity of the space according to the actual illuminance detected by the ambient light sensor module. After the calculation of the illuminance uniformity formula, the illuminance uniformity is adjusted to be the same as a target illuminance uniformity.

The invention discloses a self-powered cholesteric phase display screen display driving system and a control method thereof, and belongs to the technical field of display. The system comprises a low-light energy acquisition module, an energy management module, a control module and a display driving module. The control module controls the turn-off and turn-on of the voltage output function of the energy management module by outputting a sleep / wake-up signal, so that the system is charged by using ambient light during sleep, and image refreshing is quickly completed and the system enters sleep again during wake-up. By setting a balance point of wake-up time and energy consumption, it is ensured that refreshing energy consumption is lower than charging energy, so that energy self-balance and continuous work of the system in a luminous environment are achieved, and external charging is not needed. The problems that an existing cholesteric phase display needs frequent external charging during continuous work and a traditional light energy power supply scheme is low in efficiency in the low-light environment are mainly solved, self-powered continuous operation of the cholesteric phase display in the indoor and outdoor low-light environment is achieved, and use convenience is improved.

The invention belongs to the technical field of LED display, and provides an LED display screen brightness adjusting system and method, and the method comprises the steps: collecting the environment illumination intensity of an LED display screen in real time, judging whether the environment switching occurs or not according to the environment illumination intensity, triggering the brightness adjustment if the environment switching occurs, extracting a basic image frame which is being displayed by the LED display screen, calculating a brightness histogram, and outputting the brightness histogram; dividing a highlight area in the basic image frame according to the brightness histogram, judging whether local suppression is triggered or not, if not, marking the basic image frame as an adjusted image, and if local suppression is triggered, constructing an attenuation compensation iteration mechanism comprising attenuation coefficient dynamic updating and a nonlinear suppression function model, and performing local suppression on the highlight area to obtain a high-brightness image; the method comprises the following steps: acquiring a locally suppressed adjustment image, introducing a gamma parameter generated by adopting a space-time fusion prediction formula, calculating a global brightness adjustment value in combination with the adjustment image and environment illumination intensity, and carrying out global adjustment on the LED display screen.