5639 results about "Light intensity" patented technology

A non-invasive physiological sensor system implemented as a smart watch or other wearable device includes an emitter for emitting light and a detector for collecting light after the light interacts with a tissue of a wearer. The system can measure light intensity at one or more radial distances to estimate attenuation parameter values that can be used to correct physiological parameter bias across subjects. In addition or alternatively, the system can determine whether a detector is positioned sufficiently proximate to an obstructing tissue (for example, an artery or vein) so as to cause inaccurate measurements by the detector.

The invention relates to a hydraulic engineering concrete crack intelligent identification and quantitative analysis method and system based on machine vision. The method comprises the following steps: firstly, acquiring an original image sequence of the surface of a hydraulic engineering concrete structure, classifying according to illumination intensity, shooting angle and shooting distance, extracting crack edge features through a convolutional neural network, and fusing to obtain a crack feature set; correcting illumination through adaptive histogram equalization, correcting angles and distances through geometric transformation, and combining edge detection and scale invariant feature transformation to obtain standardized geometric parameters including crack length, maximum width and the like; if the parameter exceeds the engineering safety standard threshold value, tracking a crack track through an optical flow method to calculate increment, and inputting a neural network to output a damage trend; and finally, generating a three-color risk distribution diagram by using a finite element based on the trend, extracting high-risk data to calculate a real-time evaluation value, and dynamically adjusting the monitoring frequency to generate an optimization strategy. By adopting the method, the reliability and economy of engineering safety monitoring can be remarkably improved.

The invention relates to the technical field of three-dimensional imaging, in particular to a four-eye structured light stereoscopic vision imaging method, which comprises the following steps of: arranging four cameras and synchronously acquiring multi-view image data with structured light stripes; carrying out image preprocessing and stripe code identification on the obtained four-view-angle structured light image data, and extracting structured light stripe center line positions and corresponding space projection information under each view angle; generating three-dimensional point cloud data of the high-precision target sample by using parallax calculation and a three-dimensional reconstruction algorithm, and completing spatial registration and filtering optimization of point cloud; fusing the point cloud and the light intensity data by combining the reflection intensity information of the multi-view structured light stripes to generate a composite data set containing space and spectral information; and constructing a dense parallax field and executing three-dimensional consistency verification, and generating a high-fidelity three-dimensional reconstruction model with a complete topological relation and sparse shielding compensation capability. According to the invention, the problems of insufficient view angle coverage, shielding area information loss, difficult edge structure matching and the like of traditional stereoscopic vision imaging can be solved.

The invention discloses a machine learning-based weld defect intelligent identification system, relates to the technical field of weld defect intelligent identification, solves the technical problems of multi-modal data fusion precision and robustness optimization and defect shielding or overlapping feature deficiency, and provides a machine learning-based weld defect intelligent identification method based on PSNR dynamic parameter adjustment and gradient weight optimization. The limitation of existing fixed parameter denoising is solved, the edge feature retention rate of cracks, air holes and other defects is improved, the omission ratio is reduced, improved DeepLabv3 + segmentation semantic masks are introduced and mapped to point cloud voxels, geometric + semantic double-attribute enhanced point clouds are formed, the defect area positioning accuracy is improved, and through a cross-modal attention module, the defect area positioning accuracy is improved. Weights are dynamically distributed according to illumination intensity and workpiece materials, feature waste caused by fixed weights is avoided, depth mutation and a shielding area with semantic defects are positioned by utilizing depth information of enhanced point cloud, real overlapping and projection overlapping can be effectively distinguished by combining an improved Poisson fusion algorithm, and the overlapping defect recognition accuracy is improved.

The invention relates to a multichannel intelligent control method and system for UV LED light, and the method comprises the following steps: carrying out the spectrum scanning of a light irradiation region of a UV LED light source array, and obtaining a spectrum intensity distribution diagram; based on the spectral intensity distribution diagram, light wavelength segmentation division is carried out on a UV LED light source array, and a plurality of wavelength subintervals are obtained; performing dynamic power adjustment on the UV LED light source array according to the plurality of wavelength subintervals to obtain an optimal power configuration scheme; according to the optimal power configuration scheme, performing synchronous control on each channel of the UV LED light source array to obtain a control signal sequence of multi-channel cooperative work; and on the basis of the control signal sequence, real-time output of the UV LED light source array is adjusted, stable multi-channel UV LED light output is obtained, and the technical problems that due to the fact that spectrum output of the UV LED light source array has non-uniformity and temperature sensitivity, light intensity distribution is not uniform and wavelength drifts possibly occur under different working conditions are solved.

The invention discloses an optical imaging and coding hole technology fused optical imaging system and method, and aims to integrate scattered polarization components in a reflected light signal into coding light field data with clear layers by constructing a polarization coding modulation system, so as to highlight a coupling relationship among optical elements. A refocusing sequence and a focal plane chromatography technology are adopted, spatial geometric information and light intensity distribution characteristics of different depth layers are fully excavated, and a three-dimensional distribution rule of surface topography is disclosed; wavefront correction and deformable mirror control technologies are introduced, imaging parameters of an optical system are adjusted in a self-adaptive mode, and the application range of measurement precision is expanded; light intensity modulation analysis and phase unwrapping window processing are combined, the change trend of the surface curvature is depicted, and key feature points of morphology measurement are grasped; finally, multi-dimensional and multi-level optical measurement information is fused, three-dimensional measurement output with rich content and reliable precision is formed, and comprehensive and high-quality measurement technology resources can be provided for application scenes such as precision optical detection and surface quality evaluation.

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 provides a plate edge sealing quality detection method and system based on machine vision, and the method comprises the steps: obtaining image data streams continuously collected in a plate edge sealing processing process, carrying out the light intensity change feature extraction of the image data streams, and obtaining a time sequence light variable feature matrix and a space light variable gradient map of an edge sealing region in an edge sealing image frame sequence; carrying out relevance enhancement on the time sequence optical variation characteristic matrix and the spatial optical variation gradient map through a preset characteristic enhancement model, and generating an edge sealing quality characteristic map with a space-time constraint relation; performing defect mode identification based on the edge sealing quality characteristic spectrum to obtain defect types existing in the edge sealing area of the plate and position distribution characteristics of the defects in the edge sealing image frame sequence; and generating a quality optimization instruction containing a parameter adjustment instruction according to the defect type and the position distribution characteristic, and sending the quality optimization instruction to the plate edge sealing control equipment. According to the invention, the overall precision and stability of plate edge sealing quality detection can be improved.

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 discloses a laser channel atmospheric turbulence fading real-time compensation device and method based on a galvanometer system, and the method comprises the steps: enabling an incident light beam to irradiate a transparent PCB integrated with a photodiode array after the incident light beam is focused through a convex lens, obtaining the light intensity distribution of a current light spot through the photodiode array, and transmitting the light intensity distribution to a signal processing unit; the signal processing unit coarsely adjusts the deviation direction of the light spots according to the received light intensity distribution data, and aligns the part with the strongest light intensity in the light spots to the end face of the optical fiber; and based on the roughly adjusted light spot deviation direction, the signal processing unit dynamically adjusts the deflection angle of the galvanometer by using a gradient descent method according to the power measurement value of the receiving coupling module, so that the fine adjustment of the light spot deviation direction is realized, and the receiving coupling power is maximized. The objective of receiving optical power maximization is achieved, optical design, electronic control and algorithm optimization are combined, and atmospheric turbulence compensation with high cost performance is achieved.

The invention discloses a method for clearly imaging a mask under an optical objective, and relates to the technical field of optical detection and image processing, and the method comprises the following steps: S1, constructing a light intensity distribution model based on the boundary condition of the field of view of the optical objective in combination with the reflection characteristic and incident angle change rule of a metal edge material, and determining the coverage range of metal edge reflection crosstalk, generating a mask boundary interference prediction map; s2, according to the mask boundary interference prediction map, performing region division on the micro-reflectivity image, extracting brightness gradient characteristics of reflectivity lifting in an interference region, and generating a brightness gradient parameter set required by image filtering; the method is based on light intensity modeling, fusion direction filtering, pixel stripping, gradient reconstruction and credibility weighted fusion, realizes closed-loop control from interference prediction to pixel restoration, has high resolution and adaptivity, can accurately strip edge reflection artifacts and restore a real image structure, remarkably reduces misjudgment and rework rate, and is suitable for large-scale popularization and application. And the mask yield and the stability of the detection system are improved.

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 photovoltaic panel self-adaptive cleaning system and method based on sand and dust optical thickness monitoring. The photovoltaic panel self-adaptive cleaning system comprises a sand and dust optical thickness monitoring module, a data processing and control module, a cleaning execution module, a power supply module and a remote monitoring module. The sand and dust optical thickness monitoring module is used for monitoring the sand and dust optical thickness AOD of the environment where the photovoltaic panel is located in real time, calculating the AOD by measuring the light intensity attenuation of a specific wavelength, and correcting the atmospheric Rayleigh scattering optical thickness and the gas absorption optical thickness at the same time; the data processing and control module is in communication connection with the sand and dust optical thickness monitoring module and used for receiving the AOD data and comparing the AOD data with a preset dust retention threshold value, and when the AOD value is larger than or equal to the threshold value, a cleaning instruction is generated; and the cleaning execution module is used for receiving the cleaning instruction and executing cleaning operation. Intelligent and self-adaptive control of photovoltaic panel accumulated dust cleaning is achieved, the cleaning opportunity can be adjusted in real time according to the actual sand and dust optical thickness, and the cleaning pertinence and effectiveness are improved.

The invention relates to the technical field of vehicle-mounted display, and discloses a vehicle-mounted HUD environment illumination adaptive brightness adjusting system, which comprises an illumination acquisition module, a parameter analysis module, a model construction module, a brightness calculation module, an error evaluation module, a calibration correction module, a threshold setting module, a result output module, a feedback optimization module, a system regulation module and the like. The illumination acquisition module analyzes the illumination parameter stability and interference difference and generates an illumination perception state value; the parameter analysis module screens an optimal brightness and light intensity combination; the model construction module is used for training samples to establish a brightness and light intensity relation model; the brightness calculation module generates a brightness threshold by combining real-time illumination data mapping; the error evaluation and calibration correction module optimizes a calculation rule; and the feedback optimization module operates feedback adjustment parameters to finally generate an environment illumination adaptive brightness adjustment scheme. The system realizes accurate and dynamic adjustment of the brightness of the vehicle-mounted HUD, effectively adapts to the environment illumination change, improves the display effect and the driving safety, and has the characteristics of self-learning and self-optimization.

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 discloses a high geological disaster chain risk quantitative assessment method adapted to a high-cold and high-altitude environment, and relates to the technical field of geological disaster monitoring and prevention and control, and the method comprises the following steps: S100, building an irradiation and reflection combined observation layer, collecting the dynamic intensity of direct light and reflected light, generating an exposure time sequence fingerprint baseline, and obtaining an exposure time sequence fingerprint baseline; and determining a critical threshold value of the direct light intensity according to the base line. The method comprises the following steps: constructing an irradiation and reflection combined observation layer to extract light intensity characteristics, and generating an exposure time sequence fingerprint baseline; a trigger point boundary is extracted by adopting coherent phase decomposition and anti-fact playback, and a continuous track is reconstructed; the overexposure risk is predicted based on the time-frequency score, and spectrum gating and polarization rotation are linked to regulate and control the exposure rhythm; and reverse phase traction and phase conjugate intervention are implemented in a steady-state window, so that boundary information is maintained and the risk identification precision is improved.

The technical scheme of the invention discloses a photovoltaic power generation and greenhouse agriculture integrated system. According to the photovoltaic agricultural integrated technology disclosed by the invention, photovoltaic power generation and greenhouse planting are innovatively combined, and a solar panel with adjustable light transmittance of 30%-90% is mounted at the top of an agricultural facility, so that sunlight is utilized for power generation, and illumination required by crop growth is reserved. The system disclosed by the invention is provided with an intelligent sensor and an AI algorithm, environment data is monitored in real time, the angle, light supplementing intensity, temperature and humidity of the photovoltaic panel are dynamically adjusted, and different crop requirements (such as low illumination of leaf vegetables and medium and strong illumination of fruits and vegetables) are accurately matched. Residual electricity is stored or connected to a grid, photovoltaic waste heat is recycled in winter for heat preservation, sun shading and cooling are conducted in summer, and efficient circulation of energy is achieved.

A video generation framework that is controllable, unsupervised and based on events (CUBE) includes an event camera, which captures changes in light intensity at each pixel of a scene asynchronously and generates event camera data. A text-to-image diffusion model that is conditioned on textual descriptions integrates the event camera data to control video synthesis. Further, an edge extraction module translates event data into a format usable by the text-to-image diffusion model, whereby the diffusion model synthesizes detailed and contextually accurate videos based on textual prompts. Further, an improved system (CUBE Plus) includes a content frame identification module which selectively identifies and uses only the most information-rich event segments of the event camera data to drive cross-frame attention, and an event driven attention mechanism that allows the framework to focus on event-dense moments.

The invention relates to an unmanned aerial vehicle imaging control method and device based on AI and flight control parameter fusion, and the method comprises the steps: carrying out the scene feature extraction of historical imaging data, obtaining image features under multiple scales, constructing an AI scene adaptation strategy according to the image features, solving an illumination intensity prediction model, and obtaining an optimal imaging parameter set of a corresponding camera; and acquiring original image data shot by the camera under the optimal imaging parameter set, optimizing the original image data based on an AI scene adaptation strategy, predicting the flight state of the unmanned aerial vehicle based on the flight control parameter to generate an imaging preset parameter, and using the imaging preset parameter to control shooting of the unmanned aerial vehicle. The AI scene adaptation strategy is constructed by using AI in combination with historical imaging data, the problem of poor scene adaptability is solved, in addition, the illumination intensity prediction model is constructed by combining flight control parameters, the illumination intensity prediction model is solved, the optimal imaging parameter set of the corresponding camera is obtained, and the defect of weak illumination adaptability is overcome.

The invention relates to the technical field of building intelligent control and energy saving, and discloses a building equipment intelligent control optimization management system based on a green low-carbon building. The system comprises five subsystems, wherein an environmental parameter sensing subsystem is used for acquiring temperature and humidity gradients, illumination intensity distribution and personnel activity thermodynamic diagram data inside and outside a building through a distributed sensing network to form a multi-dimensional environmental state vector; the equipment operation state acquisition subsystem acquires an operation power curve, an energy efficiency conversion rate curve and an equipment health degree index of heating ventilation air conditioning, illumination and renewable energy equipment in real time; the dynamic load prediction subsystem establishes an energy consumption load space-time distribution prediction model according to historical data time sequence relevance; the control strategy generation subsystem is used for generating an optimized instruction set containing an equipment start-stop time sequence, a power regulation gradient and an energy distribution weight in combination with the current environment vector and a predicted load; the execution terminal adapts the subsystem to convert the instruction into a device compatible signal and calibrate a response delay.

The invention discloses a polarization spectrum modulation type multispectral stereo imaging method which solves the problem that in the prior art, an existing polarization spectrum imaging scheme does not achieve three-dimensional reconstruction of a target and achieves the purpose that the three-dimensional reconstruction of the target is not achieved under the condition that active illumination or special marks are not needed. Synchronous high-precision reconstruction of physical attributes and three-dimensional geometry of the surface of the target is realized; the method comprises the following steps: uniformly modulating polarization information and spectral information of incident light of a target through a three-way optical filter and a polaroid to obtain modulated incident light information; performing aliasing acquisition of a plurality of polarization spectrum components on the modulated incident light information through a multi-color detector combination to obtain aliasing light intensity; performing linear solution on the aliasing light intensity to obtain each polarization spectrum component vector, calculating the polarization degree and the polarization angle of each channel, and further deriving a surface zenith angle and an azimuth angle; reconstructing the three-dimensional morphology of each spectrum channel through normal gradient field frequency domain integration; and finally, fusing the multi-spectral three-dimensional data to obtain a multi-spectral three-dimensional imaging result.

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.

The invention discloses a calibration device with a spectrum self-calibration function and a high-resolution spectrum calibration method thereof. The device comprises a narrow-band light source, a broadband light source, an optical fiber isolator, a coupler, an interference system, a multi-way switch, an FP (Fabry-Perot) cavity, a collimator, an orthogonal dispersion system and a computer, wherein the orthogonal dispersion system consists of a cylindrical lens, a reflector, a virtual phase array, a grating, a focusing lens and an industrial camera; according to the device, different light source paths are gated, FP cavity modulation and orthogonal dispersion system light splitting are utilized, and an industrial camera is combined to receive light signals. According to the method, the mapping relation between pixels and wavelengths can be established, the two-dimensional spectrum is compressed into the one-dimensional calibration spectrum through light intensity modulation and normalization processing, the calibration process of the orthogonal dispersion system is simplified, and the measurement precision is improved; and system drift can be compensated in real time through self-checking calibration, and the reliability of a measurement result is ensured, so that accurate calibration and measurement of a high-resolution spectrum can be realized.

The invention provides an imaging method and system based on a polarization imaging lens and visual collaborative optimization, and a medium, and the method comprises the steps: integrating a four-way polarization filter array on the surface of an imaging sensor, and synchronously collecting a four-channel polarized light intensity image through single-frame exposure based on the imaging sensor; obtaining a three-channel RGB image, and inputting the four-channel polarized light intensity image and the three-channel RGB image into a polarization-RGB fusion neural network; polarization features and RGB features are extracted, heterogeneous information coupling optimization is carried out, and fusion features are obtained; constructing a polarization-color joint decoding network, carrying out polarization and RGB information collaborative decoding on the fusion features, training a polarization decoding process and a material classification task together based on an end-to-end joint optimization strategy, and outputting a material classification result; high-efficiency acquisition of original polarization information on a hardware level is guaranteed through the polarization filtering array; and an end-to-end joint training strategy is adopted to realize optimal decoupling and fusion of perception information.

The invention relates to the technical field of monitoring light supplement adjustment, and discloses a monitoring light supplement automatic adjustment system based on ambient light detection. An ambient light dynamic sensing module of the system captures visible light and infrared spectrum components of a monitoring area in real time through a multispectral sensor array, constructs a light intensity distribution model in combination with illumination intensity historical data, and outputs a theoretical illumination distribution diagram; the spectral feature analysis module compares the theoretical distribution map with the actually measured light field data in a multi-dimensional manner, performs spectral deviation detection and generates a spectral difference feature tensor; the light supplement demand mapping module inputs the tensor into a space illumination analysis network, and generates a light supplement coverage demand thermodynamic diagram and calibrates the boundary of a low-illumination area in combination with a field angle of monitoring equipment and position coordinates of a light supplement lamp; and the self-adaptive light supplement strategy execution module starts a multi-band mixed light supplement mode for a high-demand area according to the thermodynamic diagram, and performs phase cooperative control on adjacent light supplement lamp groups. The system realizes dynamic and accurate adjustment of light supplement, and can effectively adapt to complex ambient light changes.

The invention provides a light intensity measurement method and device based on single-photon detection and electronic equipment, and relates to the technical field of single-photon detection and laser radar imaging, and the method comprises the steps: collecting the arrival time information of photons in a plurality of single-photon detection events for each detection position; extracting a time sequence characteristic quantity related to the light intensity estimation based on the arrival time information; constructing a model input parameter for estimating the target light intensity based on the time sequence characteristic quantity; inputting the model input parameters into a light intensity estimation model, and predicting a light intensity estimation value of the target light intensity; and generating a corresponding light intensity distribution image according to the light intensity estimation value. According to the method, high-precision light intensity estimation can be realized only by a few photons, the requirements on the repeated detection times and the signal-to-background ratio are greatly reduced, and the imaging robustness is enhanced.

The invention discloses a multi-mode nonlinear optical microscopic imaging device and system, and the device achieves the two-photon and three-photon excitation imaging of a sample through an integrated light source module, a dispersion compensation module, a scanning light path module, a fluorescence obtaining module, a synchronous control module and a signal processing module. Fluorescence intensity imaging and fluorescence lifetime imaging can be supported at the same time; wherein the scanning light path module is driven by the random mask to realize sparse scanning, so that scanning point locations are effectively reduced, and the exciting light dosage is reduced; the synchronous control module performs time window screening and processing on the fluorescence signal based on the pulse synchronous signal and the position code, so that the signal acquisition efficiency is improved; the signal processing module adopts an FPGA (Field Programmable Gate Array) to carry out real-time image reconstruction and life calculation, so that the imaging speed and quality are ensured; and the master control PC can also perform high-fidelity reconstruction on the sparse sampling image through a deep learning model, so that high-speed, low-light-dose and high-resolution nonlinear fluorescence intensity and life imaging is realized.

The invention discloses an emergency rescue real-time human body detection method and device based on time sequence motion feature enhancement, and the method comprises the steps: obtaining visible light and infrared image sequences of a rescue region and environment parameters (including smoke concentration and illumination intensity) in real time, and carrying out the spatial registration preprocessing; respectively carrying out frame difference processing on the two types of image sequences, generating a binary motion mask, calculating an optical flow amplitude, and carrying out adaptive fusion according to smoke concentration to obtain a multi-scale motion energy field; human body micro-motion frequency band energy is extracted through time-frequency transformation, a frequency domain dynamic attention mask is generated, and a saliency motion target area is extracted in combination with a multi-scale motion energy field; constructing a double-branch neural network, extracting time sequence motion features and multi-modal appearance features, dynamically distributing weights and fusing the weights, and outputting a human body bounding box and detection confidence; and calculating environment complexity according to the environment parameters, determining a dynamic confidence threshold, verifying a detection result by combining the average temperature of the human body bounding box region, and generating alarm information if a condition is met. The method aims at solving the problems that a traditional method is high in omission ratio and unstable in recognition in a complex environment.

The invention relates to the technical field of intelligent control, and discloses an ultra-low power consumption miniature LED visible light intensity self-adaptive regulation and control method and system, and the method comprises the steps: obtaining an analog light intensity signal, and carrying out the smoothing processing of the analog light intensity signal, and obtaining an environment light intensity value; calculating a light intensity change rate, and if the light intensity change rate exceeds a dynamic threshold value, marking an environment state and outputting a light intensity difference value; generating a preliminary adjustment instruction according to the state matching control parameter and the difference value quantization mapping, and calculating target light intensity in combination with the basic brightness; after executing the instruction, calculating actual and target deviation, and iteratively correcting to obtain a light intensity control signal; if the power consumption exceeds the limit, optimizing the signal amplitude; the input driving circuit analyzes the synthesized pulse current, excites pixels to emit light and gathers to obtain adjustment data; and if the visual contrast is lower than a threshold value, the change rate is adjusted again to realize closed-loop refining, and the light intensity adjustment accuracy is improved. The method can improve the real-time sensing capability of ambient light.

The invention discloses a mixed gas absorption spectrum analysis method and system based on variational mode decomposition, specific laser is injected into an optical resonant cavity unit, and a detector unit continuously monitors the light intensity change and records a light intensity attenuation signal; pre-processing the recorded light intensity attenuation signal; carrying out VMD decomposition on the preprocessed ring-down signal to obtain a plurality of IMF components, respectively introducing CO2 and CO gases with known concentrations into the optical resonance unit, and recording spectral data of each single gas component; calculating the similarity and contribution degree of each IMF component, and setting a weight combination to form a joint score; the gas with the highest joint score is selected, the score is compared with an adaptive threshold value, and when the score is higher than the adaptive threshold value, the IMF component is marked as the characteristic component of the corresponding gas; and finally, gathering and outputting the marked IMF components according to gas types to obtain characteristic signals of the gases, thereby realizing multi-component gas separation in the mixed gas absorption spectrum.