4126 results about "Light field" patented technology

The invention discloses a glass lens surface scratch detection method and system, relates to the technical field of precision optical detection, and aims to solve the problems of scratch false detection, leak detection and poor algorithm adaptability caused by interference fringes, noise coupling and poor form adaptability in a high-reflection / complex coating process scene in the prior art. According to the scheme, an orthogonal polarization state composite light field is generated based on a multi-angle polarization light source array and a near-infrared compensation light source, and candidate regions are extracted through dynamic threshold segmentation and a direction gradient tensor matrix; gaussian pyramid multi-scale feature fusion and refraction angle consistency verification are utilized to eliminate artifact interference; constructing a direction constraint convolution kernel group to decompose scratches and background textures, and dynamically allocating computing resources in combination with a cascade network; feeding back closed-loop calibration light source wavelength and convolution kernel parameters in real time through coating parameters; according to the method, the precision and robustness of high-reflectivity surface scratch detection are remarkably improved, and meanwhile, the requirements for high-resolution image processing and real-time performance in a high-speed production line are balanced.

The invention discloses a metal surface quality detection method and system, and relates to the technical field of metal surface quality detection. The method is used for solving the problems of low microdefect detection precision, weak technological parameter relevance and closed-loop control deficiency of the high-reflection surface. The metal surface is irradiated through multi-angle coherent light field serialization, the phase offset of interference fringes is analyzed to generate three-dimensional shape data, and reflection noise interference is restrained. Defect depth gradient is extracted based on dynamic segmentation of process parameter constraint, deposition temperature and pressure deviation are quantified through deconvolution calculation, and process deviation feature distribution is constructed. Finite element simulation is utilized to generate a process-morphology mapping atlas library, cross-domain invariance features are extracted through depth constraint manifold alignment and comparative learning, and a causal correlation model of defect types and process parameters is established. And dynamically adjusting process parameters according to the weight gradient, and reflowing data to update the manifold rule. And high-precision three-dimensional defect detection, process deviation traceability and adaptive parameter optimization are realized.

The invention provides an adjustable spectrum-based liquid crystal display system and a control method thereof, relates to the technical field of display systems, and aims to overcome the limitations of poor environmental adaptability, easiness in causing visual fatigue, single user experience and the like of an existing display. The system creatively integrates a liquid crystal panel, a high-precision multi-main-color Micro-LED backlight, a pixel inner sensing array, an external multi-mode sensing module, a dynamic addressable micro-optical array, a dynamic polarization modulation layer and an optional transparent energy collection layer. The intelligent controller carries out fusion processing on the real-time biological state, environment information and application context data of the user obtained by the multi-source sensor, and carries out accurate state evaluation and future trend prediction. And determining an optimal space-time-direction-spectrum-polarized light field output characteristic and an intelligent energy management strategy through a multi-objective optimization decision engine, and driving each optical regulation and control component to execute in real time. The visual comfort and health level are remarkably improved, and the information fidelity and task performance in a complex environment are ensured.

The invention provides a distortion correction method and system for image projection, and relates to the technical field of image processing, and the method comprises the steps: generating a geometric deformation parameter matrix and a light field attenuation vector of a projection surface through a constructed bidirectional distortion detection model, carrying out the regional analysis of the geometric deformation parameter matrix, and obtaining a curvature feature, dividing a priority correction level through curvature features, and determining a nonlinear compensation factor according to the priority correction level and a light field attenuation vector; constructing a self-adaptive projection network based on the distortion sensitive features of the projection image and the nonlinear compensation factor, and performing reverse coordinate mapping on the projection image through the self-adaptive projection network to obtain an initial correction image; determining an artifact suppression weight map through the high-frequency detail threshold value and the low-frequency smooth threshold value of the initial correction image; according to the invention, geometric deformation parameter optimization and light field attenuation compensation of image projection can be realized, so that the distortion correction precision and the anti-artifact capability are 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 belongs to the technical field of automatic detection, and discloses an online laser detection and grading regulation and control system for particle size distribution of crushed raw ore. The invention aims to solve the problems of halo effect interference caused by adhesion of fine dust in a complex industrial environment and insufficient detection precision of a traditional method. The system obtains dynamic scattering light field data through the laser scanning module, identifies a halo effect region and generates a compensation coefficient by using the light field preprocessing module, and realizes accurate reconstruction of particle boundaries in combination with the edge reconstruction module. The particle size distribution analysis module extracts multi-dimensional geometric features based on the accurate boundary data, and generates a real-time particle size distribution curve. The grading strategy generation module formulates a regulation and control strategy according to deviation characteristics of the curve and a preset standard, and the dynamic regulation and control module adjusts parameters of crushing equipment in real time and optimizes particle size distribution. The method effectively overcomes the halo effect interference, improves the detection precision and the system stability, breaks through the single limitation of a traditional method, and provides comprehensive data support for a downstream process.

The invention relates to the technical field of display screens, and discloses an anti-dazzle Micro LED display screen and an anti-dazzle adjusting method and system.The method comprises the steps that multi-dimensional spectral data collection is conducted on incident light, and a multi-dimensional spectral feature matrix is obtained; performing space-time light field reconstruction of tensor decomposition and spherical harmonic function expansion operation on the multi-dimensional spectral feature matrix to obtain four-dimensional light field feature data; inputting the four-dimensional light field feature data into a deep learning prediction network for dynamic modeling to obtain light field distribution prediction data; performing anti-dazzle display parameter optimization based on the light field distribution prediction data to obtain a display parameter target value; and executing a hierarchical control strategy according to the display parameter target value, and generating a multi-parameter cooperative control signal for light transmittance adjustment, polarization state modulation and microstructure actuation, the method realizes accurate conversion from the light field characteristics to the control parameters, ensures the stability and continuity of the display effect, effectively reduces the system energy consumption, and improves the operation efficiency.

The present invention relates to a solar azimuth estimation method and system based on multi-channel feature enhancement and region-aware attention, belonging to the technical field of intelligent navigation for low-altitude economy unmanned systems. Aiming at the problem of decreased accuracy in solar azimuth estimation based on polarization images under complex cloud cover conditions, the present invention proposes a deep learning framework integrating multi-channel features and direction-aware attention. First, based on polarization light field information acquired by a division-of-focal-plane polarization camera, a three-channel composite input feature composed of a polarization intensity map, an adaptive threshold gradient map, and high-frequency residual edge information is constructed. Second, a ResNet backbone network embedded with a squeeze-and-excitation mechanism is adopted, and a direction-aware polarization attention module is introduced to achieve adaptive fusion of multi-scale features through luminance guidance, deep feature enhancement, and a gradient edge branch.

The invention provides a processing method and system for reconstructing an LDI sub-pixel image through sparse compression and application, and the method comprises the steps: calculating a low-resolution to-be-exposed image corresponding to each phase structure in advance through a computer image compression algorithm; the low-resolution to-be-exposed images obtained through calculation are loaded to the digital micro-reflector according to the time sequence, and the display moment of each pattern is matched with the rotation position of the corresponding phase structure; coupling the pattern of the digital micro-mirror and the phase encoding mask in a frequency domain through a 4-f optical system, and reconstructing a high-resolution exposure pattern at a sub-pixel level by utilizing a diffraction effect; projecting a high-resolution light field of the reconstructed high-resolution exposure pattern to the surface of the photoresist, and forming a target circuit pattern by accumulating exposure dose; and the micro-nano structure with sub-pixel precision is obtained after development. The system comprises an image compression module, a pattern matching module and a pattern forming module. According to the invention, the manufacturing cost of the laser direct imaging equipment is reduced under the condition of the same precision.

The invention discloses a display color adjustment method and system, and the method comprises the steps: collecting the spectral data of ambient light in real time through a multispectral sensor according to the environment where a display is located; according to the visual preference of the user, utilizing a visual response model to extract visual features of the user; according to the environment light field dynamic data set and the user visual preference data set, color parameters of a display are adjusted through a dynamic optimization algorithm, and optimized color parameters are generated; according to the optimized color parameters, color presentation of the display is adjusted in real time through a color management engine, and the color management engine ensures low delay and high precision of color adjustment through a streaming computing technology and a distributed architecture to generate a final display effect. According to the embodiment of the invention, the method can adapt to the change of ambient light in real time, considers the visual preference of a user, and achieves the efficient and precise color adjustment.

The invention provides an intelligent control method for a floodlight illumination system, and the method comprises the steps: obtaining an environment surface roughness coefficient, spectral reflection distribution and spatial geometric change data, determining the wall surface material absorptivity and shielding region coordinates, and obtaining environment reflection characteristics and shielding distribution data; analyzing shielding boundary sharpness and shielding angle distribution according to the spatial geometric change and the coordinates of the shielding area, calculating a luminous flux distribution curve of a local dark area, and judging whether the influence range of the dark area exceeds a preset threshold range or not; calculating the illumination coverage integrity according to the updated light field distribution and polarization reflection characteristics, determining the boundary sharpness of a light beam, and obtaining a light field uniformity parameter; and according to the light field uniformity parameter and the shielding thermal radiation effect, calculating and optimizing light field parameters.

The invention discloses a mobile phone silica gel shell appearance detection system based on an optical image sensor, and relates to the technical field of appearance defect detection and intelligent visual identification. An image acquisition module acquires a high-quality multi-channel image through multi-angle synchronous acquisition; the dynamic light field regulation and control module realizes self-adaptive regulation of a regional light source based on reflectivity perception and a gray gradient change rate; the image processing and defect identification module fuses edge features, texture changes and a deep learning model to realize pixel-level defect classification; the material identification and shielding module identifies a non-silica gel area through multi-dimensional spectral features and eliminates interference; a time sequence defect evolution analysis module models a defect evolution track; the trend prediction module is used for predicting the extension trend of potential cracks and fatigue areas; the control feedback module realizes intelligent judgment and response linked with the manufacturing system; the system can realize high-precision and high-robustness automatic defect detection and risk prediction, and is suitable for online quality monitoring of large-batch flexible products.

The invention relates to the technical field of image data processing, and discloses a fine metal powder defect detection method and system based on image recognition, and the method comprises the steps: illuminating a metal powder region through a non-polarized light source, and collecting two images in an orthogonal polarization state through imaging equipment with a linear polarizer, according to the method, the defect morphological fingerprints are constructed through the polarization information entropy, the three-dimensional structure information is converted into light field order degree change for detection, the dimension limitation of traditional two-dimensional imaging is broken through, and the detection accuracy is improved. Hidden defects such as internal pores and aggregates can be accurately identified, and meanwhile, stable detection and material defect cross discrimination under a dynamic working condition are realized in combination with motion compensation and multiband entropy ratio verification.

The invention relates to the technical field of projection display, and discloses a projection curtain light field display gain method and system used under ambient light. According to the method, environment light data, projection curtain data and original output signals of projection equipment are collected in real time, and a dynamic light field distribution model is established after fusion processing. And based on the dynamic light field distribution model, adopting an adaptive genetic algorithm to optimize a compensation weight, generating a light field compensation parameter set, performing reverse compensation processing of brightness gain, contrast and chromaticity offset on an original output signal, and generating an enhanced projection signal. The system comprises a multi-source data acquisition module, a light field feature extraction module, a dynamic compensation calculation module, a signal enhancement processing module and a closed-loop feedback control module, ensures that the projection image keeps an optimal display effect under different ambient light conditions, and remarkably improves the watching experience of audiences.

The invention provides an optical image encryption method and system based on a partially coherent non-diffracting light beam, and belongs to the technical field of optical encryption and information transmission. Encoding to-be-encrypted image information into the light field cross-spectral density function; the method specifically comprises the following steps: discretizing an image as an expansion coefficient of a power spectral density function at a light source under a pseudo-mode substrate, and constructing a cross spectral density function; a complex amplitude modulation algorithm is adopted to convert light field complex amplitude distribution into a pure phase hologram, the pure phase hologram is loaded to a spatial light modulator, a multi-mode incoherent superposition partially coherent non-diffraction light beam is generated, and the multi-mode incoherent superposition partially coherent non-diffraction light beam interferes with a reference light beam to obtain a light field image; performing coordinate transformation and frequency domain filtering on the light field image to extract a complex coherence degree function; and reconstructing and restoring the original image information in combination with a preset key and a digital inversion algorithm. According to the method, the light beams are constructed based on pseudo-mode superposition, image hidden coding, transmission and decryption are realized by utilizing the characteristics of partially coherent light and non-diffraction light beams, and the method is suitable for optical communication and security information transmission.

The invention discloses a visual combined infrared precast beam appearance defect detection method, and relates to the technical field of civil engineering structure detection and nondestructive testing, and the method comprises the following steps: establishing an illumination time sequence observation layer, collecting multi-dimensional optical parameters aiming at the surface of a precast beam, and generating a dynamic reflection fingerprint baseline; and performing coherent phase decomposition based on the dynamic reflection fingerprint baseline, separating the specular reflection signal from the material texture signal, and calibrating light spot track and intensity evolution data in the unified baseline. According to the method, an illumination time sequence observation layer is constructed to generate reflection fingerprints, coherent phase decomposition and anti-fact playback are combined, reflection interference is stripped, and crack boundaries are recovered; time coordinates are reconstructed through double-mirror-image anchor points, and crack evolution is accurately recovered; phase conjugate projection and light field traction are combined, a dynamic threshold optical fence is established, the exposure rhythm is controlled in a closed-loop mode, and precise detection of the defects of the precast beam is achieved.

The invention relates to the technical field of camera layout, in particular to a modeling camera layout method and system. The method comprises the following steps: acquiring three-dimensional geometric scanning data and dynamic object data of a monitoring space; performing light field space modeling on the monitoring space according to the three-dimensional geometric scanning data to obtain space light field distribution data; performing light tracing analysis on the spatial light field distribution data according to the dynamic object data to obtain light propagation characteristic data; performing effective coverage analysis based on a light intensity threshold value and a field angle range on the monitoring area by using the light propagation characteristic data so as to obtain area coverage characteristic data; and performing adaptive optimization calculation on the initial layout of the camera through the area coverage feature data and pre-acquired environment parameter data to obtain camera layout parameter data. By introducing the four-dimensional light field function, the propagation characteristics of the light in the space can be comprehensively described, so that the coverage analysis is more accurate.

The invention relates to the technical field of silicon waveguide and optical fiber coupling, and particularly provides an AI-based silicon waveguide-optical fiber mode field self-alignment coupling method and system, and the method comprises the steps: monitoring the strain distribution of a chip in real time through an integrated distributed fiber bragg grating array, and obtaining the light field intensity distribution of a coupling region through cooperation with a near-field optical probe array; constructing a deep space-time convolutional network, and generating a deformation compensation vector and a waveguide reconstruction parameter by an output layer; a nanofluid channel is integrated on the side wall of the waveguide, and the refractive index of liquid is adjusted through an electrowetting effect to realize dynamic broadening of a mode field; and the electrostatic driving micro-beam embedded below the waveguide adjusts the spatial pose of the waveguide according to an instruction of an output layer of the depth space-time convolutional network. The system comprises a light field intensity acquisition module, a convolutional network construction module and a spatial pose adjustment module. According to the method, real-time analysis and prediction are performed, so that system parameters are actively adjusted, and alignment precision and stability are improved.

The invention discloses a semiconductor mechanical arm autonomous navigation and positioning method based on AI vision, and relates to the technical field of mechanical arms, and the method comprises the following specific steps: visual perception and multi-modal information fusion: collecting multi-modal data through configured industrial, depth, light field and polarized light cameras, pre-processing the multi-modal data, and carrying out multi-modal information fusion; realizing information fusion by using a deep learning network containing a feature extraction layer and a fusion layer and an attention mechanism, and outputting a unified visual description; according to the method, a deep learning target detection model is utilized, an attention mechanism is introduced to enhance the attention and extraction capability of small target features, the recognition result is optimized in combination with surface feature information recognized by polarized light imaging, the category and position of a target object can be accurately determined, meanwhile, a mechanical arm motion error model is established, and the recognition accuracy is improved. And the fused visual positioning information is fused with sensor data such as a mechanical arm joint encoder and a gyroscope by utilizing a sensor fusion technology, and a positioning result is optimized and compensated.

The invention provides an intelligent pipe surface quality detection method and system based on machine vision, relates to the technical field of industrial automatic detection and machine vision, and aims to establish a pipe surface feature library and mark shape abnormal features. The method comprises the following steps: collecting an image of a pipe in a bright and dark composite light field, extracting gray and texture features after polarization filtering processing, reconstructing a three-dimensional point cloud covering a mortar layer and a concrete layer by matching a principal component analysis dimensionality reduction fusion feature set with a feature library, and converting the point cloud into a two-dimensional expansion graph through cylindrical projection; a mortar abnormal area and a concrete abnormal area are segmented, the hole volume is calculated through point cloud residual errors in the mortar area, and internal hollowing is detected in combination with acoustic vibration excitation and thermal response; the concrete area locates defects based on point cloud features; according to the sequence of the concrete covering process before the mortar covering process, a correlation model is constructed to match and coincide the defect sites, and the detection result is output, so that the detection automation degree and accuracy can be improved.

The invention provides a precision metal part surface defect imaging method and system in a complex light field interference environment. Acquiring an original multispectral image sequence of the surface of the metal part; generating a standardized image set based on the original multispectral image sequence; performing background separation on a single-frame image in the standardized image set through an adaptive kernel function, and extracting a low-frequency component of the image as a guided smooth image; performing pixel-level differential operation on the guided smooth image and a single-frame image of the corresponding standardized image set to generate a high-frequency defect feature map containing defect edge information; carrying out probability density function mapping on gray level distribution of the feature map based on a normal distribution model to generate a defect feature distribution map with enhanced gradient features; performing multi-scale feature fusion on the defect feature distribution map and the original multi-spectral image to construct a defect enhancement image set; the imaging visibility and the detection precision of tiny defects on the surface of the metal part are improved under the complex illumination condition.

The invention relates to a light spot uniformity optimization method and system for a high-precision VCSEL device, and the method comprises the following steps: carrying out the light field collection of a light-emitting surface of the VCSEL device, obtaining the intensity distribution of original light spots, analyzing the non-uniformity of each light-emitting unit, and extracting the non-uniformity characteristics of the light spots. And carrying out deviation cause analysis based on the characteristics, and identifying device structure deviation parameters. According to the method, an etching process is optimized, a corrected oxidized aperture configuration scheme is obtained, near-field light field simulation is carried out by adopting a finite difference time domain method, and optimized light field distribution is verified and predicted. And finally, adaptive compensation design is carried out on the Bragg reflector structure based on a prediction result, light field regulation and control are realized, target light spot uniformity distribution is finally obtained, and the problem that systematic analysis and feedback control on non-uniformity causes of a light emitting unit layer in a device are lacked in the prior art is solved. And local bright spots or dark areas are caused.

The invention discloses an impurity sorting and removing system based on machine vision, and the system comprises a data collection and preprocessing layer which is responsible for obtaining multi-dimensional physical characteristics of tea leaves and impurities, and constructing three-dimensional scene representation; the feature analysis and decision-making layer is used for extracting light field fusion features by utilizing a ResNeSt-50 backbone network, directly outputting a preliminary classification confidence coefficient through a full connection layer, forming a first layer of decision-making candidates, simulating branches by combining rigid body dynamics to predict a blade movement track, performing Bayesian correction on the preliminary classification confidence coefficient after a shielding probability graph is sampled and calculated through Monte Carlo Dropout, and forming a second layer of decision-making candidates; meanwhile, a Cook-Torrent BRDF model is integrated to carry out material reflection correction, a feature map after material correction is output, and a correction value is converted into decision threshold offset; and the knowledge storage and update layer is used for constructing a bimodal memory pool composed of a gradient direction matrix and an LRU elastic cache, and generating a pseudo sample supplement long-tail category in combination with the four-layer full-connection pulse neural network.

The invention discloses a multi-dimensional holographic image real-time rendering method and system based on dynamic light field modulation, and relates to the technical field of holographic display, the method is applied to terminal equipment and a server, the terminal equipment determines a space coordinate range based on quantum dot super-structure surface characteristics by obtaining related parameters of a target holographic scene, and the real-time rendering of a holographic image is realized. A quantum dot excitation sequence is generated to regulate and control the micro-nano structure of the super-structure surface, a joint coding model is constructed, a target light field modulation instruction set is generated through optimization, corresponding multi-dimensional light field data is requested from a server, and a holographic scene is generated through processing, fusion and rendering; the server receives the request, calls original holographic data, constructs a coding model and a compression model, and sends multi-dimensional light field data subjected to entropy compression to the terminal through a multi-channel transmission protocol; according to the method, efficient real-time rendering of the multi-dimensional holographic image is achieved, the rendering efficiency and quality are improved, and the method is suitable for scenes with high requirements for real-time performance of the holographic image.

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 discloses a real-time fatigue monitoring system based on an EEG signal, and relates to the technical field of neural regulation and control, and the system comprises a chaos reconstruction module which collects an original EEG signal, carries out the phase-space reconstruction of the original EEG signal through a chaos attractor processor, generates a chaos trajectory tensor, and carries out the phase-space reconstruction of the original EEG signal when the Lyapunov index of the chaos trajectory tensor exceeds a preset index threshold value, outputting a low-speed frequency band oscillation component and a high-speed frequency band oscillation component; and the closed-loop termination module is used for terminating the physical light field projection when the continuous detection periods of the updated alertness drop probability value, cognitive overload probability value and physiological fatigue probability value are all lower than a preset safety threshold value. Through multi-scale recursion phase space reconstruction, an original EEG signal is mapped to a three-dimensional chaotic trajectory tensor space, and dynamic frequency band decoupling is triggered by using a Lyapunov exponent threshold.

The invention discloses a naked-eye 3D display system based on a light field reconstruction algorithm, particularly relates to the technical field of naked-eye 3D, and comprises a controlled scattering medium light field acquisition environment, scattering feature enhanced light field data analysis, a hierarchical depth optimization engine and dynamic wavefront modulation display control. According to the invention, through the controlled scattering medium environment design, a scattering signal which is regarded as interference in the traditional technology is converted into a depth characteristic carrier, the data acquisition quality in a complex optical environment is obviously improved, richer and more reliable basic data are provided for light field reconstruction, and the data acquisition efficiency is improved. An innovative hierarchical deep optimization engine is combined with a multi-scale confidence evaluation and discontinuous region processing method, so that the problem of edge blur in a shielding boundary and a geometric structure complex scene is effectively solved, and the geometric consistency and detail fidelity of a reconstructed light field are greatly improved.

The invention discloses a slant path atmospheric turbulence phase screen generation and light field transmission simulation method. Belongs to the technical field of satellite-ground laser communication. The method comprises the following steps: firstly, establishing a three-layer height spectrum model in a slant-range atmospheric turbulence environment, then generating an initial field suitable for vacuum and turbulence environments by using an angular spectrum method, and generating n corresponding random dynamic phase screens according to atmospheric turbulence characteristics of different heights on a slant-range path and distribution characteristics of atmospheric wind speed. Superposing the initial field and the first phase screen, performing two-dimensional Fourier transform, and performing inverse Fourier transform on the transform field by using an angular spectrum method to obtain field distribution in front of the next phase screen; and repeating the process to pass through n phase screens in sequence, and finally obtaining the output field distribution of the uplink and the downlink. The method can effectively simulate the effects of refractive index fluctuation, wavefront distortion, light intensity flicker and the like caused by oblique-range atmospheric turbulence, and provides important theoretical support and application value for researching oblique-range laser transmission characteristics.

The invention relates to the technical field of image processing, and discloses a surgical minimally invasive surgery data processing method and system based on an AR technology. The method comprises the following steps: performing three-dimensional reconstruction and lesion segmentation on medical image data, and extracting feature points; performing position acquisition and space mapping on the surgical instrument by using the feature point data; reconstructing a light field according to the feature points and the position data and generating an augmented reality scene; performing trajectory analysis and path planning based on augmented reality; performing real-time monitoring and risk early warning on the operation path; and finally, extracting an operation rule and establishing a knowledge mapping relation. According to the method, association analysis and fusion processing of multi-source heterogeneous data in the operation process are achieved, a complete technical link from data collection to knowledge extraction is established, and the operation safety and the intelligent level are improved.

The present invention discloses an in-situ detection device and method for the surface shape of an optical-mechanical component, which belongs to the field of optical precision detection technology, and aims to solve the problem in the prior art that there is a lack of in-situ monitoring and detection of surface shape distortion during the adjustment process of an optical-mechanical component. The laser light generated by the laser in the device is incident on the optical-mechanical component to be measured after passing through a beam isolator, a beam splitter prism, and a collimator A in sequence, and is reflected. The reflected light of the optical-mechanical component to be measured is incident on the beam splitter prism after passing through the collimator A and is reflected. The reflected light of the beam splitter prism is incident on a CCD camera after passing through a perforated light screen, a collimator B, and a phase plate. The CCD camera is connected to a computer system, and the light spot diagram recorded by the CCD camera will be input into the computer system for in-situ detection of the surface shape. The method modulates the reflected light of the sample to be measured by a phase plate, and uses a phase reconstruction algorithm based on light field diffraction iteration to realize sample surface shape reconstruction. It has the advantages of high measurement accuracy, no need for a reference plane, and strong vibration resistance.