587 results about "Single pixel" patented technology

The invention discloses a special environment laser radar system and method based on polarization modulation and laser coding. The laser radar system comprises a polarization modulation laser emitting unit, a multi-channel receiving unit and a compressed sensing reconstruction unit. The polarization modulation laser emission unit comprises a laser, a beam expanding module, a spatial light modulator, a micro galvanometer array, a spatial filter and a first focusing lens which are arranged in sequence; the multi-channel receiving unit comprises a second focusing lens, a polarization beam splitter and a single-pixel detector array which are arranged in sequence; and the compressed sensing reconstruction unit comprises a compressed sensing processing module, an image reconstruction module and a loop adaptive control module which are arranged in sequence. The anti-interference capability in a complex environment is enhanced through polarization modulation, the detection resolution and the signal-to-noise ratio are improved in combination with laser coding, the imaging quality and stability of the laser radar in a special environment are greatly improved, and the method can be widely applied to the fields of military reconnaissance, disaster rescue, unmanned driving and the like.

The invention relates to the technical field of cholesteric liquid crystal electronic paper display, and discloses a cholesteric liquid crystal electronic paper display panel and a driving method thereof, and the cholesteric liquid crystal electronic paper display panel comprises an upper substrate, a lower substrate, a grid scanning line and a signal line, the electrode strip blocks continuously extend in the direction of a grid scanning line, each electrode strip block corresponds to one row of pixels, a single pixel corresponds to one pixel electrode, the electrode strip block corresponding to each row of pixels is conducted with the ITO electrode in the corresponding row through a conductive spacer, the ITO electrode is located on the periphery of a display area of the display panel, and in the direction of a signal line, the ITO electrode is connected with the electrode strip block in the corresponding row. The size of a single pixel is larger than the width L of each electrode strip block and larger than or equal to the width L'of a pixel electrode, and the distance S between every two adjacent electrode strip blocks is larger than or equal to the width W of a grid scanning line. According to the display panel and the driving method thereof, by optimizing the common electrode structure and the driving time sequence, the display performance and the refreshing efficiency of cholesteric liquid crystal electronic paper are remarkably improved.

The invention discloses a rapid polarized light acoustic imaging device which comprises an excitation source, a light beam shaping module, a rapid polarization modulation module, an energy feedback module, a rapid scanning module and an acquisition processing module. And receiving photoacoustic signals corresponding to the exciting light in four different polarization states for calculation, and extracting anisotropy information of the sample. Compared with multiple times of scanning a sample or modulating the polarization state by rotating a half-wave plate, the problems of dislocation of multiple times of polarization acquisition points and false positive calculation are avoided, meanwhile, the time interval generated by continuously modulating the laser pulses is short, and energy fluctuation among the four pulses and errors caused by fluctuation are reduced. According to the invention, the limitation of the precision and speed of polarized light acoustic microscopic imaging is overcome, the microstructure characteristics in the target sample can be rapidly, accurately and highly sensitively detected, and the method has great application prospects in biomedical imaging and high-precision material detection.

The embodiment of the invention provides an optical detection device which comprises an imaging assembly and a photoelectric detection device, and the imaging assembly is used for forming an image on an image plane of a to-be-detected area of a wafer. And the photoelectric detection device is used for receiving images and is arranged at the image plane. The photoelectric detection device comprises a light beam separation assembly and a sensor assembly, the light beam separation assembly is used for dividing a continuous first light signal in an image into multiple beams of second light signals, and the light beam separation assembly comprises a microlens array. The sensor assembly is used for receiving multiple beams of second optical signals, and each pixel unit of each sensor in the sensor assembly is used for receiving one beam of second optical signal in the multiple beams of second optical signals. The sensor assembly comprises a single-pixel sensor, and the single-pixel sensor corresponds to one micro lens in the micro lens array; and / or, the sensor assembly comprises a multi-pixel sensor, the multi-pixel sensor corresponds to a plurality of microlenses in the microlens array, and spatial segmentation is beneficial to improving the signal-to-noise ratio.

Described is a system for anomaly detection from hyperspectral data. The system receives, from a hyperspectral sensor, input hyperspectral data cubes with input data bands for every pixel. Using an optimization technique, an optimized number of virtual bands is determined to use for combining the hyperspectral data cubes to achieve optimal anomaly detection performance. The optimized number of virtual bands is less than the input data bands, resulting in reduced hyperspectral data. The hyperspectral data cubes are combined into the optimized number of virtual bands with the optimal bandwidth for each virtual band, and a set of combined hyperspectral data is output. Anomalies are detected in the set of combined hyperspectral data using an anomaly detection technique. Based on the detected anomalies, single-pixel or subpixel targets of interest are detected in the combined hyperspectral data.

The invention relates to the technical field of MIP devices, solves the problems that in the prior art, a single-pixel MIP device is large in pin number, low in screen body contrast ratio and high in manufacturing cost, and provides an all-in-one MIP device and a manufacturing method thereof.The manufacturing method comprises the steps that a substrate to be processed is obtained, and bonding pads and copolar lines are formed on the second surface of the substrate through deposition; depositing and forming an insulating layer in a non-pad area in the second surface; forming a through TGV conductive through hole in the substrate along the thickness direction, and forming a conductive metal layer in the TGV conductive through hole; forming back pin metals in one-to-one correspondence with the TGV conductive through holes on the first surface to form a pin array; welding the LED chips on the bonding pad in a flip-chip manner, and arranging the LED chips at intervals to form pixel units; and a packaging layer is deposited and formed on the LED chip and the gap area of the LED chip, and the all-in-one MIP device is obtained. The number of the pins is reduced, the contrast ratio of the screen body is improved, and the manufacturing cost is reduced.

The invention discloses an ultra-low illumination-oriented SPAD active imaging data compression method, which comprises the following steps of: performing wavelet decomposition on histogram data of a single pixel in a time-frequency domain based on wavelet transform to obtain low-frequency data of each pixel after wavelet decomposition; by taking each pixel as a center, performing non-maximum suppression and data enhancement on the low-frequency data after the wavelet decomposition of the current pixel by using adjacent pixels to obtain processed compressed data; customizing different Gaussian kernel parameters for each pixel according to the possibility that each pixel is located at the boundary, and performing Gaussian filtering on the processed compressed data of each pixel to obtain filtered data; and performing depth estimation on the filtered data to obtain a final depth image. According to the method, the depth reconstruction performance of the laser pulse can be improved by utilizing the multi-resolution characteristic of wavelet transform, the space-time correlation of signal photons and the smoothness of Gaussian filtering.

The invention provides a heart MRI quantitative imaging motion correction and parameter graph reconstruction and segmentation method and system. The method comprises the following steps: constructing a multi-task model; and constructing a motion-free simulation signal data set of the selected quantity imaging task, and pre-training the single-pixel parameter estimation network and the single-pixel signal simulation network based on the data set. And constructing a real image data set of the selected amount of imaging tasks, fixing network parameters obtained by pre-training, and training a multi-task model to determine values of residual parameters in the model. And performing motion correction, quantitative parameter graph reconstruction and region-of-interest segmentation on a newly acquired image sequence of the selected amount of imaging task through the trained multi-task model, and outputting a reconstructed quantitative parameter graph and a segmentation mask of the quantitative parameter graph. The method is more accurate and quicker, and can realize full-automatic and one-stop post-processing of heart quantitative imaging.

The invention discloses a feature hierarchical attention fusion and dynamic optimization method for single-stage target detection, and relates to the technical field of computer vision. The method comprises the steps of collecting image data, preprocessing an image and dividing the image into a training set, a test set and a verification set; the HAF-DRFPN neck network uses dynamic up-sampling single pixel point sampling to recover the feature resolution; feature extraction is optimized by using a gating residual mechanism and depth separable convolution; a feature refining feed-forward network is introduced through multi-layer perception generation weight, and feature expression is enhanced; respectively capturing and fusing superficial details and deep semantic information by utilizing channel and space attention and cross attention; a multi-branch dynamic sampling stacking framework is adopted, and cross-scale features are adaptively fused and optimized; multi-module cooperative processing is carried out on the whole architecture, and multi-scale features with higher discrimination are provided for the detection head; according to the method, the YOLO12 trunk and the detection head are connected with the HAF-DRFPN to form the model HAF-DRNet suitable for target detection, so that the flexibility and accuracy of single-stage target detection are improved.

The invention relates to a pavement crack image skeleton extraction method based on an improved Zhang-Suen refinement algorithm. The method comprises the following steps: S1, carrying out binarization processing on a pavement crack image; s2, carrying out boundary expansion on the crack binary image; s3, carrying out run-length coding on the crack binary image in the horizontal direction, and carrying out compression storage on continuous non-zero pixel segments in each row; s4, using an improved Zhang-Suen refinement algorithm to process the crack binary image processed in the step S3; s5, removing boundary extension; s6, performing simplification processing on the preliminarily refined crack skeleton image by using four predefined 3 * 3 L-shaped structure templates; s7, removing burrs in the image; and S8, outputting a crack skeleton image. The technical problems that according to an existing skeleton extraction method, a topological structure is prone to being damaged, the calculation efficiency is low, the extraction result cannot be completely a skeleton with the single pixel width, and burrs exist in the skeleton extraction result are solved.

The invention belongs to the technical field of synthetic aperture radars, and relates to an InSAR sequence time decoherence suppression method based on a complex covariance matrix, and the specific process is as follows: for a plurality of input SLC SAR image complex vectors, extracting a single-pixel p-dimensional complex scattering vector at a pixel x, and generating an initial complex covariance matrix; the method comprises the following steps: generating a rectangular search window Wx by taking a pixel x as a center, aiming at multiple input SLC SAR image complex vectors, extracting a p-dimensional complex scattering vector of a single pixel at a pixel y in the search window, and generating a reference complex covariance matrix; enabling the pixel y to traverse each pixel except the pixel x in the rectangular search window Wx, and calculating a maximum likelihood test statistic Q (x, y) according to the initial complex covariance matrix and the reference complex covariance matrix; and based on a complex covariance matrix # imgabs0 # estimated by Q (x, y), extracting the intensity, the phase and the correlation coefficient of the InSAR sequence after de-coherence suppression at the pixel x from the complex covariance matrix # imgabs0 #, and finally obtaining a time sequence de-coherence suppression result of the complete SAR interferogram sequence.

The invention discloses a single-pixel multi-encryption imaging method and device and a storage medium. The method comprises the steps of generating a single-pixel orthogonal basis transform coding illumination pattern, and exchanging the sequence of a coding illumination pattern sequence by using a time sequence key and a remapping algorithm; the coded illumination pattern is processed by using a space key, and at the moment, an image sequence is encrypted in two aspects of a space domain and a frequency domain; projecting a preset coding illumination pattern to the surface of an object to be encrypted and imaged; measuring and recording the light intensity of the reflected or transmitted light by using a detector; decrypting the signal by using the combination of the space key and the time sequence key to obtain a plaintext signal; and reconstructing the image by using a corresponding single-pixel imaging method. According to the method, the single-pixel imaging technology is utilized, the image encryption signal can be obtained under the condition of low sampling rate, calculation only needs to be carried out when the encryption coding illumination pattern is generated, and the defect that a traditional image encryption method based on a camera is large in calculation amount is overcome.

The invention discloses an electric power meter intelligent reading system based on image recognition, and relates to the technical field of computer vision. The method is used for solving the problems of poor instrument reading stability and low range identification accuracy in a complex environment. The method comprises the following steps: firstly, performing multi-scale retina processing and four-direction gradient integral response analysis through an anti-shielding dial plate detection module, generating a probability heat map based on symmetry distribution, and outputting an accurate dial plate region segmentation mask through channel fusion; secondly, extracting a single-pixel wide pointer skeleton through non-maximum suppression and morphological refinement by using a meta-learning skeleton extraction module, and obtaining scale line distribution characteristics based on radial gradient analysis; thirdly, performing three-level progressive verification through a context range analysis module in combination with a geometrical relationship, a knowledge graph and a logical relationship, and outputting a range parameter; multi-dimensional information fusion is adopted to evaluate segmentation quality and skeleton integrity and verify consistency, reliable reading is generated, credibility evaluation is carried out, and high-precision stable reading in a complex environment is realized.

The invention provides an infrared image sensor and a pixel-level reading circuit thereof, and relates to the field of infrared image sensors. The pixel-level reading circuit is integrated in a single pixel unit, and comprises a direct injection input-level circuit used for converting an infrared light-generated current generated by an infrared image sensor into an analog voltage signal; the pulse frequency modulation analog-to-digital converter is connected with the direct injection input stage circuit and is used for converting the analog voltage signal into a pulse signal; the SR latch is electrically connected with the pulse frequency modulation analog-to-digital converter and is used for carrying out accumulative counting on the pulse signals so as to form digital code words reflecting the infrared light intensity; and the digital logic control unit is electrically connected with the SR latch and is used for transmitting the digital code word to a reading bus of the infrared image sensor, so that the output of a digital signal is realized, and the reading rate of the image sensor is improved.

The invention discloses a remote sensing image road breakpoint repairing method and device and a medium. The method comprises the steps that a road image is converted into a binary image, a connected region is calculated, a threshold value is set to remove part of the connected region, skeletonization operation is conducted on the optimized binary image, and a road is converted into a road skeleton with the single-pixel width. Extracting breakpoints of all roads, and obtaining breakpoint parameter values; on the basis of the matching value between each group of breakpoint pairs, connecting the breakpoint pairs of which the matching values exceed a threshold value, and obtaining a perfect road skeleton; road width repairing is conducted on the perfected road skeleton, and a repaired road is obtained. According to the method, the repaired road is regularized, so that the width of the repaired road is ensured to conform to a physical rule, the condition of road boundary distortion or excessive connection caused by mismatching is avoided, and the repaired road boundary is more accurate and natural by optimizing the smoothness and regularity of the repaired path; and the risk of misjudgment is reduced.

The embodiment of the invention provides a photoelectric detection device and an optical detection device. The photoelectric detection device comprises a light beam separation assembly and a sensor assembly. The light beam separation assembly is used for dividing a continuous first light signal into a plurality of beams of second light signals at different spatial positions. The sensor assembly is used for receiving multiple beams of second optical signals. The sensor assembly includes a plurality of sensors, the plurality of sensors including single-pixel sensors. The continuous first optical signal is divided into a plurality of small discrete second optical signals through the light beam separation assembly, so that the light sensing area of each sensor corresponding to a sample is further reduced, the haze noise on a single sensor is further reduced through the small light sensing area, and the haze noise on the single sensor is further reduced under the condition that the original first optical signal is not changed. Noise on a single sensor is reduced, and the signal-to-noise ratio of the photoelectric detection device is improved.

The invention provides a visual positioning method and system for an automatic drilling robot of a tire mold, and the method comprises the steps: calibrating the internal and external parameters of a camera, and obtaining the target surface identification of the tire mold and the workpiece coordinates of key points; based on the image feature template, identifying a pixel coordinate of the target surface identifier and an actual physical size corresponding to a single pixel; according to the internal reference of the camera and the workpiece coordinates and pixel coordinates of the target surface identifier, the initial conversion relation of the workpiece relative to the robot coordinate system is solved; pixel coordinates of the key points are obtained based on the initial conversion relation; calculating actual coordinates of a key point robot coordinate system according to the pixel coordinates of the key point, the photographing pose and the internal reference of the camera; and matching the three-dimensional coordinates of the key points with coordinates of a robot coordinate system through a singular value decomposition algorithm, and solving an accurate conversion relation of the workpiece relative to the robot coordinate system. A target surface and key points are recognized through template matching and machine vision, and the accurate conversion relation between a workpiece and a robot coordinate system is calculated, so that efficient positioning of the tire mold exhaust hole is achieved.

The invention relates to the technical field of optical imaging, and discloses a single-pixel color imaging system based on multi-wavelength radio frequency marking. The system comprises a light source module used for generating three laser beams with three optical primary colors; the radio frequency driving module is used for generating a radio frequency complex frequency signal; the light path adjusting module is used for performing heterodyne interference processing on the three laser beams according to the radio frequency complex frequency signal, respectively forming a light spot array and a reference light source and then combining the beams, and generating a combined beam to be incident on a measured target; each laser beam corresponds to one group of sub light spot arrays; sub light spot arrays with aligned spatial positions exist among the three groups of sub light spot arrays; the detected target detection module is used for collecting light data generated after a detected target reflects the combined light beam; and the image inversion module is used for performing image inversion processing on the optical data to generate a true color image of the measured target. According to the system, the light spot array of multi-wavelength laser incidence can be registered in the spatial position.

The invention discloses a self-adaptive underwater single-pixel imaging technology based on Fourier modulation, belongs to the technical field of computational optical imaging, is used for ocean detection and improvement of ocean surveillance and defense efficiency, and adopts a self-designed LED array to replace an expensive DMD and a four-quadrant detector composed of common photodiodes to replace an expensive barrel detector. And high-speed illumination and parallel acceptance are realized while the cost is greatly reduced. The technical route comprises a high-speed underwater single-pixel imaging device, a high-speed Fourier single-pixel imaging algorithm and an adaptive sampling strategy based on Fourier single-pixel imaging. The high-speed single-pixel imaging device comprises a self-designed LED array light modulation module, a converging lens module and a receiving module. The high-speed Fourier single-pixel imaging algorithm comprises a binarization algorithm based on error diffusion and an algorithm based on adaptive compressed sensing. According to the innovative self-adaptive sampling strategy based on Fourier single-pixel imaging, a specific sampling path is generated by fusing circular sampling and random sampling according to the characteristics of an image in a Fourier spectrum, so that Fourier coefficients which have great influence on image quality are acquired as much as possible under water with low sampling rate and high turbidity, and the image quality is improved. Therefore, the high-efficiency imaging of the underwater target object is realized, and the imaging speed and quality are both considered.

The invention discloses a machine vision-based micro-plastic intelligent identification and measurement method, which comprises the following steps: filtering a water sample containing micro-plastic or not containing micro-plastic, and acquiring images under a uniform amplification factor by using a microscope to obtain a micro-plastic image to be detected and a contrast image; calculating the absolute value of the color centroid value of the contrast image and the color difference value of the micro-plastic image, generating a difference image, and carrying out denoising, graying and binarization processing on the difference image to obtain a binary image with highlighted micro-plastic; extracting pixel coordinates of the micro-plastics, setting a threshold value to carry out connected clustering, and distinguishing the micro-plastics and image impurities in combination with a preset micro-plastic recognition threshold value to realize micro-plastic recognition and quantity statistics; and further shooting a standard objective lens micrometer image, calculating the actual physical size represented by a single pixel, and automatically calculating the area and the length of the micro-plastic by combining each clustering enclosing rectangle and the number of the pixels. The method is accurate in recognition and high in operation automation degree, and can be widely applied to intelligent recognition and analysis of water body micro-plastics.

The invention discloses a pulse terahertz time-domain spectroscopy system of a single photoconductive antenna and a detection method, and relates to the technical field of terahertz, the system comprises a laser pulse generation module, a single photoconductive antenna module, a compression sampling module, a signal reconstruction module and a control unit; by integrating the random light delay modulation unit and the single-pixel detector, the system realizes random time interval sampling of terahertz signals, effectively breaks through the limitation of a traditional sampling mode, improves the flexibility and efficiency of signal acquisition, and combines a signal reconstruction module of an FPGA + GPU heterogeneous computing architecture, so that the system has a wide application prospect. The system can adaptively construct a sparse base and perform accurate sparse representation on a measurement vector, so that an original terahertz time domain signal is efficiently reconstructed by optimizing a target function and an adaptive iterative solution algorithm, the signal reconstruction precision is improved, the data processing complexity is also reduced, and the method is suitable for large-scale popularization and application. And powerful support is provided for practical application of the terahertz technology.

The invention provides an industrial anomaly classification method and system based on a multi-modal large language model, and belongs to the technical field of visual detection. The visual pre-screening module adopts a BYOL unsupervised feature extractor and a local block matching technology to calculate the minimum Euclidean distance between an image to be detected and a normal sample so as to generate an abnormal thermodynamic diagram, and efficient preliminary screening is realized; the coordinate set is converted into a binary mask through an abnormal contour marking module, and an accurate single-pixel contour is generated through morphological gradient and SIFT displacement correction; fusing a CLIP visual encoder and a GPT text encoder in a multi-modal decision engine, realizing visual-semantic alignment through cross-modal fusion and a multi-head attention mechanism, and supporting alpha hybrid dynamic rule update; and a dynamic classification executor calculates an abnormal region risk index based on the risk grading model, and generates a grading response action and a structured report. According to the invention, the classification precision is improved, so that the method can adapt to complex and diversified industrial abnormal scenes.

The invention provides a fast color single-pixel imaging system and method based on an FPGA and a DLP projector, the fast color single-pixel imaging system comprises the DLP projector, a single-pixel photoelectric detector, an AD data acquisition card, a Raspberry Pi and the FPGA, the Raspberry Pi is adopted as an upper computer, the FPGA and the AD data acquisition card are dispatched to work cooperatively, and the DLP projector and the single-pixel photoelectric detector are integrated. The rapid and stable projection of the substrate pattern and the accurate sampling of the corresponding reflected light intensity information are realized, and the efficient reconstruction of the color image of the target scene is further realized. In a data acquisition stage of an imaging system, an HDMI image data output task is executed by the FPGA, and the FPGA outputs an image frame synchronization signal, so that the stability problem and the signal synchronization problem when a substrate pattern is played at a high frame rate (60Hz) are solved by making full use of the advantages of stable and controllable sequential logic and no software level scheduling delay of the FPGA, and the stability problem and the signal synchronization problem when the substrate pattern is played at a high frame rate (60Hz) are solved. And the influence of image tearing, frame loss and frame repetition on image reconstruction is eliminated.

The invention discloses a curved broken filament cluster-shaped region closing and defect area quantification method, which comprises the following steps of: firstly, performing image acquisition on a target region containing a curved broken filament defect to obtain an original image; preprocessing the original image to obtain a binary defect area image, and performing skeletonization processing to obtain a defect skeleton curve of a single pixel width; segmenting the skeleton curve and carrying out arc fitting to obtain a fitting circle and a starting point, an ending point and a midpoint of an arc section; judging whether the arc section exceeds a semicircle or not by constructing a triangle, and complementing the arc section exceeding the semicircle by using a fitting circle to form a closed area; and finally, combining all the closed areas to generate a defect mask, calculating an actual area and judging whether the defect is qualified or not according to a preset threshold value. According to the method, the bent broken filaments are subjected to reasonable ball-shaped region closing treatment, so that the quantized defect area is highly consistent with a manual visual inspection result.

The invention discloses a single-pixel phase imaging method based on an untrained physical driving neural network, and belongs to the field of single-pixel imaging and computational optics. According to the method, by adding a physical diffraction layer and an Admn optimizer, direct reconstruction from a single-pixel detection intensity sequence to a phase object image is realized. According to the method, pre-training is not needed, and the dependency on a large data set is remarkably reduced; by introducing the total variation loss of the output phase, the influence of noise and optical distortion is effectively suppressed; and when the sampling rate is as low as 30%, the phase distribution can still be efficiently reconstructed, and the required sampling number is reduced.

The invention relates to a skeleton line intersection region redundancy restoration method based on distance constraint and center substitution, and belongs to the field of image processing, and the restoration method comprises the steps: extracting a 3 * 3 neighborhood of each foreground pixel point in a skeletonized image, temporarily setting a center pixel as a background value, and detecting an intersection point through an 8-neighborhood connection marking algorithm; realizing cross point clustering through Euclidean distance calculation and a breadth-first search algorithm based on the spatial proximity relationship of the cross points; and carrying out group screening, ignoring a group only containing a single cross point, and carrying out topology reconstruction on a group containing a plurality of cross points. According to the method, the redundant pixel cluster is accurately identified, the quality of the skeleton line is improved, the redundant pixels in the diagonal line area are accurately identified and cleared through the template matching algorithm, the skeleton line is ensured to strictly meet the single-pixel width requirement, and false endpoints and line length measurement errors are avoided.

The invention relates to the technical field of defect detection, in particular to a defect detection method and system based on a microwave frequency crystal resonator, and the method comprises the steps: forming a microwave probe through a microwave frequency crystal resonator array, placing a to-be-detected material below the microwave probe, and setting a scanning area and scanning step lengths in two directions on the surface of the material; controlling the probe to perform point-by-point scanning according to step length, and collecting a plurality of reflection coefficients of each sampling point to form an echo signal matrix; performing singular value decomposition on the matrix, applying an adjustable coefficient to a first singular value and a second singular value, and adaptively selecting an optimal coefficient according to imaging quality to reconstruct an echo signal; performing two-dimensional Fourier transform on the reconstructed matrix, constructing a spatial filter in combination with probe spacing and defect depth to perform phase compensation, performing two-dimensional Fourier transform to obtain a defect image, and performing threshold segmentation on the defect image to obtain a binary image only containing defects; and analyzing the connected regions to obtain the gravity center position of each defect and the defect area determined by the pixel number and the single pixel area. The problems of serious clutter interference, insufficient defect imaging contrast ratio, difficulty in quantitative evaluation of defect size and the like in the existing microwave detection can be solved.

The invention relates to a gallium oxide defect detection method. The method comprises the following steps: step 1, obtaining exciting light with a proper wavelength; 2, modulating the exciting light obtained in the step 1 so as to enable the exciting light to accurately enter a microscope system with proper energy; 3, irradiating the modulated exciting light to a gallium oxide sample on an electric displacement table through a microscope system, collecting fluorescence generated after the gallium oxide sample is excited through the microscope system, and transmitting the fluorescence to a spectrograph system to obtain a corresponding fluorescence spectrogram under a preset single pixel point position; and 4, setting a spectrograph system to collect the fluorescence intensity under a specific wavelength, and driving the gallium oxide sample to move through an electric displacement table so as to scan the fluorescence intensity of all pixel point positions in a sample detection range, thereby obtaining a gallium oxide defect fluorescence intensity imaging graph in the sample detection range. The method has the advantage of high sensitivity, can realize rapid nondestructive detection, and also reduces the detection cost at the same time.

The invention discloses an image deblurring method and system based on an energy distribution model, and relates to the technical field of image processing, and the method comprises the steps: building a pixel energy distribution model through analyzing the blurring cause of an image collected by a diffraction limited system; taking an image plane region corresponding to the pixel as a basic unit, and performing convolution operation by using a point spread function and a pixel description function to obtain a pixel energy distribution model; determining a mathematical description form of a point diffusion spot and determining an Airy spot radius so as to calculate energy distribution of a single pixel; dividing the pixel energy distribution model into designated areas, and calculating the energy ratio of each area; deducing a blurring-removing operator based on the energy ratio; and performing convolution operation on the original image and the deblurring operator to complete deblurring processing of the image. Through the image deblurring method based on the energy distribution model, the definition of the image acquired by the diffraction limited system is improved.

The invention belongs to the technical field of optical measurement, and particularly relates to a high-stability synthetic wavelength phase demodulation method. The method comprises the following steps: based on three-wavelength synthesis phase preprocessing and branch correction, expanding an unambiguous range to a millimeter level by calculating a secondary synthesis wavelength; in the staged processing strategy, a rough measurement height contour is generated by using a corrected synthetic phase, and then efficient candidate height screening is realized by combining integer period traversal and local microentry error function optimization; and finally, abnormal solutions are eliminated through multi-wavelength consistency inspection, and the noise immunity is ensured. The method does not need to depend on complex hardware, large-range (dozens of microns) high-precision (sub-nano-scale) measurement is achieved through pure-method design, the surface contour detection requirement of a large-size workpiece is met, the single-pixel processing time is shortened to the microsecond level, real-time measurement is supported, and the method is suitable for large-size surface appearance detection in the fields of aerospace, precision manufacturing and the like.