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54results about How to "Guaranteed reconstruction accuracy" patented technology
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Regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method
ActiveCN101908230AStable matching costReduce mistakesImage analysis3D modellingObject pointReconstruction method
The invention discloses a regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method, which is implemented by the following steps: (1) shooting a calibration plate image with a mark point at two proper angles by using two black and white cameras; (2) keeping the shooting angles constant and shooting two images of a shooting target object at the same time by using the same camera; (3) performing the epipolar line rectification of the two images of the target objects according to the nominal data of the camera; (4) searching the neighbor regions of each pixel of the two rectified images for a closed region depth edge and building a supporting window; (5) in the built window, computing a normalized cross-correlation coefficient of supported pixels and acquiring the matching price of a central pixel; (6) acquiring a parallax by using a confidence transmission optimization method having an acceleration updating system; (7) estimating an accurate parallax by a subpixel; and (8) computing the three-dimensional coordinates of an actual object point according to the matching relationship between the nominal data of the camera and the pixel and consequently reconstructing the three-dimensional point cloud of the object and reducing the three-dimensional information of a target.
Owner:江苏省华强纺织有限公司 +1
Improved self-adaptive sparse sampling fault classification method
InactiveCN109993105AReduce redundant informationReduce complexityMachine bearings testingCharacter and pattern recognitionClassification methodsTime shifting
An improved self-adaptive sparse sampling fault classification method belongs to the technical field of fault diagnosis. A traditional sparse classification method is improved. Firstly, a wavelet module maximum value and a kurtosis method are used for carrying out feature enhancement processing on signals, and on the premise that signal sparsity is guaranteed, a unit matrix is adopted to replace aredundant dictionary. Secondly dimension reduction is carried out on data by adopting a Gaussian random measurement matrix, thereby reducing redundant information in the signal, and reserving effective and small amount of data. Then, a sparse coefficient is solved by adopting a sparsity adaptive matching pursuit (SAMP) algorithm, and the compressed signal is reconstructed; and finally, a cross correlation coefficient is adopted as a judgment basis of the category of the fault, so that an improved adaptive sparse sampling fault classification method is provided. Experimental verification proves that redundant information in signals is effectively reduced, the influence of time shift deviation on fault type judgment is avoided, meanwhile, the operation complexity is reduced, and the calculation speed and the reconstruction precision are improved.
Owner:BEIJING UNIV OF CHEM TECH
Rapid compression perception reconstruction method facing to wearable device
ActiveCN107147397AGuaranteed reconstruction accuracyFast reconstruction accuracyCode conversionMultiplier methodReconstruction method
The invention discloses a rapid compression perception reconstruction method facing to a wearable device, and belongs to the signal processing field. The method comprises the steps of: performing compression measurement to an original electrocardiogram signal x through a constructed m*n dimension random sparse binary observation matrix phi, so as to get an observation vector y, the length of which is m; and based on the observation matrix phi and the observation vector y, reconstructing the original signal by the compression perception reconstruction method learned from the alternating direction multiplier method and the block sparse Bayes, so as to get an estimation vector of the original signal, which is as shown in the description. Compared with the conventional compression perception reconstruction method learned from the block sparse Bayes, the method provided by the invention is advantaged in reaching quicker reconstruction speed on the premise of ensuring the reconstruction precision.
Owner:UNIV OF ELECTRONIC SCI & TECH OF CHINA +1
Sparse unmixing method based on optical calculation
InactiveCN106788714AGuaranteed reconstruction accuracyIncrease storage capacityCharacter and pattern recognitionFree-space transmissionAlgorithmDecomposition
The invention relates to a sparse unmixing method based on optical calculation. The method comprises the following steps: S1, an optical filtering method is adopted to acquire a transform domain sparse coefficient matrix for hyperspectral signals; S2, a deterministic measurement matrix is designed to realize perception measurement on the hyperspectral signals; S3, parallel multiplication calculation is carried out on the sparse coefficient matrix and the deterministic measurement matrix through a hardware FPGA for acquiring endmember signals; and S4, the sparse structural information of the hyperspectral signals and a structured reconstruction algorithm are used for reconstructing an abundance matrix. The optical filtering technology and an electrical system are adopted to realize multiscale geometric analysis, the sparse unmixing efficiency is greatly improved on the premise of ensuring the reconstruction precision, and quick and effective sparse decomposition can be realized.
Owner:CHONGQING TECH & BUSINESS UNIV
Variable step size distributed compressed sensing reconstruction method based on recurrent neural network
InactiveCN107317583AExpand the scope ofThe amount of calculation does not increaseCode conversionNeural architecturesConditional probabilityLeast squares
The invention belongs to the field of distributed compressed sensing reconstruction technology, and particularly relates to a variable step size distributed compressed sensing reconstruction method based on a recurrent neural network. The method comprises the following steps: acquiring structural information of a vector to be reconstructed of each channel by using the recurrent neural network, obtaining each non-zero conditional probability of the vector in each channel, then estimating an optimal atom of the current iteration, and then determining a value of a non-zero term of each channel by solving a least square problem, and completing the reconstruction of signals. According to the method, non-combined sparse multi-channel signals can be reconstructed, and meanwhile, the computational complexity of the coding end cannot be increased.
Owner:HUBEI UNIV OF TECH
Three-dimensional human body rapid reconstruction method based on simple measuring clothing
ActiveCN108269302ALow costHigh speedImage enhancementDetails involving processing stepsFeature vectorHuman body
The invention discloses a three-dimensional human body rapid reconstruction method based on simple measuring clothing. For each sample human body of an existing human body library, characteristic parameters and characteristic curves are extracted as human body characteristics to form a human body characteristic database; a PCA method is used to construct a human body shape space; a neural networkis used to establish a mapping model between the human body characteristics and the human body shape space; the characteristic parameters of a human body to be tested are measured, and characteristiccurves of the human body to be tested is obtained by using simple measuring clothing; and the characteristic parameters and characteristic curves of the human body to be tested are input into the mapping model to obtain characteristic values corresponding characteristic vectors of the human body to be tested in the human body shape space, and a three-dimensional human body model is obtained through restoration and reconstruction. In the invention, the characteristic curves of high spatial dimension provide rich surface geometric information of the human body, the multi-layer neural network accurately reflects the mapping model between the human body characteristics and the human body shape space, and the accuracy and reliability of the human body three-dimensional reconstruction are improved.
Owner:ZHEJIANG UNIV
Curved surface reconstruction method of three-dimensional point cloud, computer equipment and computer readable storage medium
ActiveCN112669463ASmall footprintImprove operational efficiency3D modellingComputational sciencePoint cloud
The embodiment of the invention provides a curved surface reconstruction method of three-dimensional point cloud, computer equipment and a computer readable storage medium. The disclosed curved surface reconstruction method comprises the following steps: inputting point cloud data; constructing a KD tree spatial data index of the point cloud data to obtain block point clouds which are equal in number and are uniformly distributed; carrying out grid reconstruction on each block point cloud by adopting a Delaunay point-by-point insertion method to obtain a triangulation network model corresponding to each block point cloud; and detecting an overlapping region between the triangulation network models corresponding to the block point clouds, reconstructing the grids of the overlapping region, and splicing the triangulation network of the overlapping region and the triangulation network of the non-overlapping region after grid reconstruction to obtain a complete triangulation network model corresponding to the input point cloud data. According to the technical scheme provided by the embodiment of the invention, the memory consumption is effectively reduced, and the grid reconstruction efficiency and the grid reconstruction precision of the point cloud data are relatively good.
Owner:河南信大融通信息科技有限公司
Teleoperation method for unstructured environment based on 5G + AR
ActiveCN111459274AFast 3D reconstructionAccurate and fast teleoperation assemblyInput/output for user-computer interactionProgramme-controlled manipulatorComputer graphics (images)Teleoperation
The invention discloses a teleoperation method for an unstructured environment based on 5G + AR. The method comprises the following steps: firstly, carrying out rapid three-dimensional reconstructionon an unstructured environment where a robot is located, and mapping a reconstructed scene into a virtual reality space; and then, capturing a gesture action of a user, establishing a virtual model ofthe hand of the user, and mapping the gesture action into the virtual reality space, thereby realizing interaction between the user and the virtual object; finally, introducing an auxiliary technology to help the user finish teleoperation work more accurately and quickly.
Owner:GUANGZHOU LONGEST SCI & TECH
Reconstruction method and device for target electromagnetic-scattering-characteristic data
ActiveCN109444842AGuaranteed reconstruction accuracyImprove efficiencyWave based measurement systemsEcho signalReconstruction method
The invention discloses a reconstruction method and device for target electromagnetic-scattering-characteristic data, and relates to the technical field of radar imaging. The method includes the stepsthat a three-dimensional echo signal model of a target is built, and the three-dimensional echo signal model is converted into a state-space equation; according to scattering echo data of the target,a generalized Hankel matrix is built, and the state-space equation is solved based on the Hankel matrix to determine a parameter estimating value of the target scattering center; according to the parameter estimating value of the target scattering center, electromagnetic-scattering-characteristic data of the target is reconstructed. Through the steps, the reconstruction accuracy of the target electromagnetic-scattering-characteristic data is guaranteed, and efficient compression and real-time loading of the full-space target electromagnetic-scattering-characteristic data can also be achieved.
Owner:BEIJING INST OF ENVIRONMENTAL FEATURES
Eddy current array detection apparatus based on compressed sensing and detection method thereof, and eddy current array probe
PendingCN107167517AGuaranteed reconstruction accuracyReduce the sampling frequencyMaterial magnetic variablesData acquisitionHardware modules
The invention relates to an eddy current array detection apparatus based on compressed sensing and a detection method thereof, and an eddy current array probe. The eddy current array detection apparatus comprises an excitation signal generator, a power amplifier, the eddy current array probe, a signal acquisition module, a FPGA controller and a PC host computer. The eddy current array probe is composed of eddy current probe units, and each eddy current probe unit is composed of a probe shell, a tip, a bottom cover, mounting nuts, excitation coils, coil formers, an iron core, a TMR magnetic sensor and a printed circuit board. According to the invention, in virtue of the characteristic of sparsity of array signals, the precision of signal reconstruction is guaranteed and signal sampling frequency is greatly reduced, so requirements on hardware modules like sampling circuits are lowered, the amount of sample data is reduced, hardware burden in data acquisition, transmission and storage is mitigated, and the service life of equipment is prolonged; and for portable instruments powered by limited energy and equipped with array probes, energy consumption for sampling and calculating can be greatly saved, and the service life of the portable instruments can be substantially prolonged.
Owner:KUNMING UNIV OF SCI & TECH
Robot vision SLAM closed-loop detection method based on stack type combined auto-encoder
InactiveCN111753789AImprove accuracyImprove robustnessCharacter and pattern recognitionNeural architecturesStochastic gradient descentFeature vector
The invention discloses a robot vision SLAM closed-loop detection method based on a stack type combined auto-encoder, and belongs to the field of mobile robot vision SLAM. The method comprises the following steps: S1, preprocessing a visual SLAM scene image, and inputting the visual SLAM scene image into a stack type auto-encoder model; s2, training a network model layer by layer, iterating network parameters by adopting a stochastic gradient descent algorithm, and continuously adjusting the model parameters to minimize a reconstruction error; s3, extracting a feature vector of the visual SLAMscene image by using the trained stack type combined auto-encoder; s4, calculating the similarity between the feature vector VK of the kth key frame (current frame) of the visual SLAM scene and the feature vectors V1, V2,..., VN of the historical key frames; and S5, comparing the similarity score with a set threshold value, and if the similarity score is greater than the set threshold value, judging that a closed loop is formed. According to the invention, the accuracy and robustness of visual SLAM closed-loop detection can be effectively improved.
Owner:CHONGQING UNIV OF POSTS & TELECOMM
Circular arc front-and-back edge of aviation blade reconstruction method based on error control
InactiveCN103093091AGood noise immunityImprove reconstruction qualitySpecial data processing applicationsLeast squaresReconstruction method
The invention discloses a circular arc front-and-back edge of an aviation blade reconstruction method based on error control, and is used for solving the technical problem that anti-noise performance of the existing blade section characteristic parameters extraction method based on the measured data is poor. The circular arc front-and-back edge of the aviation blade reconstruction method based on the error control is composed of selecting region points covering the front-and-back edge of the aviation blade, arranging the region points, and matching the arranged region points with a cubic spline so as to gain a curve L0. The method carries out discretion and encryption on the matched spline curve L0 in an arc equal-length mode, respectively marks the head discrete point as P0i and the end discrete point as P1i, utilizes the least square method to carry out a circular matching for the discrete points between P0i and P1i containing P0i and P1i, calculating the average error epsilon i from the discrete points to an ith matching circle, and setting the iteration control error as epsilon until the epsilon i is less than or equal to the epsilon, the iteration ends. Based on the error control based on the matching of the least square method for fitting, utilizing the iterative matching method based on the error control, the circular arc front-and-back edge of the aviation blade reconstruction method reconstructs blade circular arc front-and-back edge, avoids that the points in the selected area involve the matching, wherein the points are not on the circular arc, and improves the anti-noise performance.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Hyperspectral sparse unmixing device
ActiveCN109655154AImprove image qualityImprove extraction accuracyRadiation pyrometryColor/spectral properties measurementsMultiscale geometric analysisEngineering
The invention relates to a hyperspectral sparse unmixing device and belongs to the technical field of hyperspectral unmixing. The device comprises a first box body, an air inlet fan, an air inlet cylinder, a filtering grid plate, a noise reduction assembly, a sponge, a damping cotton and a filtering assembly, wherein one end of the air inlet cylinder is inserted and fixed in the side wall of the first box body, the air inlet fan is arranged between the upper inner wall and the lower inner wall of the air inlet cylinder, the filtering grid plate is vertically arranged between the upper inner wall and the lower inner wall of the air inlet cylinder and is positioned at one end port of the air inlet cylinder. According to the invention, the noise reduction assembly filters redundant waves of the signal in the low-pass filter, and real-time additive noise such as cloud layer, atmosphere and the like in the acquisition process is removed, filtered and quantized, so that the quality of the hyperspectral image is improved, and the extraction precision of the end element generating sparse demixing is improved; the multi-scale geometric analysis is achieved by adopting the optical filteringtechnology through the filtering assembly, the sparse demixing efficiency is greatly improved on the premise of ensuring the reconstruction precision, and the rapid and effective sparse decompositionis achieved.
Owner:CHONGQING TECH & BUSINESS UNIV
Wave-front sensor, wave-front detection method and wave-front detection system based on microholographic array
ActiveCN106441084AExpand the detection rangeSuppresses the effect of reconstruction accuracyUsing optical meansAxial displacementWavefront sensor
The invention discloses a wave-front sensor, a wave-front detection method and a wave-front detection system based on a microholographic array. The wave-front detection method based on the microholographic array comprises the following steps: creating the microholographic array which simultaneously has a microlens imaging function and a double helix point diffusion-function function; enabling a to-be-detected wave-front to pass through the microholographic array and obtaining a double helix lattice diagram on a rear focal plane of the microholographic array; obtaining a wave-front slope value according to the double helix lattice diagram, and performing wave-front reconstruction on the wave-front slope value to obtain to-be-detected wave-front information. After the to-be-detected wave-front passes through the microholographic array, the double helix lattice diagram is obtained on the rear focal plane of the microholographic array; when pixel points of the rear focal plane of the microholographic array are out of focus, double helix points can rotate according to a certain rule but cannot significantly expand like gauss points, so that the influence of wave-front out-of-focus errors on reconstruction precision can be inhibited; when a sample generates axial displacement, high detection precision can be stilled obtained, and the detection range in the axial direction of the sensor is improved on the premise of ensuring the detection precision.
Owner:SHENZHEN UNIV
Monocular 3D reconstruction method with depth prediction
The invention discloses a monocular 3D reconstruction method with depth prediction. The monocular 3D reconstruction method comprises the following steps: A, obtaining a depth map and rough pose estimation of an RGB image by using a monocular depth estimation network; b, calculating camera pose estimation in combination with an ICP algorithm and a PnP algorithm, and executing loopback detection on a local level and a global level to ensure the consistency of a reconstruction model; and C, converting the depth map into a global model, and then inserting the random fern code of the current frame into a database. According to the invention, the defects in the prior art can be overcome, and large-scale high-quality three-dimensional reconstruction is realized.
Owner:NAT UNIV OF DEFENSE TECH
Vehicle-mounted rail frequency shift signal rapid compression method based on compressed sensing
InactiveCN103716057AReduce complexityImprove real-time performanceCode conversionReconstruction methodEngineering
The invention discloses a vehicle-mounted rail frequency shift signal rapid compression method based on compressed sensing. The vehicle-mounted rail frequency shift signal rapid compression method is used for rapid compression of rail frequency shift signals in LKJs, DMSs and vehicle-mounted subjectivization cab signal systems on ordinary-speed trains and high-speed trains. The method includes the steps of firstly, calculating the sparsity of a vehicle-mounted rail frequency shift signal to be compressed, and determining whether to conduct sparsity conversion on the vehicle-mounted rail frequency shift signal to be compressed or not according to the sparsity; secondly, compressing a sparsity coefficient through a gauss random matrix to obtain compressed data; thirdly, effectively recovering the rail frequency shift signal just through a compressed sensing reconstruction method when uncompressing the compressed data. According to the method, the compression ratio of the rail frequency shift signal is high, the instantaneity is high, the storage loads of the vehicle-mounted LKJs, the vehicle-mounted DMSs and the vehicle-mounted cab signal systems can be effectively reduced, the bandwidth requirement of vehicle-ground wireless transmission of the vehicle-mounted rail frequency shift signal is lowered, the transmission time delay of vehicle-ground wireless transmission of the vehicle-mounted rail frequency shift signal is reduced, and the method has wide application prospects in high-speed rail vehicle-mounted signal real-time monitoring.
Owner:CHINA RAILWAYS CORPORATION +1
High-energy sparse CT detector, CT detection system and detection method
ActiveCN111157555AReduce the number of rowsGuaranteed accuracyMaterial analysis using wave/particle radiationRadiation intensity measurementComputed tomographyNuclear medicine
The invention discloses a high-energy sparse CT (computed tomography) detector, a CT detection system and a detection method, belongs to the technical field of CT detection, and solves the problems that a CT detection device in the prior art is high in cost, not beneficial to popularization and application of equipment, low in cost, incapable of ensuring imaging precision and the like. The CT detector comprises high-energy detectors and low-energy detectors, the high-energy detectors and the low-energy detectors are arranged in a back-to-back mode, and one low-energy detector is arranged aboveeach high-energy detector; the number of rows of the low-energy detectors is larger than the number of rows of the high-energy detectors, and at least part of the high-energy detectors are distributed in a centralized mode. Part of high-energy detectors of the CT detector are arranged in a centralized mode, the cost is reduced, and meanwhile the imaging precision is high.
Owner:BEIJING HANGXING MACHINERY MFG CO LTD
Eddy current testing method of irregular wear-out defect of thimble tube by introducing multimedia units
InactiveCN108303461AImprove reconstruction accuracySmall sizeMaterial magnetic variablesEddy-current testingControl equation
An eddy current testing method of the irregular wear-out defect of a thimble tube by introducing multimedia units comprises steps as follows: firstly, a degenerate magnetic vector potential method discrete control equation is obtained; secondly, the multimedia units containing a substrate and the defect simultaneously is introduced into a unit attribute of the irregular wear-out defect of the thimble tube, the conductivity and the magnetic conductivity attribute in the gauss point position are judged according to the area where the gauss integral point position in the multimedia units is located, and the process of the degenerate magnetic vector potential method discrete control equation is corrected; then, an eddy current detection signal is obtained according to an experiment system; finally, the actual size of the irregular wear-out defect of the thimble tube is obtained according to a conjugate gradient algorithm. After the multimedia units are introduced to the eddy current testing method of the irregular wear-out defect of the thimble tube, the size of the units can be reasonably increased in the premise that the reconstruction accuracy of the eddy current nondestructive detection of the irregular wear-out defect of the thimble tube is guaranteed, so that the total number of the units is notably reduced, the calculation efficiency is effectively improved, and the method has very high practical value.
Owner:XI AN JIAOTONG UNIV +1
Image processing method, system and device and storage medium
PendingCN113674172AGuaranteed convergenceGuaranteed reconstruction accuracyImage enhancementImage analysisImage denoisingImaging processing
The invention provides an image processing method, system and device and a storage medium, which are used for image sparse reconstruction, image denoising, compressed sensing image reconstruction or image restoration. The image processing method comprises the following steps: establishing a general linear optimization inverse problem under the norm regular constraint of a sparse signal; on the basis of a standard or learned iterative soft threshold shrinkage algorithm, establishing a differentiable deep network model based on convex combination to solve the problem; introducing a deep neural network of any structure in the solving step to accelerate the solving step, and reducing the number of iterations required for convergence of the algorithm. According to the method, a traditional iterative optimization algorithm and a deep neural network of any structure are combined, the image reconstruction performance is improved, rapid convergence is ensured, and the current demand of image sparse reconstruction is met.
Owner:SHANGHAI JIAO TONG UNIV
Feedback method based on ELM superposition CSI in FDD large-scale MIMO system
ActiveCN111193535AGuaranteed reconstruction accuracyReduce training timeSpatial transmit diversityNeural learning methodsChannel state informationSuperposition coding
The invention relates to a feedback method based on ELM superposition CSI in an FDD large-scale MIMO system, which belongs to the technical field of wireless communication. The feedback method comprises the steps that a user side reads downlink channel state information and an uplink user sequence, carries out the superposition of the downlink channel state information and the uplink user sequence, obtains a superposition sequence, and then achieves transmission; and a base station end uses an ELM interference elimination network to recover downlink channel state information and the uplink user sequence in the obtained receiving sequence. Compared with non-superposition coding CSI feedback, the method has the advantages that uplink bandwidth resource occupation is completely avoided. Compared with superposition of CSI feedback based on deep learning, the method has the advantages that under the condition of keeping equivalent network recovery performance, the number of parameters is reduced, the memory occupation space is reduced, and the network training time is shortened.
Owner:XIHUA UNIV
A fast reconstruction method of 3D human body based on simple measurement suit
ActiveCN108269302BLow costHigh speedDetails involving processing stepsImage enhancementPattern recognitionHuman body
The invention discloses a three-dimensional human body rapid reconstruction method based on a simple measuring suit. For each sample human body in the existing human body database, extract characteristic parameters and characteristic curves as human body characteristics to form a human body characteristic database; use PCA method to process and construct human body shape space; establish a mapping model between human body characteristics and human body shape space through neural network ;Measure the characteristic parameters of the human body to be measured, and use the simple measuring suit to obtain the characteristic curve of the human body to be measured; input the characteristic parameters and characteristic curves of the human body to be measured into the mapping model to obtain the corresponding feature vectors of the human body to be measured in the human body shape space eigenvalues, and then restore and reconstruct to obtain a 3D human body model. In the present invention, the characteristic curve of high spatial dimension provides abundant geometric information of the human body surface, and the multi-layer neural network accurately reflects the mapping model between the human body features and the human body shape space, thereby improving the accuracy and reliability of the three-dimensional reconstruction of the human body.
Owner:ZHEJIANG UNIV
Sheet metal part rectangular contour three-dimensional measurement method and system based on feature fitting
PendingCN114742853AGuaranteed accuracyGuaranteed reconstruction accuracyImage analysisUsing optical meansPoint cloudComputer graphics (images)
The invention discloses a sheet metal part rectangular contour three-dimensional measurement method and system based on feature fitting, and belongs to the field of three-dimensional measurement. According to the method, preliminary contour extraction is realized based on a sheet metal part image, a rectangular contour is detected, and approximate quadrilateral fitting is carried out; sub-pixel contour extraction is carried out, corresponding point matching is realized, and a three-dimensional point cloud is reconstructed; and constructing a three-dimensional rectangular projection fitting model based on iterative rotation, and calculating three-dimensional rectangular parameters. Compared with a traditional method of fitting rectangles after three-dimensional point cloud reconstruction based on structured light, the method can reduce the problem of reconstruction errors of contour edge parts caused by illumination variation, image noise and the like, improves contour point cloud reconstruction precision, realizes automatic recognition of contours and accurate parameter acquisition, and improves the accuracy of contour point cloud reconstruction. And the accuracy of three-dimensional measurement of the profile of the sheet metal part is
Owner:HUAZHONG UNIV OF SCI & TECH
1bit compression superposition CSI feedback method based on feature extraction and mutual anisotropy fusion
ActiveCN113726376AGuaranteed reconstruction accuracyHigh precisionRadio transmissionNeural architecturesFeature extractionAlgorithm
The invention discloses a 1bit compression superposition CSI feedback method based on feature extraction and mutual anisotropy fusion, and the method comprises the steps: obtaining the learning amplitude of corresponding downlink CSI through a first neural network according to the amplitude of an uplink CSI estimation vector; performing CSI feature extraction by utilizing expert knowledge according to a recovery feedback vector obtained by the base station, and recovering a feature amplitude and a feature angle of downlink CSI; according to a downlink CSI splicing amplitude obtained by splicing the characteristic amplitude of the downlink CSI and the learning amplitude of the downlink CSI, obtaining a fusion amplitude of the downlink CSI through a second neural network; and recovering to obtain a downlink CSI reconstruction vector according to the fusion amplitude of the downlink CSI and the feature angle. Compared with single-bit CS superposition CSI feedback, the method has the advantages that the amplitude of the downlink CSI lost by the single-bit CS can be recovered according to the bidirectional heterogeneity of the uplink and downlink channels, the reconstruction precision of the CSI is greatly improved, and meanwhile, the reconstruction efficiency of the CSI is remarkably improved.
Owner:XIHUA UNIV
Three-dimensional reconstruction method based on GPU parallel acceleration
PendingCN111899326AReduce computationFast operationImage enhancementImage analysisConcurrent computationAlgorithm
The invention belongs to the field of machine vision research, and particularly relates to a three-dimensional reconstruction method based on GPU parallel acceleration. The method mainly comprises thefollowing steps: initializing an algorithm; loading the image sequence modulated by the structured light, and copying the image sequence in the computer memory to a common memory of the GPU equipmentside in parallel; the GPU is used for carrying out background segmentation on images shot by the left camera and the right camera in parallel, three-dimensional reconstruction is only carried out onsegmented foreground targets, redundant calculation is reduced, and the calculation efficiency is improved; solving an image sequence phase principal value by using GPU parallel acceleration and carrying out phase unwrapping to obtain an absolute phase value; distortion correction is carried out on the phase unwrapped image; stereoscopic matching is carried out in a serial and parallel combined mode, that is, serial processing is carried out on local areas of an image, parallel processing is carried out between the areas, and stereoscopic matching is carried out; disparity map preprocessing; and calculating a three-dimensional point cloud according to the disparity map. According to the method, the parallel computing capability of the GPU is fully utilized, the overall computing speed of the algorithm is increased, and the application scene of three-dimensional reconstruction is expanded.
Owner:苏州小优智能科技有限公司
Regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method
InactiveCN101908230BStable matching costReduce mistakesImage analysis3D modellingObject pointReconstruction method
The invention discloses a regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method, which is implemented by the following steps: (1) shooting a calibration plate image with a mark point at two proper angles by using two black and white cameras; (2) keeping the shooting angles constant and shooting two images of a shooting target object at the same time by using the same camera; (3) performing the epipolar line rectification of the two images of the target objects according to the nominal data of the camera; (4) searching the neighbor regions ofeach pixel of the two rectified images for a closed region depth edge and building a supporting window; (5) in the built window, computing a normalized cross-correlation coefficient of supported pixels and acquiring the matching price of a central pixel; (6) acquiring a parallax by using a confidence transmission optimization method having an acceleration updating system; (7) estimating an accurate parallax by a subpixel; and (8) computing the three-dimensional coordinates of an actual object point according to the matching relationship between the nominal data of the camera and the pixel andconsequently reconstructing the three-dimensional point cloud of the object and reducing the three-dimensional information of a target.
Owner:江苏省华强纺织有限公司 +1
Multifunctional senor sample selection method based on kernel subtractive clustering
InactiveCN103196497AGuaranteed reconstruction accuracyReduce the amount of sample dataMeasurement devicesSpecial data processing applicationsWorkloadHigh density
The invention relates to sensors, and discloses a multifunctional senor sample selection method based on kernel subtractive clustering. The multifunctional senor sample selection method includes the following steps: step 1, sampling is carried out on a sensor which needs to be subjected to signal reconstruction, and sample data are obtained; step 2, the sample data obtained in the step 1 is subjected to normalization processing; step 3, the kernel subtractive clustering is used for mapping the sample data, which are already subjected to the normalization processing, to a high-dimensional space to enable the sample data to be linearly separable, and the sample data are classified; and step 4, a clustering center of each type of the sample data is used as a sample point to be selected. According to the multifunctional senor sample selection method, on the basis that the reconstruction accuracy is guaranteed, the number of the sample data which are needed for the signal reconstruction is reduced. The fact that each senor is subjected to high-density sampling is not needed, and therefore workloads which are needed for the sampling are greatly reduced.
Owner:XIAMEN UNIV
Method for rebuilding front and back oval edges of aerial blade based on error control
InactiveCN103077315BImprove reconstruction qualityAvoid Participation in FittingSpecial data processing applicationsAviationAlgorithm
The invention discloses a method for rebuilding front and back oval edges of an aerial blade based on error control, which is used for solving the technical problem of poor anti-noise performance existing in the conventional high-precision rebuilding method for a front edge of a blade. According to the technical scheme, the method comprises the following steps of: selecting region points covering the front edge or the back edge of the blade; sequencing the region points; performing spline fitting on the sequenced region points for three times; performing equal-arc-length encryption discretion on fitted spline curves, and marking beginning and end discrete points as P0i and P1i respectively; fitting discrete points at a P0iP1i section by using a least square method, and marking beginning and end discrete points on the intersection of the P0iP1i section and a fitting oval as P0(i+1) and P1(i+1) respectively; calculating an average error epsiloni ranging from the discrete points to an ith fitting oval; and setting an iteration control error as epsilon till the epsiloni is less than or equal to epsilon to finish iteration. According to the method, the front and back oval edges of the blade are rebuilt by adopting an error control-based iterative fitting method on the basis of fitting through the least square method, so that points on a non-oval circular arc in the selected region are prevented from participating in fitting, and the anti-noise performance is improved.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Image reconstruction method, device, equipment and storage medium
ActiveCN111047660BGuaranteed reconstruction accuracyImprove rebuild speedReconstruction from projectionPattern recognitionFast Fourier transform
The present application belongs to the technical field of image processing, and provides an image reconstruction method, apparatus, device and storage medium. The method obtains the sampling data of the target object; the sampling data is input into the deep learning network after training for processing, and the reconstructed image corresponding to the sampling data is obtained, wherein the sampling data is obtained based on a preset sampling mode in a non-Cartesian coordinate system. Under-sampling frequency-domain data; compared to the prior art technical solution for image reconstruction based on non-uniform fast Fourier transform on under-sampling frequency-domain data in a non-Cartesian coordinate system, the deep learning network in the embodiment of the present application undergoes image reconstruction. Pre-training can directly reconstruct the corresponding image according to the input undersampling frequency domain data in the non-Cartesian coordinate system, without manual selection / adjustment of parameters such as scale factors, which improves the undersampling frequency in the non-Cartesian coordinate system. Reconstruction speed of domain data.
Owner:SHENZHEN INST OF ADVANCED TECH
A method and device for reconstructing target electromagnetic scattering characteristic data
ActiveCN109444842BGuaranteed reconstruction accuracyImprove efficiencyWave based measurement systemsRadar imagingReconstruction method
The invention discloses a reconstruction method and device for target electromagnetic-scattering-characteristic data, and relates to the technical field of radar imaging. The method includes the stepsthat a three-dimensional echo signal model of a target is built, and the three-dimensional echo signal model is converted into a state-space equation; according to scattering echo data of the target,a generalized Hankel matrix is built, and the state-space equation is solved based on the Hankel matrix to determine a parameter estimating value of the target scattering center; according to the parameter estimating value of the target scattering center, electromagnetic-scattering-characteristic data of the target is reconstructed. Through the steps, the reconstruction accuracy of the target electromagnetic-scattering-characteristic data is guaranteed, and efficient compression and real-time loading of the full-space target electromagnetic-scattering-characteristic data can also be achieved.
Owner:BEIJING INST OF ENVIRONMENTAL FEATURES
A Fast Compression Method for Frequency-Shifted Signals of Vehicular Tracks Based on Compressive Sensing
InactiveCN103716057BReduce complexityImprove real-time performanceCode conversionReconstruction methodEngineering
Owner:CHINA RAILWAYS CORPORATION +1
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