31 results about "Edge matching" patented technology

The invention relates to the technical field of multi-image fusion recognition, in particular to a data fusion method and system for CCD visual detection, and the method comprises the following steps: obtaining a horizontal pixel row calculation gradient construction trend sequence, repairing an edge fracture to generate an integrity index, extracting a gray value to detect feature mutation, and distributing fusion weights to establish a mapping relation. And executing image fusion and balancing the contrast to generate a fusion matrix result. According to the method, the fracture edge region is identified, interpolation compensation is executed, the structural similarity index of the local gray sequence in the image overlapping region and feature direction mutation detection are combined, accurate identification of the edge matching result is guided, and fusion weight factor mapping corresponding to signal-to-noise ratio distribution is introduced; according to the method, the distribution relation between the pixels in the region and the credible weight is effectively established, the edge transition among the multi-source images is more natural through Poisson constraint and contrast balance adjustment of the fusion region, and the structural fidelity and the judgment stability of the fusion image are remarkably enhanced.

The present invention relates to the technical field of image detection, and in particular to a method for rapid detection of a fracture region in a precision-stamped part of a new energy vehicle. The method comprises: acquiring a complete stamped part grayscale image; acquiring each sub-region in the complete stamped part grayscale image; for each sub-region, taking a fitting curve of all edge pixels of the sub-region as an edge curve of the sub-region, and constructing a curvature evaluation factor between each pixel and the adjacent previous pixel on the edge curve; constructing the degree of curvature change of the edge curve; constructing a curvature sequence and a distance sequence of the edge curve; acquiring each subsequence of the curvature sequence of the edge curve; constructing the fracture edge matching degree, a local stress discontinuity index and a fracture region confidence level of the sub-region; and on the basis of the fracture region confidence levels of all sub-regions, using a clustering algorithm to cluster and delineate a fracture region. According to the present invention, the accuracy of detection of the fracture region in the precision-stamped part of the new energy vehicle can be improved.

The invention discloses a distributed urban and rural planning decision support method and system, and relates to the technical field of data analysis, and the method comprises the following steps: S100, drawing a planar graph of a to-be-planned region, dividing the planar graph of the region according to a Morse decomposition method, and constructing a region matrix, S200, calculating the coverage rate of the region matrix, and S300, calculating the coverage rate of the region matrix. And planning the surveying and mapping path. According to the method, planning units and surveying and mapping grids are unified into the same quadrilateral matrix through Morse complex, repeated zoning and edge matching errors are effectively avoided, the edge weight is inversely proportional to the building coverage rate, an unmanned aerial vehicle and a surveying and mapping vehicle automatically and preferentially encrypt a high built-up area, field working hours are saved, the data precision of a core construction area is guaranteed, and the construction efficiency is improved. The regional matrix naturally corresponds to edge nodes, and each node only communicates with an adjacent unit, so that the MST and the local route can be locally solved, the communication complexity is reduced, and the method is suitable for large-scale regional surveying and mapping.

The invention discloses an acquisition device of a background knife edge matching graph and an acquisition method of a background schlieren graph, and belongs to the technical field of schlieren imaging.The acquisition device of the background knife edge matching graph uses a transparent background particle plate as a particle background of background schlieren; and the transparent background particle plate is placed in a knife edge schlieren light path to form a fusion light path. The knife edge schlieren and the background schlieren are integrated on the same fusion light path, so that a matching graph between the background schlieren and the knife edge schlieren under a gas density disturbance flow field is acquired under the conditions of the same flow field and the same visual angle. Further, carrying out difference calculation and filtering on the image A and the image B according to pixels to remove particle ghosts, and obtaining an image D only carrying knife edge schlieren; carrying out difference calculation and particle morphology enhancement on the image A and the image D to obtain an image E only containing particle information, and then carrying out particle displacement calculation; the operation is simple, the calculation complexity is low, and the accurate background schlieren graph can be quickly obtained.

The invention provides an edge matching positioning method and system. The method comprises the following steps: acquiring a real-time image and a reference image in a sample library; inputting the real-time image and the reference image into a pre-constructed region score model to obtain a matching calculation score output by the region score model; based on the matching calculation score, performing paraboloid fitting by taking a matching peak value and a neighborhood as sampling points to obtain a sub-pixel position offset; and adding the sub-pixel position offset to the coordinate value of the current matching position to obtain a final positioning position coordinate. The technical problem that the positioning precision of edge matching calculation is low is solved.

The invention discloses a shipping accident analysis method. The method comprises the following steps: constructing a shipping accident knowledge graph; inputting questions, retrieving the shipping accident knowledge graph by adopting a retrieval enhancement generation method, and generating answers; wherein the retrieval enhancement generation method is adopted to retrieve the shipping accident knowledge graph and generate the answer, and the method comprises the following steps of: analyzing a question by adopting a large language model to generate a query statement; retrieving in the shipping accident knowledge graph according to the query statement, outputting nodes and edges matched with the query statement from the shipping accident knowledge graph, and generating a Bayesian network according to the matched nodes and edges; generating a query result according to the conditional probability of a target node and a father node thereof and / or the posterior probability of a child node thereof in the Bayesian network, and inputting the query result into the large language model; and the large language model generates an answer according to the query result. The invention further discloses a shipping accident analysis device, computer equipment and a storage medium. The method comprises the following steps: extracting and storing shipping accident data by adopting a large language model in combination with a knowledge graph, and analyzing the shipping accident data in combination with a Bayesian network analysis model to obtain an occurrence probability of a complete causal chain from causes to accident results in an accident, so that objective and accurate accident causals are sorted out for complex shipping accidents, and the probability of occurrence of the complete causal chain is improved. And reliable conclusions and suggestions are provided for subsequent shipping businesses.

The invention provides a missile carrier positioning ring assembling method and system based on vision and angle registration, and the method comprises the steps: collecting a missile carrier positioning hole region image through an industrial camera, extracting hole position geometric information after image processing, and calculating the angle of a missile carrier positioning hole column relative to a camera coordinate system; the chuck is controlled by the PLC to rotate the missile carrier, and the target hole column of the missile carrier is adjusted to be in the vertical upward direction; acquiring an image of the positioning ring, identifying asymmetric structure features to extract a main shaft direction angle, and calculating an angle difference between the missile carrier and the positioning ring; a positioning ring is clamped through a clamp at the tail end of a robot, a planning path is converted through a multi-stage coordinate system, angle pre-compensation is conducted on the positioning ring in the carrying process, the positioning ring is inserted into a missile carrier hole site through an adsorption and limiting structure, and meanwhile the insertion force and speed are adjusted based on feedback of a force / torque sensor; and after assembly, collecting a reinspection image, analyzing and evaluating the insertion depth and the boundary offset through edge matching, and judging whether the assembly is qualified or not according to a preset threshold value.

The application discloses a motor insert sheet defect detection method based on multi-sensor fusion, relates to the technical field of motor insert sheet defect detection, and comprises the following steps: in the presence of boundary penetration, calculating edge matching mismatch degree, edge jump rate, edge inversion proportion and edge closure deviation to form a geometric conflict feature set of an insert sheet edge, which is used for representing image geometric expression differences caused by boundary penetration; inputting the geometric conflict feature set into a fusion confidence evaluation function to obtain a fusion confidence evaluation factor, which is used for identifying whether the insert sheet edge has a fusion distortion risk. The application solves the structural expression conflict problem caused by boundary penetration in the multi-view imaging fusion process of the motor insert sheet, constructs a fusion confidence evaluation mechanism to identify the fusion distortion risk, dynamically limits the image participation fusion condition, and thus improves the recognition accuracy of the edge structure and the stability of the fusion result in the insert sheet defect detection.

The application discloses a shipping accident analysis method, comprising the following steps: constructing a shipping accident knowledge graph; inputting a question, searching the shipping accident knowledge graph by using a search enhancement generation method, and generating an answer; wherein the search enhancement generation method comprises the following steps: analyzing the question by using a large language model, generating a query statement, searching the shipping accident knowledge graph according to the query statement, outputting nodes and edges matched with the query statement from the shipping accident knowledge graph, generating a Bayesian network according to the matched nodes and edges, generating a query result according to the conditional probability of a target node and its parent nodes and / or the posterior probability of the target node and its child nodes in the Bayesian network, inputting the query result into the large language model, and generating an answer according to the query result by the large language model. The application further discloses a shipping accident analysis device, a computer device and a storage medium. By using a large language model combined with a knowledge graph to extract and store shipping accident data, and by using a Bayesian network analysis model to analyze the shipping accident data, the occurrence probability of a complete cause-and-effect chain from causes to results of an accident can be obtained, so that objective and accurate causes and effects of a complex shipping accident can be sorted out, and reliable conclusion opinions can be provided for subsequent shipping business.

The invention discloses an incremental mapping method and device and a storage medium, and the method comprises the steps: stopping employing a priori map for positioning if it is detected that a mobile device is out of the range of the priori map, and carrying out the positioning based on a constructed incremental map; if it is detected that the mobile device moves from the outside of the prior map range to the inside of the prior map range, starting a prior map for positioning, matching the environment perception data at the current moment with the prior map based on a branch and bound algorithm, and obtaining a matching score corresponding to a successfully matched pose; unary edge constraints are added to poses corresponding to the environment perception data with the matching scores larger than a preset score threshold value; and carrying out accumulative error optimization on the calculated pose by utilizing unary edge constraint so as to align the incremental map with the prior map. The mapping pose is restrained by adding the unary edge matched with the prior map, the alignment effect between the incremental map and the prior map can be improved, and map ghosting and faults are avoided.

The application discloses a photovoltaic array fault detection and positioning method based on bipartite graph matching, comprising the following steps: 1) based on the connection structure of a photovoltaic array, a photovoltaic array bipartite graph is established, and the connection points of components on the same photovoltaic component string constitute an independent node set in a sub-bipartite graph; 2) under the complete matching rule of the bipartite graph, the minimum edge covering rule and the constraint that equal-weight points in the bipartite graph are not connected, edge matching of the bipartite graph is derived, the edge is converted into a voltage sensor, and optimal configuration of the voltage sensor is obtained; 3) the fault voltage threshold of the photovoltaic component under different faults is calculated, the actual measured value of the photovoltaic component voltage collected by the voltage sensor is compared with the fault voltage threshold, and photovoltaic array fault detection and positioning are realized. The application realizes accurate detection and positioning of open-circuit, short-circuit, aging and shading faults of each photovoltaic component by using fewer voltage sensors, and the voltage sensor only needs to be connected between adjacent photovoltaic component strings, and is easy to operate.

The invention is suitable for the technical field of operation and maintenance management of Internet of Things equipment, and provides an Internet of Things equipment repair process management method and system and computer device.The method comprises the steps that on the basis of a directed graph structure, a repair process model comprising multiple nodes and multiple edges connected with the nodes is constructed in advance; binding an automatic task node in the repair process model with a task script, and respectively configuring circulation conditions for a plurality of edges led out from the automatic task node; when a repair request is received, creating a work order based on the repair request and starting a repair process instance; when the repair process instance flows to the automatic task node, automatically triggering and executing the task script bound with the repair process instance; and according to the received execution feedback data, a target edge with a transfer condition matched with the execution feedback data is decided in the repair process model, and the repair process instance is driven to transfer to a next node along the target edge. According to the invention, the problems of slow response and low efficiency of repair management of the existing Internet of Things equipment are solved.

The invention discloses a bipartite graph matching-based photovoltaic array fault detection and positioning method, which comprises the following steps of: 1) establishing a photovoltaic array bipartite graph based on a photovoltaic array connection structure, and forming an independent node set in a sub bipartite graph by component connection points on the same photovoltaic component string; 2) exporting edge matching of the bipartite graph under the constraints of a complete matching rule and a least edge coverage rule of the bipartite graph and unconnected medium weight points in the bipartite graph, converting edges into voltage sensors, and obtaining optimal configuration of the voltage sensors; and (3) calculating fault voltage thresholds of the photovoltaic module under different faults, collecting voltage measured values of the photovoltaic module through a voltage sensor, and comparing the voltage measured values with the fault voltage thresholds to realize fault detection and positioning of the photovoltaic array. According to the method, fewer voltage sensors are adopted, accurate detection and positioning of open circuit, short circuit, aging and shielding faults of each photovoltaic module are achieved, the voltage sensors only need to be connected between the adjacent photovoltaic module strings, and operation is easy.

The invention belongs to the technical field of surveying and mapping, and particularly relates to a multi-source digital elevation model splicing optimization method combining a third-order polynomial and a Bezier curve. The method is suitable for splicing DEM data obtained by unmanned aerial vehicle oblique photography and RTK measurement, and is especially used for solving the abrupt and discontinuous problems of heterogenous digital elevation model (DEM) data in an edge matching area due to inconsistent resolution and elevation precision. The method comprises the steps of data acquisition and conversion, grid resampling, overlapped region extraction and weighted splicing, third-order polynomial fitting processing, Bezier curve smooth correction and the like. Buffer areas are constructed on the two sides of the splicing line, a similarity threshold value is set, trend surface fitting and transition curved surface construction are guided, and the elevation continuity and the model smoothness of the splicing area are effectively improved. And finally, precision verification is carried out through a root mean square error (RMSE), and the consistency and availability of the spliced DEM in spatial expression are ensured.

A perception and map edge association system for an autonomous vehicle includes one or more controllers executing instructions to receive a plurality of perception lane edge candidates that are each representative of a perception lane edge and a plurality of map lane edge candidates that are each representative of a map lane edge. The one or more controllers identify a discrepancy between a selected perception lane edge candidate and a best fit map edge candidate for a lane characteristic based on a posterior association probability matrix and a discrepancy flag. The one or more controllers segment the pair of inconsistent perception and map lane edges into one or more matching segments. The one or more matching segments indicate where the perception lane edge and the map lane edge match one another based on the lane characteristics. The perception and map edge association system improves localization and scene creation performance.

The invention discloses a motor insert defect detection method based on multi-sensor fusion, and relates to the technical field of motor insert defect detection, and the method comprises the following steps: calculating an edge matching mismatch degree, an edge jump rate, an edge inversion ratio and an edge closing deviation under the condition of boundary interspersion, forming a geometric conflict feature set of insert edges, and calculating the edge matching mismatch degree, the edge jump rate, the edge inversion ratio and the edge closing deviation; the representation module is used for representing image geometric expression differences caused by boundary interpenetration; and inputting the geometric conflict feature set into a fusion confidence evaluation function to obtain a fusion confidence evaluation factor for identifying whether the edge of the insert has a fusion distortion risk or not. According to the method, the problem of structural expression conflict caused by boundary interpenetration in the multi-view imaging fusion process of the motor insert is solved, a fusion confidence evaluation mechanism is constructed to identify the fusion distortion risk, and the image participation fusion condition is dynamically limited, so that the identification accuracy of an edge structure and the stability of a fusion result in insert defect detection are improved.

This application discloses a method, apparatus, device, and storage medium for recognizing the edge contour of a graphic, relating to the field of machine vision technology. The method includes: image processing of an image to be recognized to obtain pyramid gradient images at different levels of the image; inputting the pyramid gradient images into a preset edge matching model to obtain a set of candidate points for the contour of a target graphic in the image to be recognized, wherein the preset edge matching model is a model trained based on sample images labeled with the target graphic using a sparse sampling method and an adaptive threshold segmentation method; and connecting the candidate points in the candidate point set to obtain the target graphic in the image to be recognized. In this application, the adaptive threshold segmentation method clearly distinguishes the contour of the target graphic from the contours of other graphics, and the sparse sampling method reduces the number of candidate points obtained. Therefore, the preset edge matching model can obtain a small number of accurate candidate points, thereby improving the accuracy of recognizing the target graphic using the matching method.

The invention provides a road surface target identification method and system based on Hough transformation, and the method comprises the steps: obtaining an edge image of a target image and an edge image of a to-be-matched image, and carrying out the generalized Hough transformation of the edge image of the target image and the edge image of the to-be-matched image; establishing a mapping table of the edge image of the to-be-matched image; initializing a matching area confidence accumulator according to the size of the edge image of the target image; traversing the edge points of the edge image of the target image, calculating the position of each possible image to be matched according to the edge angle, and adding 1 to the confidence accumulator; a plurality of local maximum values in the target area are obtained through matching parameter space searching, and each local maximum value corresponds to one road surface target in the target area. Edge matching replaces an existing surface matching algorithm, the calculation amount in the recognition process is reduced, and the accuracy of road surface target recognition is improved.

The invention discloses an urban three-dimensional model data generation method, an urban three-dimensional model data generation device, urban three-dimensional model data generation equipment and a computer readable storage medium, and the method comprises the steps: carrying out the construction processing of a three-dimensional model based on obtained oblique photogrammetry data, and obtaining first urban three-dimensional model subdata; performing three-dimensional model construction processing outside the range of the oblique photogrammetry data based on the high-resolution satellite stereoscopic image to obtain second urban three-dimensional model sub-data; and performing edge matching processing on the first urban three-dimensional model sub-data and the second urban three-dimensional model sub-data based on a geometric continuity principle, a texture consistency principle and an attribute uniformity principle to obtain urban three-dimensional model data. Multi-source data are efficiently integrated, and global modeling precision and efficiency are improved.

The invention discloses a spatio-temporal interpolation neural network model and a spatio-temporal data modeling method based on the spatio-temporal interpolation neural network model, relates to the technical field of spatial interpolation, and aims to accurately model spatial dependence by introducing an embedded layer of spatial coordinates and a spatio-temporal basis function so as to establish a direct relation between DNN and Kriging spatial prediction. By means of a deep neural network structure, the model can automatically extract features in large-scale and dynamically-changing spatial data, and effectively identify a nonlinear relationship between spatial points, thereby realizing more accurate spatial interpolation. The method is not only suitable for non-linear prediction with covariables, but also can process non-Gaussian or non-stationary data, and greatly improves the applicability and robustness of the model. Besides, the deep learning model is excellent in performance on solving the local grid edge matching problem, the edge matching area can be smoothed, and the accuracy and reliability of gridding processing are improved.

The application relates to the technical field of image change detection, in particular to a low-altitude unmanned aerial vehicle video frame extraction and orthographic image change detection method based on deep learning, which is characterized in that unmanned aerial vehicle video is acquired to perform frame-by-frame semantic segmentation and grid feature extraction, adjacent frame grid distribution is compared to screen change-related frames, spatial mapping of the change-related frames and orthographic images is constructed through edge matching, images are spliced according to positions and edge transition processing is performed to generate a continuous sequence, finally, new and old image ground categories are compared based on a geographic coordinate system, and video frame extraction and image change detection results are output. According to the application, grid time sequence description based on ground semantics is introduced, change recognition is converted into category evolution analysis with semantic meaning, key space-time regions with attribute transfer are focused, continuous image organization under a unified geographic reference is combined, content space continuity is ensured, result time sequence direction and spatial certainty are strengthened, and expression stability and explanation clarity of patrol change information are improved.

The invention discloses a multi-dimensional edge matching load identification method based on electricity utilization acquisition and breadth search, relates to the related field of load identification technologies, and aims to solve the core problem that the accuracy of power event detection and load state identification is seriously insufficient in the prior art. The method comprises the steps of firstly defining a load type, then dividing power slow change and sudden change by using first-order and second-order difference regions, extracting multi-dimensional edge features, designing a dynamic threshold adjustment mechanism, realizing multi-dimensional breadth-first search matching of a rising edge and a falling edge, and simultaneously extracting multi-dimensional load features to distinguish similar loads. And the load electricity consumption is planned and distributed in real time according to the breadth-first search result, and a set of full-flow technical scheme from power signal detection to load identification and energy consumption metering is formed. Accurate detection of a power event and effective identification of a full working state of a load are realized, the overall accuracy of non-intrusive load identification is improved from a core link, and a foundation is laid for subsequent load decomposition and accurate energy consumption metering.

The invention discloses a transportation time determination method and electronic equipment, and the method comprises the steps: determining a target time-space sub-graph in a target graph based on the logistics feature information of a to-be-predicted target order; the target graph comprises at least one time-space sub-graph, each time-space sub-graph has an order corresponding to the time-space sub-graph, and the order represents a backtracking dimension of historical order data contained in the time-space sub-graph; determining a causal edge target weight of a causal edge matched with the target order in each target time-space sub-graph based on the target time-space sub-graph, and an order fusion weight corresponding to the target time-space sub-graph; and determining the target transportation time of the target order based on the reference transportation time parameter corresponding to the causal edge matched with the target order, the causal edge target weight and the order fusion weight.

The invention relates to the technical field of crossing of computer graphics, geographic information technology, digital twinning and intelligent traffic, and discloses a multi-source three-dimensional geographic information data fusion method and system, and the method comprises the steps: obtaining an oblique photography surface model to be fused, a fine three-dimensional structure model and a digital elevation model; obtaining a live-action model and a terrain model which are spatially aligned; respectively determining a first edge matching area and a second edge matching area based on the outline and the spatial position of the fine three-dimensional structure model; performing driving reconstruction related to the fine three-dimensional structure model on the terrain model; transitional deformation related to the fine three-dimensional structure model is carried out on the real scene model so that the deformed real scene model can be smoothly connected with the fine three-dimensional structure model in the second edge matching area; and integrating the fine three-dimensional structure model, the deformed real scene model and the reconstructed terrain model. According to the method, the seamless effect in the true geometric sense is achieved, and a reliable geometric foundation is laid for high-precision engineering application.

The present application belongs to the field of optical imaging, and proposes a kind of 2pi space imaging implementation method based on image information edge matching and splicing.Utilize the camera internal and external parameters obtained by scaling, adopt coordinate matrix transformation to correct image distortion, realize cylindrical projection by camera imaging geometric relation inversion.Find the coincident part of two pictures, quickly and accurately complete similar point extraction and matching.Use coordinate conversion to splice all processed images.Estimate the gray scale of non-integer coordinate values in original coordinates by bilinear interpolation method, and realize the smooth transition between the brightness of two images by fading-in and fading-out method.The present application is suitable for the splicing of near distance panoramic image in 2pi space.

The application discloses a background knife-edge matching image acquisition device and a background schlieren image acquisition method, and belongs to the technical field of schlieren imaging. The background knife-edge matching image acquisition device uses a transparent background particle plate as a particle background of a background schlieren image, and places the transparent background particle plate in a knife-edge schlieren light path to form a fusion light path. The knife-edge schlieren image and the background schlieren image are integrated on the same fusion light path, so that the matching image between the background schlieren image and the knife-edge schlieren image under the same flow field and the same visual angle condition of a gas density disturbance flow field can be collected. Further, the image A and the image B are subjected to pixel difference value calculation and filtering to remove particle residual images, so as to obtain an image D which only carries the knife-edge schlieren image; the image A and the image D are subjected to difference value calculation and particle morphology enhancement to obtain an image E which only contains particle information, and then particle displacement calculation is performed; the operation is simple, the calculation complexity is low, and the accurate background schlieren image can be quickly obtained.

The invention discloses a fine stereo matching method. The method comprises: obtaining original left and right views; an original foreground edge enhanced stereo matching network model is constructed and initialized; training the original foreground edge enhanced stereo matching network model; and inputting a left view and a right view of a pair of actual scenes into the foreground edge enhanced stereo matching network model, and outputting a corresponding high-precision disparity map. The method has the advantages that foreground edge matching precision is remarkably improved, parallax probability distribution is adaptively corrected through a peak value parallax encoder, multi-peak and full-band information is fused, and an initial parallax image is clearer and more accurate at the object contour. The parallax refinement capability and the network generalization are enhanced; a negative domain feature attention module retains negative domain information through Leaky ReLU; and through a multi-scale layered attention module, foreground details in the context are accurately captured and enhanced, and the adaptive capacity and generalization performance of the model in different scenes are improved. And the calculation overhead is small, and the reasoning time of the network cannot be remarkably increased.

The invention discloses a task connection graph generation method and device, equipment, a storage medium and a product, and the method comprises the steps: adding virtual nodes in a directed task connection graph of a to-be-processed task according to an obtained error task connection, and correcting the connection relation between the nodes in the graph; therefore, the directed task connection graph does not have an edge matched with the wrong task connection, and the accuracy of the directed task connection graph is improved.

The invention discloses a method for improving large-area DSM precision through control points. The method comprises the steps of overall terrain correction and overall plane and elevation precision improvement. Dividing the target area into regular grids, counting control points in each grid, and determining the elevation correction amount of each grid according to the number of the control points in each grid and the relationship between the longitude and latitude ranges of the control points and corresponding thresholds; carrying out iterative updating on the obtained elevation correction quantity of the grid with the effective elevation correction quantity, and obtaining the elevation correction quantity of the corresponding grid after iterative updating; and on the basis of the elevation correction of the corresponding grid after iteration update, calculating the elevation correction of each row and column of the grid by bilinear interpolation by taking the center of each grid as a reference so as to update the whole DSM. The method has the advantages that on the basis of overall correction, the strategy of combining block processing and iterative correction is adopted, the correction precision can be improved, and meanwhile it can be guaranteed that no edge matching trace caused by block exists in the corrected large-area DSM.