26 results about "Digital surface" patented technology

This invention relates to the field of laser processing technology, and discloses a method and system for femtosecond laser three-dimensional surface processing based on adaptive optics. The method includes: spatial topology reconstruction of the original point cloud data of the workpiece to be processed to obtain a three-dimensional digital surface; row spacing planning and optimization of the three-dimensional digital surface to obtain a spatial processing trajectory, and point wavefront mapping of the spatial processing trajectory to obtain pre-compensated phase distribution data; optical field distortion analysis of the surface reflected light signal of the workpiece to be processed to obtain the actual wavefront phase; encoding the pre-compensated phase distribution data into an initial wavefront control command for a beam shaping device, and iteratively optimizing the initial wavefront control command to obtain a wavefront supplement signal; and updating the spatial processing trajectory by combining the real-time contour data of the workpiece to be processed. This invention can improve the efficiency of femtosecond laser three-dimensional surface processing based on adaptive optics.

The application relates to a stereo matching and disparity map optimization method based on adaptive smooth constraint, which comprises the following steps: acquiring satellite stereo pairs and refined rational polynomial coefficients; processing the satellite stereo pairs and the rational polynomial coefficients by adopting a core line resampling method based on orthographic correction to generate core line image pairs; performing stereo matching on the core line images by adopting a semi-global matching algorithm based on adaptive parameters to generate an initial disparity map; performing optimization processing on the initial disparity map by using an improved weighted least square algorithm to obtain a final disparity map; and generating point clouds by spatial forward intersection based on the final disparity map, performing gridding processing on the point clouds, and acquiring a final digital surface model. Compared with the prior art, the application realizes the balance between noise suppression and detail reservation, thereby improving the accuracy and completeness of the DSM.

The application relates to a low-altitude signal coverage prediction method and system based on spherical non-uniform sampling, wherein the method comprises the following steps: determining the region complexity of different regions according to a digital surface model graph, constructing a direction sampling weight function according to the region complexity and an antenna directional diagram gain; performing spherical non-uniform sampling on a unit sphere based on the direction sampling weight function to generate a ray direction set matched with the sampling weight; calculating the spherical solid angle corresponding to each sampling direction based on the ray direction set, calculating the transmission power corresponding to each ray according to the spherical solid angle and a base station antenna directional diagram; taking the ray direction set and the transmission power as inputs to perform ray tracking propagation calculation to obtain the received signal power of each sampling point at low altitude, and the low-altitude signal coverage prediction is completed. The problems of how to improve the efficiency and accuracy of low-altitude signal coverage prediction in the related art are solved.

This invention discloses a three-dimensional terrain construction method based on multimodal semantic constraints, belonging to the field of three-dimensional terrain modeling technology. This method acquires optical remote sensing images and digital surface models and constructs unified spatial reference data. Guided by multimodal semantic constraints, it performs joint semantic parsing of ground features to generate a set of semantic masks with structural consistency. Furthermore, based on the mapping relationship between semantic categories and surface physical attributes, it performs regional geometric reconstruction of the digital surface model to form three-dimensional terrain entities that conform to the spatial expression characteristics of ground features. Simultaneously, by parsing engineering cost documents and extracting spatially oriented engineering cost data, under spatial and semantic consistency constraints, it associates and maps engineering cost information with three-dimensional terrain entities, ultimately forming a three-dimensional terrain data result that integrates terrain geometric information and engineering economic attributes.

The present application provides a kind of open-pit mine step line high-precision extraction method, device and electronic equipment, wherein the method comprises: using Gaussian filter and bilateral filter to carry out denoising processing to the target model of open-pit mine;The target model includes digital surface model, digital elevation model;The second derivative of the target model after denoising is calculated, and the initial discrete points of step line are extracted based on the second derivative;The initial discrete points of step line are corrected, and the step line discrete points obtained by correction are split to obtain the step line discrete point set of different height steps;Each step line discrete point in the step line discrete point set is sorted and smoothed, and the target step line is connected to obtain. By the present application, the open-pit mine step line is extracted with high precision and automation, and the problem of weak anti-interference ability and low extraction precision in the existing related technology is solved.

The application provides a flue-cured tobacco plant height measurement method and device based on unmanned aerial vehicle cooperation and electronic equipment, and belongs to the field of agricultural technology.The method comprises the following steps: determining digital surface model information of a to-be-measured flue-cured tobacco field based on an image of the to-be-measured flue-cured tobacco field; the image of the to-be-measured flue-cured tobacco field is obtained by splicing images of different tobacco field regions collected by an unmanned aerial vehicle; determining digital elevation model information of the to-be-measured flue-cured tobacco field based on the digital surface model information; and determining the plant height of each flue-cured tobacco plant in the to-be-measured flue-cured tobacco field based on the digital surface model information, the digital elevation model information and the tobacco field ridge height.The application can quickly calculate the plant height of each flue-cured tobacco plant in the to-be-measured flue-cured tobacco field, has the advantages of strong objectivity, high timeliness, rapid response and the like, and is low in cost, so that only a small amount of manpower is needed to realize full-coverage accurate monitoring of the plant height of flue-cured tobacco at the level of hundreds of mu and thousands of mu.

This application discloses a multi-mode fusion method and system for calculating canopy height in fields and orchards, belonging to the field of agricultural remote sensing and precision agriculture monitoring technology. It utilizes an unmanned aerial vehicle (UAV) platform equipped with a lidar sensor, a multispectral sensor, and a pose acquisition module to simultaneously collect lidar point cloud data, multispectral image data, and timestamped pose data. Based on the pose data, spatial registration and stitching are performed on the point cloud data to generate a 3D point cloud model of the crop; geometric correction and stitching are performed on the multispectral image data to generate a multispectral orthophoto. The two are unified to the same geographic coordinate system to establish a spatial mapping relationship; spectral indices are calculated based on the multispectral orthophoto to identify land cover categories and regions; corresponding subsets of the point cloud are extracted based on the spatial mapping relationship to generate a digital surface model and a digital ground model; and canopy height is calculated by the difference. This application integrates multi-source data to achieve automated and high-precision calculation of canopy height for crops such as corn and fruit trees, and has strong applicability.

The application relates to the field of low-altitude inspection, and discloses a river obstacle monitoring and identifying method based on a millimeter wave radar, which is used for improving the real-time performance and robustness of river obstacle monitoring. The method comprises the following steps: collecting millimeter wave radar original intermediate frequency data and high-overlap-rate aerial image streams synchronously to generate a multi-source data set; filtering water surface clutter by using a distance-Doppler spectrum, extracting a strong scattering target, and calculating a spatial coordinate to generate an effective target point cloud; selecting an elevation peak point as a rigid control point through a geographic grid, and combining with aerial triangulation calculation to generate a river correction digital surface model. The application adopts a hard-wired synchronous trigger mechanism to ensure the space-time alignment of the multi-source data, optimizes the stability of the elevation control point through neighborhood density checking and anisotropic weighted adjustment, and outputs a monitoring result including the position, height and projected area of the obstacle, so that the real-time performance, accuracy and robustness of the river obstacle monitoring are significantly improved.

The application discloses a kind of mine subsidence monitoring methods based on unmanned aerial vehicle photogrammetry and LiDAR technology, utilize unmanned aerial vehicle to carry out flight shooting to mining area, obtain mining area surface image data;Image data obtained is handled by motion recovery structure algorithm SfM, generates digital surface model DSM, orthophoto map DOM and digital elevation model DEM;Utilize airborne LiDAR system to scan mining area, obtain the three-dimensional point cloud data of mining area surface;Differential GNSS technology is used to correct and precision improvement to LiDAR point cloud data;The digital elevation model DEM generated by unmanned aerial vehicle photogrammetry is fused with the registration of corrected LiDAR point cloud data in unified coordinate system;Fused data is handled and analyzed, constructs mining area subsidence model, realizes the dynamic monitoring of mining area surface subsidence condition.The application effectively solves the problems existing in the traditional mining area subsidence monitoring method, provides strong technical support for mine geological disaster prevention, ecological environment protection and mining area sustainable development.

The application provides a method and device for determining the deformation of an open-pit mine dump based on time-series InSAR technology, which aims to effectively fuse continuous multi-period observations, eliminate the interference of surface elevation on SAR interference phase, and improve the determination accuracy of the deformation of the open-pit mine dump. The method comprises the following steps: obtaining SAR satellite images and a digital surface model of a target area in a preset period; constructing a plurality of multi-master image differential interference queues based on the SAR satellite images; calculating differential interference phases based on the plurality of multi-master image differential interference queues and the corresponding digital surface model, and obtaining unwrapped phases after atmospheric filtering processing by combining a singular value decomposition method; and calculating the deformation of the target area based on a sequential adjustment method, wherein after constructing an error estimation matrix containing elevation errors and unwrapped phases, the sequential adjustment method is used to obtain a velocity matrix corresponding to the time-series phase by using the error estimation matrix, and the deformation of the target area is calculated based on the velocity matrix.

This invention provides a geological disaster monitoring method and system based on UAV vision and target collaboration, belonging to the field of disaster monitoring technology. The method includes: acquiring geological images at different times; performing terrain modeling based on the geological images and target locations to obtain a digital surface model; identifying vegetated and bare areas based on the geological images; constructing a Delaunay triangulation based on targets in the vegetated areas to calculate vegetation displacement; calculating bare land displacement based on the digital surface model; fusing vegetation and bare land displacements using thin-plate spline functions to obtain global displacement information; detecting cracks using an improved Canny-Zernike operator based on the digital surface model and identifying crack skeleton lines using a morphological thinning algorithm; and modeling displacement gradient tensors based on crack skeleton lines and global displacement information to construct a crack opening distribution map and obtain monitoring results. This invention creatively combines physical noise reduction, intelligent fusion, and precise analysis to achieve high-precision positioning in harsh environments.

This disclosure relates to the field of data processing technology, and provides a method, apparatus, storage medium, and computer device for digital terrain model reconstruction. The method includes: acquiring a training dataset; constructing a multi-stage progressive reconstruction network and training the network using the training dataset to obtain a trained multi-stage progressive reconstruction network; the multi-stage progressive reconstruction network includes multiple cascaded reconstruction stages; acquiring high-resolution optical images and low-resolution digital surface models, and inputting these images and models into the trained multi-stage progressive reconstruction network; and performing progressive upsampling and residual refinement processing on the high-resolution optical images and low-resolution digital surface models of the area to be reconstructed through multiple cascaded reconstruction stages to obtain a digital terrain model of the target resolution. This embodiment achieves stable enhancement of terrain structure at multiple resolutions and high-quality generation of high-resolution digital terrain models.

This application relates to a multi-purpose method, apparatus, and computer device for extracting building floor counts. The method includes: acquiring building vector data, real-scene 3D data, and digital elevation model data of a target area; generating a digital surface model of the target area based on the real-scene 3D data; constructing a 3D data scene; generating verification floor count data of the target area based on the digital surface model and the digital elevation model data; generating standardized elevation views of each standardized elevation view using a multi-view acquisition strategy; and statistically analyzing the floor count data of the target area using a multimodal large model based on the standardized elevation views; and generating a target building floor count result for the target area based on the verification floor count data and the statistical floor count data. This method can improve the dynamic acquisition accuracy of large-scale building floor counts.

The present invention discloses a method for processing urban rainstorm waterlogging simulation data based on distributed computing, which includes the following steps: uploading a digital surface model to a control node server, the control node server splitting the digital surface model into data chunks with the same number as the computing node servers according to the number of computing node servers, and distributing N data chunks to N computing node servers for processing; the computing node servers completing simulation calculations according to the rainstorm waterlogging model tool and feeding back the results to the node server; the control node server summarizing and completing the fusion and splicing of the rainstorm waterlogging simulation results according to the processing results of each computing node server. The present invention overcomes the problem of high time consumption of massive geographical data in the application of urban rainstorm waterlogging simulation and calculation, utilizes the rich computing resources provided by the computer cluster, realizes the parallel preprocessing of geographical data and the collection of calculation results, and solves the most time-consuming calculation link in waterlogging simulation.

The disclosure includes a system and method for determining a three-dimensional (3D) structure from an image including receiving, using one or more processors, a digital surface model (DSM) image; receiving, using the one or more processors, a non-DSM image; outlining, using the one or more processors, a structure in the non-DSM image; and determining, using the one or more processors, a set of features based on the DSM image.

The present application relates to the technical field of remote sensing information extraction and flood control safety supervision, in particular to a riverway inside obstructing flood discharge forest and high-stalk crop identification method based on deep learning technology, which utilizes the front view, rear view and normal view three-line array stereo image pair data obtained by optical stereo mapping satellite in the riverway management range, constructs high-precision digital surface model through aerial triangulation and image matching procedures. The present application fuses stereo image pair image and spaceborne laser radar data, constructs deep unbalanced regression deep learning network model, realizes automatic identification and spatial distribution monitoring of riverway inside obstructing flood discharge forest and high-stalk crop, utilizes the digital surface model generated by optical stereo image pair and the discrete canopy height information obtained by spaceborne laser radar, combines the multi-scale spatial feature extraction and nonlinear regression ability of deep network, realizes seamless expansion from discrete laser point height to continuous canopy height plane, and improves the spatial continuity and precision of high-stalk vegetation identification result.

This invention discloses a risk-driven, air-ground collaborative hierarchical inspection method for large-scale linear archaeological sites. The method includes aerial acquisition of imagery and point cloud data of the linear archaeological site to be inspected, generating a digital surface model; calculating the risk value of each cell in the digital surface model based on at least one of topographic, structural, material, and environmental indicators; determining ground detection candidate areas based on the risk values; then performing accessibility scoring on the ground detection candidate areas and generating a detection task sequence based on the scoring results; and having a ground detection device arrive at the points sequentially according to the detection task sequence. Through pose-synchronized back-projection voxelization and fusion of multi-source surface features, a three-dimensional convolutional neural network is driven to achieve accurate detection of internal cavities within the archaeological site. This application overcomes the problems of fragmented surface observation and internal detection, inefficient resource scheduling, and high maintenance costs of three-dimensional models in traditional inspections, thus forming a scalable, reusable, and sustainably updated digital twin inspection framework for archaeological sites.

The application discloses a kind of satellite image digital surface model automatic construction method considering untextured water area, belong to photogrammetry and remote sensing technical field.The application includes: automatic data preprocessing, generates epipolar image pair;Adaptive stereo matching processing, initial digital surface model is generated by block pyramid matching and domain adaptive calibration;Water area intelligent optimization, state analysis is carried out to water area region, water surface dynamic type is determined and modeling strategy is dynamically selected, error closed loop correction mechanism is introduced, error source is traced back reversely and is locally corrected.The application realizes the dynamic adaptation of water area modeling, cross-domain generalization and self-correction, solves the problem that the precision of existing method decreases and matching fails due to domain offset in complex scenes such as wave water surface and inclined water surface, significantly improves the precision and automation degree of digital surface model of untextured water area, and can be widely applied in digital twin, urban planning, water conservancy monitoring and other fields.

This invention discloses an automatic method and system for generating 3D white models of buildings based on multi-source satellites. The method includes: acquiring dual-line array stereo image data and laser altimetry data of a target area to form a stereo observation dataset; fusing the processed dual-line array stereo image data and laser altimetry data; automatically identifying and finely extracting the roof outline of each building within the target area and outputting it as vector polygon data; extracting the vector outline of each building and performing spatial analysis on the digital surface model; and using the difference between its corresponding top elevation and bottom elevation as the building height to form a 3D white model dataset of buildings in the target area. This method achieves automated, high-precision, and robust extraction of building outlines and heights, automatically generating structurally complete and semantically rich city-level 3D white models, and enabling rapid, accurate, and large-scale acquisition of large-scale urban 3D information.

This invention discloses a method, system, storage medium, and product for unmanned vehicle (UAV) path planning in field environments under UAV collaboration, belonging to the field of UAV path planning, and solving the problem of low data accuracy in the global path planning of UAVs in existing technologies. This invention acquires a top-down visible light image of the passable area and performs image pose calculation and sparse point cloud data generation; then generates a two-dimensional orthophoto and digital surface model of the passable area; a semantic segmentation model performs semantic segmentation on the two-dimensional orthophoto and extracts ground feature classification data; after gridding the digital surface model and ground feature classification data, slope values ​​and ground feature classification values ​​are calculated; based on the slope value and ground feature classification value of each grid cell, the passage cost of each grid cell is calculated; the starting and ending coordinates of the UAV are input, and UAV path planning is performed based on the path planning algorithm and the obtained passage cost map. This invention is used for UAV-collaborated path planning in field environments.

The application relates to the technical field of image processors, and discloses a tumor incisal edge design method based on a skin local image. The method comprises the following steps: establishing a global space coordinate system associated with the skin of a patient; collecting a local image and a six-degree-of-freedom pose by using a handheld device integrated with a pose tracking function; projecting and fusing the image to a digital surface model in real time to generate a panoramic image; segmenting a tumor boundary by using a deep learning model, and generating a safe incisal edge path by outward expansion based on a geometric algorithm; and finally projecting the incisal edge to the skin surface in the form of structured light by using a built-in projection unit of the device. The application realizes high-precision and low-delay dynamic planning and visualized guidance of the tumor incisal edge, and improves the precision and efficiency of the operation.

This application relates to a method, system, electronic device, and storage medium for component analysis of printed circuit boards. The method may include: acquiring a digital surface image of the printed circuit board under test; inputting the digital surface image into a component recognition and segmentation model for recognition and segmentation processing to obtain physical attribute information corresponding to multiple electronic components; selecting a target electronic component from the multiple electronic components; determining the spatial layout relationship between the target electronic component and at least one associated electronic component within a preset neighborhood based on the spatial coordinate information of the target electronic component; and matching the functional semantic label of the target electronic component from a preset circuit function knowledge base based on the type information of the target electronic component and the corresponding spatial layout relationship. According to the technical solution provided in this application, high-precision, pixel-level perception of all components on the PCB surface is achieved, avoiding the missed detections or misjudgments caused by traditional AOI relying solely on template matching.

The application relates to the technical field of image processing, and discloses a target detection land illegal land use identification method based on unmanned aerial vehicle images. The method performs spectral difference processing and elevation change detection processing on historical legal land use data corresponding to a target area, a digital orthographic image map and a digital surface model to obtain a suspected change area set. Finally, the suspected change area set is input into a target illegal land use identification model to obtain an identification result. The target illegal land use identification model comprises a backbone network, a neck network and a detection head connected in sequence. The backbone network is obtained by retaining the first level to the fourth level of an original backbone network in a YOLOv8-P2 model and leading out a high-resolution branch at the second level. The neck network is obtained by replacing an original neck network in the YOLOv8-P2 model with a pruned one-way feature pyramid network. The detection head is obtained by replacing an original detection head in the YOLOv8-P2 model with multiple parallel sub-detection heads. In this way, the detection accuracy of illegal land use can be improved.

The invention relates to a computer-implemented method, a system and a computer program product for supporting preoperative planning of placement of a dental implant in a patient's jaw. A dental axis representation, a dental crown representation and / or an implantation axis representation is generated using a provided digital 3D surface visualization, e.g. a digital plaster model, at least part of the existing dental crowns and / or the oral mucosa of the patient and statistical parametric 3D shape models (SSM). This is done based on the digital 3D surface visualization and the corresponding statistical parametric 3D shape model. In addition, the method, system and computer program product can also be used to generate a corresponding statistical parametric 3D shape model. For a plausibility check, the determined representations for the tooth axis, crown and / or implantation axis can be displayed in an additionally recorded 2D X-ray image, e.g. an orthopantomogram.