285 results about "Quadtree" patented technology

The invention belongs to the technical field of image processing, and particularly relates to a monitoring image defogging enhancement method in a high-dust environment of a mineral separation site, which comprises the following steps of: performing smooth denoising on an original image by using weighted guided filtering, and obtaining global atmospheric light through a quadtree subdivision method; constructing a same-color heterogeneous discrimination index combining a spectrum similarity factor and a texture confidence factor for distinguishing dust and ore with similar colors; calculating a pixel-level dynamic defogging coefficient based on the discriminant index, and obtaining an adaptive transmissivity in combination with dark channel prior; and finally, restoring the image by using an atmospheric scattering model and carrying out contrast-limited adaptive histogram equalization processing. According to the method, the problem of misjudgment caused by the fact that the colors of the ore and the dust on the ore dressing site are similar is effectively solved, powerful defogging of the dust area and detail reservation of the ore area are achieved, and the definition and the contrast ratio of the monitoring image are improved.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention discloses an image edge feature enhancement correction fusion method based on a guide filter, and aims to solve the problems that detail features of a low-illumination visible light image and an infrared image are not obvious, focusing edge information is not clear, and registration of a multi-focus image is wrong. The invention provides an edge feature enhancement correction fusion method based on a guide filter. In the illumination enhancement stage, a visible light image is divided into a base layer and a detail layer through a guide filter, and the image contrast and detail information are enhanced. For an infrared image, an infrared background is reconstructed by using a quadtree decomposition and Bezier interpolation method, unclear focusing edge feature information is extracted, and the visibility of image details is enhanced. And finally, reconstructing the two processed images by using a multi-scale weighted gradient method, and performing fusion by calculating large-scale and small-scale weight scales.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention belongs to the field of unmanned aerial vehicle (UAS) traffic management (UTM) and computer science, and particularly relates to a method and system for airspace modeling and path planning of a logistics unmanned aerial vehicle, and the method comprises the steps: S1, receiving multi-source data, and constructing a hierarchical mixed data model; s2, coding the control constraint data and the dynamic environment data into semantic attributes of nodes in a two-dimensional quadtree layer and / or voxels in a three-dimensional octree layer so as to generate a semantic airspace model containing computable rules; s3, based on the semantic airspace model, executing a hierarchical path planning algorithm to determine a flight path from the starting point to the ending point; and S4, combining the refined paths, and outputting a four-dimensional flight path containing a timestamp. The airspace rule is internalized into the model attribute, the real-time performance, safety and compliance of path planning are remarkably improved, the airspace resource utilization efficiency is improved, and key technical support is provided for large-scale urban unmanned aerial vehicle logistics operation.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention discloses a seepage field adaptive analysis method and device based on a flexible polygon unit, and the method comprises the steps: dividing the polygon unit into a plurality of sub-regions, and constructing an internal water head field of each sub-region; recognizing a free water surface according to water head features extracted from the internal water head field of each sub-region; if the free water surface is recognized for the first time at present, or the error of the positions of the free water surfaces recognized by two adjacent rounds of iteration does not meet a preset condition, quadtree decomposition is carried out on the free water surface to obtain new sub-regions; returning to the step of extracting the water head features according to the internal water head field of each sub-region until the error of the positions of the free water surfaces identified by two adjacent rounds of iteration meets a preset condition, and obtaining a grid division result of the polygon unit; and performing seepage field analysis on the polygon units based on a grid division result to obtain a seepage field analysis result. According to the method, the complex seepage field is accurately simulated, and the optimal balance between high-precision discretization near the free water surface and the overall calculation efficiency is realized.

The invention discloses a three-dimensional model wall thickness measuring method, device and equipment combining a ray method and a spherical surface method, and a storage medium, and is applied to the field of three-dimensional models. Processing the input three-dimensional model by adopting a self-adaptive subdivision algorithm of a quadtree to generate an optimized triangular mesh; the method comprises the following steps: constructing an axial alignment bounding box (AABB) hierarchical tree structure optimized based on a superficial area heuristic (SAH) cost function, and in a wall thickness calculation stage, combining the advantages of a ray method and a spherical method: performing dynamic judgment according to an included angle between a normal vector at an intersection point of a ray and the inner surface of a model and an initial ray direction; the hybrid strategy ensures that reliable and efficient measurement results can be obtained in different geometric feature regions; a visual distribution diagram of color coding can be generated; according to the method, through adaptive grid optimization, efficient SAH-AABB acceleration and ray / spherical surface method mixed measurement, high-precision and efficient global measurement of the wall thickness of any three-dimensional model, especially a complex structure model, is realized.

The invention provides a dynamic grid updating and scheduling method and system for watershed scale ecological restoration. The system comprises a data fusion access module, a dynamic grid generation module and a central cooperative controller. The data fusion access module is used for receiving multi-source heterogeneous data, the dynamic grid generation module is used for constructing an initial watershed grid by adopting a quadtree space division algorithm based on the multi-source heterogeneous data, and the central cooperative controller is used for periodically scanning a full-watershed grid set. Comprehensively judging information value density and updating urgency of each grid according to a multi-dimensional index; by adopting the above technical scheme, the autonomous evolution and precise adaptation of the watershed spatial discretization unit can be realized, the global monitoring breadth and the local description precision are dynamically balanced, and the response sensitivity to an emergent ecological event is improved.

The invention relates to the technical field of capacitive touch, and discloses a capacitive touch signal self-adaptive compensation method and device. The method comprises the following steps: collecting original capacitance signal grid data in an initial contact stage, and constructing a dynamic contact quadtree; on the basis of the quadtree, a first point position prediction algorithm of contact dynamics perception is operated, and stable coordinate prediction mapping with confidence is constructed; and executing multi-mode first point decision and touch event generation based on the mapping, outputting a touch event and feeding back the touch event to an operating system. According to the method, initial contact signal features are captured through the dynamic contact quadtree, stable coordinate prediction mapping and multi-modal decision are combined, the problem of jumping coordinates in the initial touch stage of an existing system is solved, the touch accuracy of scenes such as vehicle-mounted center control and industrial HMI is improved, the operation risk is reduced, and the application value of the capacitive touch technology is expanded.

The invention relates to the technical field of mobile robot autonomous navigation path planning, and discloses a complex orchard scene-oriented hybrid sampling global path planning method, which comprises the steps of adopting a Gaussian hybrid sampling strategy, switching between global uniform sampling and Gaussian offset sampling through a probability threshold, and considering global exploration and key area guidance; a dynamic node expansion strategy is adopted, the expansion step length is adaptively adjusted according to the distance between the expansion step length and a target point, and the expansion direction is optimized by fusing vectors facing a sampling point and the target point and introducing an obstacle influence factor; a layered collision detection strategy is adopted, and step-by-step filtering is carried out through rough detection based on a quadtree, secondary screening based on an axis alignment bounding box and accurate geometric judgment in sequence so as to improve the efficiency; and a dynamic iteration termination mechanism is adopted, and the minimum number of iterations and the path quality convergence state are combined as composite termination conditions. The method can quickly generate a smooth and safe path, and is especially suitable for structured scenes such as orchards.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention provides a low-delay high-performance image semantic-channel joint coding system, and relates to the technical field of communication and image processing, and the method comprises the steps that a sending end extracts semantic features through a neural analyzer, and divides the semantic features into a plurality of partitions through a quadtree structure; and coding each partition step by step by using a context-aware feature coding strategy, and finally mapping to a complex value channel symbol to be sent to a receiving end. And a receiving end reconstructs the semantic features through a corresponding decoding and synthesizing module and generates a reconstructed image, so that end-to-end efficient image transmission is realized. According to the method, a context-based partition coding mechanism and a quadtree partition module strategy are introduced into a coding structure, so that the method has higher context modeling capability and parallel processing capability, and the adaptive capability to an image structure and semantic content can be effectively improved; transmission delay can be reduced, and image reconstruction quality and channel interference resistance can be enhanced.

The invention discloses a Web-based visual editing method, belongs to the technical field of industrial configuration, and aims to solve the problems of complex deployment of traditional configuration software and insufficient Web scheme performance. The method comprises the following steps: constructing a front-end architecture (Vue. Js + Konva.js) containing a graphic element module, a canvas management module and the like; the primitive adopts JavaScript prototype chain inheritance + SVG / Canvas double-layer rendering, and a canvas is divided into four layers and is provided with a quadtree index; an editor and an expression engine are generated by using a factory pattern for attribute configuration; page management supports state capture recovery; real-time communication is based on WebSocket + PubSub, and data aggregation and incremental updating optimization are combined. Cross-platform zero deployment and Web environment near-desktop performance are achieved, editing efficiency is improved, industrial protocols such as OPC UA are compatible, and the method is suitable for the field of energy and intelligent manufacturing.

The invention relates to the technical field of live ammunition point positioning, in particular to a simulated live ammunition point accurate positioning method. According to the method, the time and the displacement value of track segmentation are calculated based on the shooting parameter set, the coordinate set of each track segment is defined, the longitudinal deviation value is calculated in combination with the gravitational acceleration, segmentation processing of track generation is refined, the track calculation accuracy is ensured, and the target range is determined by judging the relation between the coordinate points and the target range point by point. The Euclidean distance between candidate points and the center of the target is calculated in combination with a gradient descent method, the screening process of hit point positions is optimized, the offset between a to-be-hit point and the center of the target is reduced by adjusting the initial velocity and the shooting angle of a bullet for multiple times, coordinate points exceeding the boundary of a target range are corrected through a quadtree segmentation algorithm, and the accuracy of target shooting is improved. The re-segmentation calculation of the track points meets the constraint condition of the space boundary, the effectiveness of the track point set and the accuracy of the drop point positioning are improved, and comprehensive data support is provided for weapon debugging and training.

The invention relates to the technical field of geological disaster monitoring, and discloses an unmanned aerial vehicle aerial survey intelligent identification and grading method and system for geological disaster hidden danger points, and the method comprises the steps: converting a pixel-level identification result into hierarchical data which retains a spatial topological structure through constructing a confidence quad-tree; establishing a weighted decision grid based on aerial survey parameters to realize coupling modeling of observation conditions and confidence uncertainty, calculating topology difference to generate a spatial difference field to quantify the deviation degree of a confidence field and a standard grading decision surface, and finally executing self-adaptive grading judgment to output a risk grade result with a confidence label; according to the method, the problem of confidence field and decision boundary space topology mismatch caused by truncation of confidence continuous measurement information in a grading stage in a traditional serial architecture is solved, systematic underestimation of misjudgment risks in observation condition limited areas such as alpine and gorge areas is avoided, and consistency of actual credibility of a risk quantification result and a nominal grade is realized.

The invention provides a three-dimensional geologic body rendering method and system which are used in the field of geospatial information visualization, and the method comprises the steps: obtaining a three-dimensional geologic body model; simplifying the three-dimensional geologic body model by a half folding algorithm based on secondary error measurement; blocking the simplified geologic body model through a planar quadtree, and constructing a spatial index tree according to the blocks to generate a geologic body blocking model of an LOD level; obtaining a viewpoint position and a vision field range of a user, calculating a screen space error, switching a geologic body partitioning model corresponding to an LOD level, and preferentially loading a high-precision close-range tile; the calculation shader based on the WebGPU performs parallel rendering on the geologic body block model tiles; and after the tiles of the geologic body block model are compressed through a Draco compression algorithm, the geologic body block model data stream is sent to the client. According to the scheme, the processing efficiency of the geologic body model in the links of loading, rendering, transmission and the like is improved, and the rendering efficiency of the geologic body model under mass requirements can be effectively guaranteed.

The invention relates to the technical field of industrial data processing, in particular to a PDF drawing vector review method and system based on the creative technology, and the method comprises the steps: receiving a PDF drawing data stream through a creative security communication channel, and converting the PDF drawing data stream into a standardized graphic primitive containing a two-dimensional coordinate and engineering metadata through a sandbox security parser; and on the basis, a spatial semantic data structure integrating quadtree spatial indexes and semantic grouping information is constructed. According to the method, a dynamic performance benchmark test data model is also constructed; and during rendering, predicting and selecting an optimal rendering scheme capable of meeting preset target performance based on the model, efficiently generating an interactive graphic review interface by utilizing the data structure, and finally receiving and storing a user review instruction associated with the graphic object. By constructing the adaptive rendering model and fusing a data structure of space and semantic information, high-performance and safe vectorization interactive review of the PDF drawing in a credential environment is realized.

The invention discloses a water flow numerical simulation self-adaptive grid block encryption method based on a quadtree spatial data structure, and relates to the field of simulation and analysis of hydrodynamic problems in water conservancy projects, and the simulation of water flow movement is calculated through a grid Boltzmann method. The self-adaptive encryption is realized by a self-adaptive grid refining technology based on a quadtree spatial data structure. The dam break wave flowing phenomenon in the dam break process is simulated, the water volume of a calculation area is constant, the upstream and downstream water levels are different before complete dam break, the upstream and downstream water flow flowing and self-adaptive grid encryption conditions in the instantaneous complete dam break process are simulated and analyzed, the real-time display function of the calculation result is achieved, and the calculation accuracy is improved. Through reasonable parameter setting, the speed field, the pressure field, the grid number and other conditions obtained through calculation can be displayed on a screen in real time under the condition that the calculation speed is not affected. A user can conveniently adjust calculation parameters according to a calculation intermediate result, and simulation calculation can be continued according to a preset target.

The invention provides a water body pollution spatial-temporal distribution dynamic monitoring system based on multi-source remote sensing data fusion and deep learning, and relates to the technical field of data processing, and the system comprises the steps: obtaining a satellite hyperspectral image, unmanned aerial vehicle multispectral data, and water quality parameter data collected in real time through ground Internet of Things equipment; the inversion module is used for performing pollutant concentration inversion on the satellite hyperspectral image to obtain pollutant concentration data; performing local pollution source positioning on the unmanned aerial vehicle multispectral data to obtain pollution source position data; acquiring real-time water quality parameter data from ground Internet of Things equipment; the spatial discretization module is used for carrying out spatial discretization processing on pollutant concentration data, pollution source position data and real-time water quality parameter data, establishing a quadtree index and carrying out recursion division on the quadtree index into sub-regions; and generating a dynamic space correction parameter according to the statistical characteristics of the data points in each sub-region. The method can effectively improve the water body pollution time-space distribution monitoring precision and the pollution early warning reliability.

In various examples, embodiments are directed to identifying map data (e.g., relevant to a route) using a quad-tree spatial index. In this regard, spatial map data that indicates various map features is represented in a quad-tree spatial index for use in identifying map data. To identify map data, bounding shapes may be generated in association with various segments of a route. An indication of an object-oriented bounding shape may be used to query the quad-tree spatial index to identify map data related to the object-oriented bounding shape. In embodiments, an object-oriented spatial index may be generated that indexes the object-oriented bounding shapes associated with the route. The object-oriented spatial index may be used to query the quad-tree spatial index to identify map data related to the corresponding object-oriented bounding shapes. Alternatively, the quad-tree spatial index may be used to query the object-oriented spatial index to identify map data.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention provides a geographic element spatio-temporal topology establishment method for a large ocean forecast disaster reduction model, and belongs to the technical field of ocean observation forecast. Multi-source heterogeneous ocean data is fused and cleaned in real time, sparse data complementation of physical constraints is realized by using a temperature-salt flow collaborative interpolation model and a graph neural network, and the real-time fusion and cleaning of the multi-source heterogeneous ocean data are realized. A spatial index is established based on quadtree Z curve coding, a main filter and an auxiliary filter are executed in parallel through a GPU double-layer sub-thread grid to achieve millisecond-level query response, and local increment updating is conducted on a topological relation through spatial partitioning and an event-driven mechanism. Bayesian Kriging interpolation and Monte Carlo simulation are introduced to add confidence labels for topological nodes to quantify uncertainty, and finally standardized spatio-temporal topological relation data are output, so that the technical problem that a large ocean forecast disaster reduction model is difficult to understand and a geographic element spatio-temporal topological relation under the condition of observation forecast data is efficiently constructed is solved.

A geometry cleanup method for a 2.5D model for characterizing a layered circuit board structure, comprising: merging adjacent points on the basis of an adaptive quadtree; performing an edge intersection operation; removing a sharp angle; aligning points to edges; simplifying a polygon; and performing local update.

The invention discloses a space block convergence method and device based on grouping combination, a storage medium and electronic equipment, and the method comprises the steps: dividing a target layout into a plurality of regions; performing horizontal scanning and vertical scanning on the pattern in each area by adopting a scanning line method, generating polygonal blocks, and forming a space block of each polygonal block; constructing a quadtree structure based on each space block; for any two adjacent areas, polygon blocks at the common boundary are extracted from the corresponding quadtree structures, and two boundary block sets are formed; performing grouping and merging processing on the two boundary block sets to generate a new boundary block set; forming a space block set by the new boundary block set and the non-boundary blocks in the two adjacent areas; optical rule detection is performed on each polygonal block in the set of spatial blocks. According to the scheme, the optical rule detection efficiency can be improved.

The invention provides an alignment method for territorial space planning multi-modal data, and belongs to the technical field of big data processing.The alignment method comprises the steps that a quadtree structure is adopted to segment a remote sensing image, a three-dimensional index is established, a graph segmentation algorithm is utilized to divide vector data space subgraphs, a space-time weight matrix fusing space weight, time weight and credibility weight is constructed, and the three-dimensional index is established; inputting the preprocessed multi-modal data into a multi-modal semantic fusion model comprising a residual neural network, a bidirectional encoder and a graph convolutional network to extract a unified semantic representation vector, identifying conflict data by calculating semantic similarity, constructing a rule priority directed graph, and calculating a rule importance score by adopting a random walk algorithm; and executing the conflict resolution rule according to the priority and outputting the aligned data set. The technical problem that efficient alignment of the multi-source heterogeneous territorial space planning data on the semantic level is difficult to realize is solved.

The invention discloses an unmanned aerial vehicle patrol and security monitoring linkage management method. According to the system, urban geographic information data and key monitoring area coordinates are acquired, hierarchical grid division is realized by using a quadtree spatial index algorithm, and a patrol task distribution basic data structure is established; solving an approximate optimal solution of the patrol path of the unmanned aerial vehicle by adopting an improved greedy strategy, and performing optimization adjustment according to technical parameters and weather conditions of the unmanned aerial vehicle; the unmanned aerial vehicle collects video data in real time through high-definition camera equipment in the patrol process, target detection is conducted through a deep learning model, and potential safety hazards such as personnel gathering and vehicle abnormity are recognized; detecting violent conflicts and illegal intrusion behaviors in combination with a time sequence analysis algorithm, and generating an abnormal event report; cooperative work of the unmanned aerial vehicle, the ground robot and the command center is realized; and a patrol scheme is dynamically adjusted according to meteorological conditions, and robot scheduling is optimized through energy consumption management.

A method of partitioning in video coding for JVET, comprising representing a JVET coding tree unit as a root node in a quadtree plus binary tree (QTBT structure that can have quadtree or binary partitioning of the root node and quadtree or binary trees branching from each of the leaf nodes. The partitioning at any depth can use asymmetric binary partitioning to split a child node represented by a leaf node into two child coding units of unequal size, representing the two child coding units as leaf nodes in a binary tree branching from the parent leaf node and coding the child coding units represented by final leaf nodes of the binary tree with JVET. Disclosed is a generalized method of partitioning a block, either square or rectangular, which leads to more flexible block sizes with possible higher coding efficiency.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention relates to the technical field of space optimization, and discloses a container loading space optimization method based on robot collaboration, and the method comprises the steps: building a multi-dimensional physical model of a package through obtaining the point cloud data and weight distribution of the package; generating a loading scheme containing a target pose, a pressure tolerance threshold and a loading sequence based on a reinforcement learning algorithm; the mechanical arm generates a motor current-position composite control instruction according to a pre-trained grabbing dynamical model, and accurate grabbing is achieved; in the loading process, the pose of the parcel is monitored in real time through a Kalman filtering algorithm, when deviation exceeds a threshold value, a local space KD tree is constructed, a collision probability gradient field is calculated, and a compensation scheme meeting stability constraints is generated; and finally, updating the quad-tree index and feeding back to the reinforcement learning algorithm for online optimization. The problem that in the robot loading process, the grabbing force control is not accurate, and the efficiency is reduced due to execution deviation accumulation is effectively solved, and efficient and accurate automatic loading is achieved.