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GPU-CPU (Central Processing Unit-Central Processing Unit) collaborative rapid coordinate conversion method and system for raster data

A raster data and coordinate conversion technology, applied in image data processing, instruments, etc., can solve the problems of inability to convert huge images and low efficiency of raster data coordinate conversion, etc., and achieve the effect of fast processing

Pending Publication Date: 2022-02-08
山东省国土测绘院
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above problems, the present invention proposes a GPU-CPU cooperative raster data fast coordinate conversion method and system. The present invention can solve the problems of low efficiency of traditional raster data coordinate conversion and the inability to convert some huge images, thereby Really realize high-efficiency data conversion

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  • GPU-CPU (Central Processing Unit-Central Processing Unit) collaborative rapid coordinate conversion method and system for raster data
  • GPU-CPU (Central Processing Unit-Central Processing Unit) collaborative rapid coordinate conversion method and system for raster data

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Embodiment 1

[0037] A GPU-CPU coordinated raster data fast conversion method, comprising the following steps:

[0038] (1) Construction of regular grid parameters.

[0039] ① Construct a 3D point cloud dataset, use the same-named control point data of different input coordinate systems, and use the difference between the X direction and the Y direction as the Z value to construct a 3D point cloud dataset (X, Y, Z).

[0040] Z x =x a -x b

[0041] Z y =y a -y b

[0042] Points a and b are a pair of control points with the same name, and x and y are the abscissa and ordinate of the point.

[0043] ②Construction of regular grid parameters

[0044] First, using the 3D point cloud dataset, the Delaunay triangulation algorithm is used to generate the Delaunay triangulation, and the Z value is assigned to each node of the triangulation; then, a regular grid with a resolution of 1km*1km is constructed, and each grid The value of the grid is extracted from the triangular network through t...

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Abstract

The invention provides a GPU-CPU collaborative raster data rapid coordinate conversion method and system. The method comprises steps of constructing a three-dimensional point cloud data set, generating a triangulation network, extracting data in the triangulation network, and interpolating the data into a regular grid, thereby achieving construction and assignment of the parameters of the whole coordinate conversion regular grid; original grid data being loaded, relevant information of a target grid being obtained through the regular grid parameters, and blank target grid data being generated; partitioning the raster data according to the data information of the CPU end; constructing a memory pointer of the CPU end by using the information of the regular grid parameters, applying for a memory space of the GPU end, and copying memory information of the CPU end to the GPU end; and iteratively executing coordinate conversion and interpolation on the original raster data in the video memory space of the target raster data block. According to the method, high-efficiency data conversion can be truly realized.

Description

technical field [0001] The invention belongs to the technical field of image data processing, and in particular relates to a GPU-CPU coordinated raster data fast coordinate conversion method and system. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] Geospatial data is mainly vector and raster data. With the improvement of sensor resolution and data acquisition frequency, the scale of raster data is getting larger and larger. Remote sensing images are the main representative of raster data. Due to the existence of image A variety of coordinate systems have high requirements for data conversion efficiency, and the coordinate conversion of massive raster data greatly limits the conversion efficiency. At the same time, the traditional coordinate conversion parameters, especially in the face of huge raster data conversion, will cause data dis...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T19/20
CPCG06T19/20
Inventor 魏国忠朱伟张衡张省宋禄楷李贵余孙燕
Owner 山东省国土测绘院