BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA
In order to solve the problem that the source of LiDAR data error needs to be adjusted and the data volume is large, the adjustment speed between the voyages is slow and cannot be automatically adjusted. Based on the iterative nearest point (ICP) algorithm, this paper proposes an improved iterative...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-02-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W10/229/2020/isprs-archives-XLII-3-W10-229-2020.pdf |
| _version_ | 1818912154299924480 |
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| author | B. Song G. Q. Zhou Y. L. Lu X. Zhou X. Zhou P. Liang |
| author_facet | B. Song G. Q. Zhou Y. L. Lu X. Zhou X. Zhou P. Liang |
| author_sort | B. Song |
| collection | DOAJ |
| description | In order to solve the problem that the source of LiDAR data error needs to be adjusted and the data volume is large, the adjustment speed between the voyages is slow and cannot be automatically adjusted. Based on the iterative nearest point (ICP) algorithm, this paper proposes an improved iterative closest point (ICP) algorithm based on GPU parallel octree. The algorithm quickly constructs the octree of LiDAR nautical belt data in the GPU, uses the octree to quickly find the overlapping area of the nautical band, and then uses the ICP algorithm in the overlapping area to solve the adjustment parameters R and T quickly. Then the entire flight belt is quickly adjusted. Experiments with example data show that this method can quickly and automatically adjustment a large number of LiDAR data, and the adjustment precision can meet the precision requirements of the production. |
| first_indexed | 2024-12-19T23:10:05Z |
| format | Article |
| id | doaj.art-07e5deb087e74937be9d93bc7848d6cb |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-19T23:10:05Z |
| publishDate | 2020-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-07e5deb087e74937be9d93bc7848d6cb2022-12-21T20:02:15ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-02-01XLII-3-W1022923310.5194/isprs-archives-XLII-3-W10-229-2020BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATAB. Song0G. Q. Zhou1Y. L. Lu2X. Zhou3X. Zhou4P. Liang5Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi 541004, ChinaGuangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi 541004, ChinaGuangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi 541004, ChinaGuangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi 541004, ChinaCollege of Mechanical and Control Engineering, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi541004, ChinaGuangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, No. 12 Jian’gan Road, Guilin, Guangxi 541004, ChinaIn order to solve the problem that the source of LiDAR data error needs to be adjusted and the data volume is large, the adjustment speed between the voyages is slow and cannot be automatically adjusted. Based on the iterative nearest point (ICP) algorithm, this paper proposes an improved iterative closest point (ICP) algorithm based on GPU parallel octree. The algorithm quickly constructs the octree of LiDAR nautical belt data in the GPU, uses the octree to quickly find the overlapping area of the nautical band, and then uses the ICP algorithm in the overlapping area to solve the adjustment parameters R and T quickly. Then the entire flight belt is quickly adjusted. Experiments with example data show that this method can quickly and automatically adjustment a large number of LiDAR data, and the adjustment precision can meet the precision requirements of the production.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W10/229/2020/isprs-archives-XLII-3-W10-229-2020.pdf |
| spellingShingle | B. Song G. Q. Zhou Y. L. Lu X. Zhou X. Zhou P. Liang BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA |
| title_full | BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA |
| title_fullStr | BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA |
| title_full_unstemmed | BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA |
| title_short | BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA |
| title_sort | based on gpu for strip adjustment algorithm of lidar data |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W10/229/2020/isprs-archives-XLII-3-W10-229-2020.pdf |
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