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| A secondary filter method of LiDAR point cloud based on curvature statistics |
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WAN Jian-hua1, HUANG Rong-gang1, ZHOU Hang2, ZENG Zhe1
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(1.School of Geosciences in China University of Petroleum, Qingdao 266580, China;2.College of Geosciences in China University of Petroleum, Beijing 102249, China)
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| Abstract: |
| The rusults of conventional skewness balancing exist non-ground points of low vegetation and side of buildings. Aimed at this, a secondary filter method of LiDAR point cloud was developed based on curvature statistics to filter the remained non-ground points in the result of filter based on conventional skewness balancing. The results of the secondary filter method proposed and conventional skewness balancing were compared. The results show that the former can remove 83% more pionts of vegetation and 5% more pionts of building than the latter. The secondary filter method of LiDAR point cloud based on curvature statistics can efficiently filter the non-ground points remained in the conventional skewness balancing method. |
| Key words: LiDAR point cloud filter method curvature statistics |
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