Research on airborne laser point cloud thinning algorithm with terrain features

Decheng Hu

doi:10.1117/12.3048747

27 November 2024 Research on airborne laser point cloud thinning algorithm with terrain features

Decheng Hu

Author Affiliations +

Proceedings Volume 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024); 134023K (2024) https://doi.org/10.1117/12.3048747
Event: International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 2024, Zhengzhou, China

Abstract

This study proposes a novel thinning algorithm to effectively preserve terrain features in response to the problem of increased processing burden caused by high density of airborne laser point cloud data. This study is based on constructing a spatial triangulation using a regular triangulation network, with the maximum distance point between the laser point cloud and the spatial triangulation within the projection range of the triangulation as the terrain feature points to be retained. This algorithm achieves a significant reduction in data volume while ensuring the main terrain features of point cloud data, achieving good results in balancing the efficiency and accuracy of the algorithm.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Decheng Hu "Research on airborne laser point cloud thinning algorithm with terrain features", Proc. SPIE 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 134023K (27 November 2024); https://doi.org/10.1117/12.3048747

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