〗Filtering of Airborne LiDAR Point Cloud Data Based on Mathematical
Morphology and Region Growing
1 Faculty of Geosciences and Environment Engineering, Southwest Jiaotong University, West High-Tec Zone, Chengdu 611756, China〖JP〗
2 State-Province Joint Engineering Laboratory of Spatial Information Technology of High-Speed Rail Safety,
West High-Tec Zone, Chengdu 611756, China
3 The Third Surveying and Mapping Engineering Institute of Sichuan, 2 Xinjun Street, Chengdu 610500, China
Abstract According to the phenomenon that a morphological filter erodes terrain excessively and the demand of seed ground points for region growing, a two-stage “rough-refined” filtering strategy is proposed. First, a rough digital elevation model (DEM) is obtained by applying a multi-scale morphological filter to airborne LiDAR data, which is called rough filter. Then, region growing is applied to gain refined DEM based on the seed ground points derived from the rough DEM. When tested against the ISPRS LiDAR reference datasets, the experiment shows that the proposed algorithm is highly adaptable to various landscapes in reserving the detail of terrain effectively, and also is more robust.
GU Yanchao,FAN Dongming,YU Biao et al. 〗Filtering of Airborne LiDAR Point Cloud Data Based on Mathematical
Morphology and Region Growing[J]. jgg, 2015, 35(5): 811-815.
GU Yanchao,FAN Dongming,YU Biao et al. 〗Filtering of Airborne LiDAR Point Cloud Data Based on Mathematical
Morphology and Region Growing[J]. jgg, 2015, 35(5): 811-815.
