Research on Airborne LiDAR Point Cloud Data Filtering Method
In order to improve the filtering effect of airborne LiDAR point cloud in complex terrain areas, an airborne LiDAR point cloud filtering method combining cloth simulation filtering (CSF) and improved irregular triangular network (TIN) is proposed in this paper. The main steps to realize airborne LiDAR point cloud filtering are as follows: Firstly, the gross errors in the original point cloud data are eliminated by using KD tree algorithm; Secondly, CSF is used to filter the point cloud data after gross error elimination, and the tall ground points such as buildings are filtered to obtain the initial ground points; Finally, the improved TIN algorithm is used to further fine filter the initial ground points, and the final ground point results are obtained. In order to test the effectiveness and superi-ority of the method proposed in this paper, two groups of experimental data are used for filtering experiments. The results show that the point cloud filtering method in this paper can effectively reduce class Ⅰ and class Ⅱ errors, and has good accuracy for point cloud filte-ring under different terrain conditions.
airborne LiDAR point cloudfilteringcloth simulation algorithmtriangulation irregular networkaccuracy analysis
万方数据
维普
