Comparison of handheld LiDAR point cloud filtering methods for complex mountain microtopography
In this paper,a typical use case of hand-held laser point cloud data for measuring soil erosion and surface erosion in complex mountainous areas is presented,the performance of delta filter algorithm,slope filter algorithm and cloth simulation filter algorithm in point cloud classification of ground-based LiDAR is compared and analyzed. In order to obtain the highest performance,the parameters corresponding to three kinds of filters are used to test the test data set,and the optimal filtering of each algorithm is obtained through comparative analysis,the experimental results show that for smooth bare landform filtering,cloth simulation filtering is the best,progressive densification triangle filtering is the second,and slope filtering algorithm is the worst,the progressive encrypted triangle filter algorithm has the best filtering effect,the cloth simulation filter is the second,and the slope filter algorithm has the worst filtering effect. The experimental results provide valuable information for optimizing the parameters of the filtering algorithm to improve its performance in detecting micro-terrain changes,and verify the effectiveness of the progressive encrypted triangle filter in complex areas.
hand-held 3D laser point cloudprogressive encryption triangle filterslope filtercloth simulation filtersmooth bare landformcomplex mountain landform
万方数据
维普
