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.
关键词
手持三维激光点云/渐进加密三角网滤波/坡度滤波/布料模拟滤波/平缓裸露地貌/复杂山地地貌
Key words
hand-held 3D laser point cloud/progressive encryption triangle filter/slope filter/cloth simulation filter/smooth bare landform/complex mountain landform
维普
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