Influence of flattening point cloud on filtering accuracy

Point cloud filtering is a very important link in Lidar data processing, that is, separating ground points and non-ground points in the point cloud, which lays a foundation for subsequent data processing. The filtering accuracy will directly affect the accuracy of the final DEM. Based on the "rotation invariance" of point cloud, this paper firstly uses Euler transformation, axis angle transformation and homogeneous transformation to flatten the target point cloud. Then the mainstream filtering methods such as cloth simulation filtering algorithm, statistical filtering method, bilateral filtering and slope filtering are used to filter the point clouds before and after flattening, and the filtering results are evaluated by ISRIS index. Finally, the corresponding DEM model is constructed through the filtering results, and the overall error of DEM constructed by each filtering algorithm is quantitatively analyzed through the evaluation indexes of DEM average error, median error and maximum error, so as to study the influence of point cloud flattening on point cloud filtering.