Filtering of Airborne LiDAR Point Cloud Data Based on Progressive TIN

Airborne LiDAR point cloud data filtering is not only the key to obtain high-precision Digital Elevation Model,but also one of the difficulties and the focus in the current study of the LiDAR point cloud data post-processing.In this paper,the method is proposed for filtering LiDAR point cloud data based on progressive TIN and the details of filter principle is described.Firstly,LiDAR point cloud data is organized by regular grid and Triangulated Irregular Network(TIN),seed points are selected by regional sub-block method or mathematical morphology.Then,an initial sparse TIN is created from the seed points and densified upward and ground points are extracted in an interactive process.In experiments it is shown that the filter method can effectively remove different sizes of buildings,low vegetation and other objects,and keep topographical features better.Finally,the point cloud of different regions is selected to do the experiment,and the shaded relief maps for the grids generated from unfiltered and filtered LiDAR point cloud data are shown.