Integrating Morphological Grayscale Reconstruction and TIN Models for High-quality Filtering of Airborne LiDAR Points.

Based on the characteristics of the morphological filter and the TIN-based progressive filter, a high-quality LiDAR point cloud filtering algorithm combining Morphological grayscale reconstruction and TIN Models is proposed in this paper. Its main strategies are: 1 Implementing morphological grayscale reconstruction with a priority of Type I Error and non-minimum suppression. In this step, LiDAR point clouds are tagged as Reliable terrain points G, suspicious terrain points S and suspicious Non-terrain points NG; 2 Suspicious non-terrain points are further tagged based on the iterative order of Morphological grayscale reconstruction. In this step, small and constant height interval is used to filter the possible non-terrain points at different elevation; 3 Constructing the initial TIN from points G and further filtering points S and NG points, respectively, by adaptively adjusting the parameters of the ground point criterion at associated point layer. We did an experiment with 15 ISPRS test data sets and assessed the results with the standard criterion as found in the literature. The result shows that proposed filtering algorithm dramatically improved filtering quality, even for complex terrain. [ABSTRACT FROM AUTHOR]