Abstract: 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 reconstrution and TIN Models is proposed in this paper. Its main strategies are:lImplementing morphologicalgrayscale 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 suspiciousNon-terrain points NG;②Suspicious norrterrain points are further tagged based on the iterative orderof Morphological grayscale reconstruction. In this step，small and constant height interval is used tofilter the possible non-terrain points at different elevation;③Constructing the initial TIN from pointsG and further filtering points S and NG points，respectively，by adaptively adjusting the parameters ofthe ground point criterion at associated point layer. We did an experiment with 15 ISPRS test data setsand assessed the results with the standard criterion as found in the literature. The result shows thatproposed filtering algorithm dramatically improved filtering quality，even for complex terrain.