Restoration of Individual Tree Missing Point Cloud Based on Local Features of Point Cloud

LiDAR (Light Detection And Ranging) technology is an important means to obtain three-dimensional information of trees and vegetation. However, due the influence scanning mode, environmental occlusion mutual between tree canopies other factors, a point cloud often has different degrees data loss, which affects high-precision quantitative extraction vegetation parameters. Aiming at problem laser being missing, individual incomplete restoration method based on local features proposed. The L1-Median algorithm used extract key points skeleton, then dominant direction skeleton density are calculated, near missing area moved these gradually complete compensation. experimental results show that above repair can effectively with good robustness adapt geometric structures correct branch topological connection errors.