Hierarchical moving curved fitting filtering method based on LIDAR data
多级移动曲面拟合LIDAR数据滤波算法

LIDAR data is accurate 3D data of terrain acquired from airborne laser detection and ranging system. Compared with hardware technique, data post-processing technique of LIDAR data is weak and time consumed. In this situation, a HMCFA (Hierarchical Moving Curved Fitting Algorithm) filtering method of LIDAR data is reported in this paper. Firstly, block grid searching and indexing mechanism is set up to label discrete LIDAR cloud points. Secondly, quadratic polynomial is set up to fit land terrain with different window size. At last, adaptive threshold is used to distinguish ground points and non-ground points. Accuracy assessment results indicate that the filter error is less than 1m, which can be used in application.