A Method for Noise Removal of LIDAR Point Clouds

摘要

LiDAR can quickly and accurately obtain precision and high-density surface elevation data. In cooperation with high-precision GPS positioning technology and IMU attitude sensor, a typical noise removal algorithm of LIDAR point clouds based on FEA is proposed. Firstly point clouds is partitioned into smaller and similar units, then all of the units are classified into noise units or non-noise units with adjacency-based reasoning rules. Finally, the low noise is removed by iterative processing with finer threshold, The result shows that this method has good performance in noise removal.