An Improved 1-D filtering Method for LIDAR Point Cloud

摘要

This paper discusses how to separate non-ground points from raw LIDAR point cloud. For the purpose of improving processing efficiency and precision, an improved 1-D filtering method is proposed. The entire filtering process is divided into eight steps and non-ground points are eliminated progressively. In these processing steps, a key-point detection technique is used to segment points in profile. Based on these profile segments, detailed analysis is utilized to implement segment-oriented filtering innovatively. This method makes use of entire features of segmental points for classification, so it is more accuracy and robust than traditional point-by-point classification. Two different scale datasets are used to test our method. Compared to 1-D labeling method, the proposed method is more effective and efficiency.