Study On Algorithms Of Airborne LiDAR Point Cloud Data Filtering

The filtering of airborne laser scanning points cloud is one of the critical data processing technologies, therefore, the deep research of filtering algorithms is practically valuable and useful. In the area of photogrammetry and remote sensing, it is full of frontier research task. This paper analysed and summarized airborne LiDAR status, systematic composition, research actualities of filtering, the acquisition theory and characteristics of point cloud, and the standards of judging filtering errors. This paper tested the algorithms of point cloud filtering and post-processing and made the precision analysis. The research work embodies as follows:1. On the basis of introducing the airborne LiDAR technique research background and significance, domestic and foreign LiDAR point cloud data filtering algorithms, the research status, the system theory and composition and their main parameters comparisons, and list the LiDAR data post-processing commonly used software, this paper discusses the airborne laser scanning point cloud data processing steps, which provides the theory basis for the experiments.2. Aiming at the characteristics of the complexity and dispersion of the point cloud data, this paper studied the morphological filtering used in processing of LiDAR point cloud, tested standard sample data given by ISPRS according to algorithm, did lots of experiments about window, grid spacing, elevation difference threshold as the three parameters to weed out the non-ground points, we can get different ground point cloud data on the same block of data by giving different window size, grid spacing and elevation difference threshold for filtering. Contrasts of the errors displayed the better filtering results.3. According to procedure, on the basis of pre-processing of airborne LiDAR point cloud data, this paper explored Causal Auto-Regressive process Model as one method of the Robust Estimation to process the point cloud data.