A novel compression algorithm for LiDAR data

Light Detection and Ranging (LiDAR) data compression is a critical research field for data processing during past few years because of the large storage size. When LiDAR has small number of data points, the surface generation represented by interpolation methods may be inefficient. This paper presents a compression algorithm to simplify the LiDAR data set, which is constructed based on the quad-tree structure, for fast preprocessing step. The related theory and the methods to make it reality are discussed in detail respectively. Some conclusions were induced from tests: the method presented in this paper can provide multiple compression ratios based on needs, and guarantee the accuracy of LiDAR data for each case.