Lossless progressive compression of LiDAR data using hierarchical grid level distribution

This letter considers a new approach for the lossless progressive compression of light detection and ranging (LiDAR) data stored within a LAS file (public file format for the interchange of three-dimensional point cloud data), which is used for storing the results of LiDAR scanning. The presented method builds a hierarchical data model for arranging LAS points into different levels in one pass. The higher levels are compressed using variable length and arithmetic coding, whilst the lower levels apply a prediction model of the non-progressive compression schema. The order of the points, as captured by the LiDAR scanner, has to be preserved within each level as better compression ratios are achieved in this way.