Light Detection and Ranging (LIDAR) has become one of the prime technologies for rapid collection of vast spatial data, usually stored in a LAS file format (LIDAR data exchange format standard). In this article, a new method for lossless LIDAR LAS file compression is presented. The method applies three consequent steps: a predictive coding, a variable-length coding and an arithmetic coding. The key to the method is the prediction schema, where four different predictors are used: three predictors for x, y and z coordinates and a predictor for scalar values, associated with each LIDAR point. The method has been compared with the popular general-purpose methods and with a method developed specially for compressing LAS files. The proposed method turns out to be the most efficient in all test cases. On average, the LAS file is losslessly compressed to 12% of its original size.
COBISS.SI-ID: 14953494
A pseudo-triangulation is a planar subdivision into polygons with three convex vertices, useful for ray shooting, visibility problems and kinetic collision detection. As pseudo-triangulations are quite young, there is a lack of specialized algorithms for them. In this paper, we address the question of location in pseudo-triangulations. We propose two location algorithms based on the so-called stochastic walk and present their experimental results. The class of walk location algorithms is very popular for triangulations, namely in engineering applications, due to simplicity and low memory requirements, in spite of their non-optimality.
COBISS.SI-ID: 15010838
The biggest problems encountered are large storage requirements, lesser transportability (file sizes) and real-time visualization (up to a billion for some scans). With typical broadband Internet connections already offering speeds above 10 Mbps, remote storage and visualization is becoming a reasonable option for LiDAR use. The transport issues is solved by storing all point data on a server and organizing it into a data structure which enables quick handling of range and level-of-detail queries from a remote client. The client designed to connect to this server uses advanced point-based rendering for high quality display of transferred data.
COBISS.SI-ID: 25619495