A scan-line-based data compression approach for point clouds: Lossless and effective
Liu Xianxiong, Yue Wang, Qingwu Hu, Dengbo Yu · 2016
Light Detection and Ranging (LIDAR) is an attractive and effective technique to obtain spatial information of terrain features. While the vast amount of points presents problems for data exchange, distribution, and storage. Thus, a data compression approach for point clouds is proposed in this paper to solve these problems. In our proposed approach, JPEG2000 standard is exploited to compress the color information. To compress the 3D coordinate, a distance based predictor is employed to predict the forthcoming point using the information of previous points. And a compression and decompression algorithm based on arithmetic coding is proposed to compress or decompress the predictor. The experiment results reveal that our approach is effective and efficiency.