在研究FARO 激光扫描点云数据特点的基础上，将压缩感知理论和算法应用于3D 点云数据的压缩. 通过对点云数据降维处理，直接对坐标数据进行采样压缩，应用正交匹配追踪算法进行恢复，并对恢复数据采用统计滤波的方法滤除边缘噪点. 仿真结果表明：该方法能有效地实现点云数据的压缩，且有较好的鲁棒性.
This paper applies an algorithm for compression of 3D point cloud based on a study of scanning theory of the FARO laser scanner. The raw point cloud is processed via dimension reduction. The coordinate data are sampled and compressed, and then recovered using the orthogonal matching pursuit (OMP)algorithm.The recovered data are then processed with a statistic filter to remove edge point noise. Simulation results show that the presented method can compress point clouds with good robustness.
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