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.
ZHANG Xi-min1,2,3, YU Xiao-qing1,2, WAN Wang-gen1,2, ZHANG Juan1,2
. Point Cloud Compression Based on Compressed Sensing[J]. Journal of Applied Sciences, 2014
, 32(5)
: 458
-462
.
DOI: 10.3969/j.issn.0255-8297.2014.05.004
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