An adaptive compression algorithm of scattered point cloud based on wavelet technology

An adaptive compression algorithm of scattered point cloud based on wavelet technology is proposed in this paper. The proposed algorithm converts 3D space point cloud into point sets on a 2D plane by using slicing technology in rapid prototyping theory. After the wavelet transform operation, the wavelet coefficients of the sorted point cloud data are obtained, the peaks of these wavelet coefficients can represent the points to be reserved. According to the experiment, the fast and efficient compression of scattered point cloud can be achieved when the slice thickness is approximately 2 to 3 times the sampling interval. Comparison results between the proposed algorithm and conventional algorithm indicates that the former exhibits obvious advantages in feature reservation. The details and feature information can be ultimately reserved in this algorithm, thus making the compression results ideal. The proposed algorithm does not need to set a threshold to explain its adaptability and realize automatic compression.