Research On 3D Laser Scanning Point Cloud Data Reduction Algorithm

Three dimensional laser scanning technology is a new technology which appeared in the middle of the 1990s.It is a new breakthrough of GPS surveying and Mapping Technology.By means of high speed laser scanning measurement,the 3D coordinate data of the surface of the measured object can be obtained quickly and rapidly with large area and high resolution.At present,there are many methods to compress the point cloud data.There is a grid based compression method,based on the point cloud compression method,but there are still some problems in the evaluation of the compression algorithm and the advantages and disadvantages of the algorithm.Aiming at the above problems,this paper uses MATLAB as the programming platform of several commonly used compression algorithms are implemented,and then analyze and compare the advantages and disadvantages of the algorithm,based on the proposed new compression algorithm,mainly completed following several aspects research:1.the classification,basic working principle and process of point cloud data processing are studied.2.The spatial division of point cloud data is studied.Including K neighbor search and point cloud data vector estimation,for the subsequent point cloud simplification algorithm to do the basic work.3.This paper focuses on the research of the point cloud data compression algorithm,and realizes the random sampling method,the bounding box centroid method,the shortest distance sampling method and the method of the vector angle method four compression algorithms.Standford and the bunny point cloud data of four kinds of algorithm for compression test,the 3D model was established by use of point cloud data compression,and the surface area and volume,respectively from the standard deviation of three parameters to assess the advantages and disadvantages of analysis and comparison of four algorithms.4.In this paper,a new algorithm is proposed,which is based on the curvature characteristics of the point cloud data.In this algorithm,the point cloud data is divided into high curvature part and low curvature part according to the curvature.5.Standford Bunny point cloud data is used to compress the curvature shortest distance algorithm and the quality of the results is evaluated.According to the results of the quality evaluation,the new algorithm is more accurate than the four compression algorithms under the same compression ratio.At the same time,the algorithm has the advantages of simple parameter setting and high efficiency,and has good practical value.