|Table of Contents|

Point cloud data compression algorithm based on improved coordinate increment(PDF)

西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

Issue:
2016年06期
Page:
849-856
Research Field:
Publishing date:

Info

Title:
Point cloud data compression algorithm based on improved coordinate increment
Author(s):
YAO Wan-qiangLIN Xiao-huMA FeiXUE Bei
College of Geomatics,Xi'an University of Science and Technology,Xi'an 710054,China
Keywords:
coordinate increment method terrestrial laser scanning point cloud compression scan line feature retain
PACS:
P 207
DOI:
10.13800/j.cnki.xakjdxxb.2016.0615
Abstract:
In order to improve the efficiency of 3D modeling and application of point cloud data,it is necessary and urgent to carry out data compression under the premise of ensuring the geometric feature.The terrestrial laser scanning often produces high density and information redundancy of point cloud data.However,the existed algorithms are insufficient.Extending the point cloud data point by point compression of one dimensional scanning line in the coordinate increment method to two-dimensional scanning lines between,thus a point cloud data compression algorithm based on improved coordinate increment has been proposed on the basis of studying the existing algorithms.A case study is conducted in Matlab to compare the compression effect of the proposed method and several existing typical compressionmethod from qualitative and quantitative such as coordinate increment algorithm,random sampling algorithm,barycenter of area data compressing method and curvature sampling algorithm.The experiments show that the proposed method achieves good compression effect with a relatively short time,moderate speed and well preserved feature information for point cloud data of scan-lined plane or curved surface,providing some reference for the storage and management of massive point cloud data in the era of big data.

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Last Update: 2016-11-28