DocumentCode :
607463
Title :
Data compression system for LiDAR based on quad-tree structure
Author :
Ruoyu Du ; Hyo Jong Lee
Author_Institution :
Div. of Comput. Sci. & Eng., Chonbuk Nat. Univ., Jeonju, South Korea
fYear :
2012
fDate :
3-5 Dec. 2012
Firstpage :
1358
Lastpage :
1363
Abstract :
In recent years, three-dimensional (3D) data has become increasingly available, in part as a result of significant technological progresses in Light Detection and Ranging (LiDAR). LiDAR provides longitude and latitude information delivered in conjunction with a GPS device and elevation information generated by a pulse or phase laser scanner. The main advantages of LiDAR over conventional surveying methods lie in the high accuracy of the data and relatively little time needed to scan large geographical areas. On the basis of analyzing LiDAR data, we propose a compression system to simplify the data set which uses the quad-tree structure as a preprocessing step. The related theory and the methods to make it reality are discussed in detail. Some conclusions come from tests: the method presented in this paper can get a series of compression ratios, and can guarantee the accuracy of LiDAR data.
Keywords :
Global Positioning System; data compression; optical radar; quadtrees; 3D data; GPS device; GPS elevation; LiDAR data; compression system; data compression system; geographical areas; latitude information; light detection and ranging; longitude information; phase laser scanner; preprocessing step; quad-tree structure; surveying methods; three-dimensional data; LiDAR data; data compression; quad-tree;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing and Convergence Technology (ICCCT), 2012 7th International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-0894-6
Type :
conf
Filename :
6530552
Link To Document :
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