Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (9): 71-74.DOI: 10.3778/j.issn.1002-8331.2010.09.021

• 研发、设计、测试 • Previous Articles     Next Articles

Research on organization of airborne LiDAR points cloud based on improved quadtree algorithm

ZHI Xiao-dong1,LIN Zong-jian2,SU Guo-zhong3,ZHONG Liang1   

  1. 1.Department School of Remote Sensing Information Engineering,Wuhan University,Wuhan 430079,China
    2.Chinese Academy of Surveying and Mapping,Beijing 100039,China
    3.Academy of Opto-Electronics,Chinese Academy of Sciences,Beijing 100080,China
  • Received:2009-09-24 Revised:2009-11-18 Online:2010-03-21 Published:2010-03-21
  • Contact: ZHI Xiao-dong


支晓栋1,林宗坚2,苏国中3,钟 良1   

  1. 1.武汉大学 遥感信息工程学院,武汉 430079
    2.中国测绘科学研究院,北京 100039
    3.中国科学院 光电研究院,北京 100080
  • 通讯作者: 支晓栋

Abstract: Through analysis of all kinds of point cloud data organization and processing flow,the indicators of determining the performance of algorithm are proposed.The algorithm of quadtree construction is improved to raise the speed of creating spatial index,and the algorithm of data spatial query is improved to raise the speed of data filtering. At last,the experiments prove the validity and reliability of the method.

Key words: Light Detection And Ranging(LiDAR), massive point cloud, data organization, quadtree, minimum circumscribed rectangle

摘要: 分析了点云数据处理中常用数据组织方法,并指出方法的性能判定指标。对常用的构建四叉树方法进行了改进以提高建立四叉树索引的速度,分析及改进索引算法改进以增进数据筛选的速度,最后通过实验证明了该方法的有效性和可靠性。

关键词: LiDAR, 海量点云, 数据组织, 四叉树, 最小外包矩形

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