八叉树与三维R~*树集成的激光点云数据存储结构

Integrated Laser Point Cloud Data Storage Structure Based on Octree and 3D R~*-tree

针对海量激光点云数据组织与管理困难等问题,结合八叉树在三维空间上的快速收敛能力以及三维R~*树对不规则分布的多维点数据性能稳定的优势,提出了一种八叉树与三维R~*树集成的空间混合索引结构—3DOR~*树。首先,通过对激光点云数据进行八叉树划分;然后,对八叉树叶子节点构建三维R~*树,进而实现3DOR~*树索引结构的构建;最后,对激光点云数据进行特征分析,构建基于3DOR~*树的激光点云数据存储结构,实现基于3DOR~*树的激光点云存储与管理。本文以江西理工大学图书馆激光点云数据为例,进行实验对比分析,证明了基于3DOR~*树的激光点云数据存储结构比三维R~*树、八叉树与三维R树混合树等其他树形结构,具有高效的空间存储与查询等优势,可应用于海量激光点云数据存储、管理与分析应用。

Aiming at the difficulties of massive laser point cloud data organization and management, a new spatial index structure-3DOR^＊-tree is proposed. This is constructed by fully integrating Octree with fast convergence capability of 3D space and 3D R^＊-tree with the advantages of stable performance of irregularly distributed data. Firstly, laser point cloud data is divided using Octree, and then 3D R^＊-trees are built on the octree leaves. The laser point cloud data is stored only on the leaves of 3D R^＊ tree and 3DOR^＊-tree index structure is constructed. Then, we analyze feature of laser point cloud to achieve laser point cloud storage and management based on 3DOR＇-tree. At last, the point cloud data of the library of JiangXi University of Science and Technology are used for experiment and comparative analysis. The result shows that the improved storage structure of laser point cloud data based on 3DOR^＊-tree has an advantage of efficient space storage and query compared to other tree structure, such as 3D R＂ tree, integrated tree of Octree and R tree and so on. Thus, 3DOR＇- tree can be applied to management and analysis applications of massive laser point cloud data storage.