摘要
多波束测深数据在水下地形地貌研究与应用中具有十分重要的价值。针对多波束测深数据量大,相关处理方法效率低等问题,提出一种基于莫顿编码的八叉树海量点云数据结构。首先,根据点云的包围盒大小及最大深度进行空间划分;然后,对各个节点赋予索引值,并对索引值进行二进制编码,建立基于莫顿编码的八叉树数据结构;最后,以SOR(statistical outlier removal)滤波实验为例,测试提出的数据结构在邻域内快速搜索的效率,结果表明,基于莫顿编码的八叉树数据结构具有更高的搜索效率,对于提高海量测深数据处理效率具有一定参考意义。
MBES(multi-beam echo sounder)data is significantly important in the research and application of underwater topography and landforms.To solve the problems of low efficiency of related algorithms in processing large volume of MBES data,an octree data structure based on Morton coding is proposed.Firstly,the space is divided according to the size of the bounding box and the maximum depth of the point cloud;then,each node is assigned an index value,and the index value is binary coded to establish an octree data structure based on Morton coding.Finally,take the SOR(statistical outlier removal)filtering experiment as an example to test the efficiency of the proposed data structure in rapid search in the neighborhood.The results show that the octree data structure based on Morton coding has higher search efficiency,which is of great significance for improving the processing efficiency of massive bathymetry data.
作者
许方正
卜宪海
屠泽杰
闫循鹏
XU Fangzheng;BU Xianhai;TU Zejie;YAN Xunpeng(College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590,China)
出处
《海洋测绘》
CSCD
北大核心
2023年第1期1-4,共4页
Hydrographic Surveying and Charting
基金
国家自然科学基金(41930535)。
关键词
海量测深数据
莫顿编码八叉树
数据结构索引
邻域快速搜索
SOR滤波
large volume of bathymetry point cloud
octree based on morton code
index of data structure
rapid neighborhood search
statistical outlier removal
