首页 | 本学科首页   官方微博 | 高级检索  
     

多值体素连通区域构建下的机载LIDAR数据三维平面提取
引用本文:王丽英,王鑫宁. 多值体素连通区域构建下的机载LIDAR数据三维平面提取[J]. 地球信息科学学报, 2021, 23(9): 1598-1607. DOI: 10.12082/dqxxkx.2021.200579
作者姓名:王丽英  王鑫宁
作者单位:1. 辽宁工程技术大学测绘与地理科学学院,阜新 1230002. 黑龙江地理信息工程院,哈尔滨 150081
基金项目:辽宁省教育厅科学技术研究项目(LJ2019JL015)
摘    要:
针对现有的面向机载LIDAR数据的三维平面提取算法存在的基于离散激光点设计导致算法设计困难、仅利用几何特征的一致性导致的在平面平滑过渡区域易产生错误提取的问题,本文提出了一种多值体素连通区域构建下的机载LIDAR三维平面提取方法.该算法基于体素结构设计且综合利用了机载LIDAR数据的几何、激光反射强度信息,将传统的平面...

关 键 词:机载激光雷达  多值体素结构  三维平面提取  区域增长  空间连通区域  法向一致性  反射强度一致性  缓冲区分析
收稿时间:2020-10-08

Multi-value Voxel Connected Region Construction based on 3D Plane Extraction for Airborne LIDAR Data
WANG Liying,WANG Xinning. Multi-value Voxel Connected Region Construction based on 3D Plane Extraction for Airborne LIDAR Data[J]. Geo-information Science, 2021, 23(9): 1598-1607. DOI: 10.12082/dqxxkx.2021.200579
Authors:WANG Liying  WANG Xinning
Affiliation:1. School of Geomatics, Liaoning Technical University, Fuxin 123000, China2. Heilongjiang Institute of Geomatics Engineering, Harbin 150081, China
Abstract:
The traditional 3D plane extraction algorithm for airborne LIDAR data have defects. For example, designing on discrete LIDAR points leads to difficulties in the design of point-based plane extraction methods. It is easy to generate false detection in the smooth transition region of plane by using only the consistency of geometric features. To overcome the above restrictions, a new 3D plane detection algorithm for airborne LIDAR data was developed based on multi-value voxel connected region construction method. The proposed algorithm is designed based on voxel structure and makes comprehensive use of the geometry and the reflection intensity formation from airborne LIDAR data. It converts the traditional plane feature point clustering into connected region construction based on voxel and reflection intensity statistics under spatial constraints. It gives the multi-valued voxel structure construction scheme of airborne LIDAR point cloud data and the planar extraction scheme on this basis, which contributes to the development of airborne LIDAR point cloud data processing and application based on the theory of multi-valued voxel model. The specific implementation process of the algorithm is showed as follows: ① The airborne LIDAR point cloud data is regularized to a multi-valued voxel structure, where voxel value is the average laser reflection intensity, curvature, and normal vector of the LIDAR point(s) within the voxel. ② In the DSM data of voxel structure, voxels with smaller curvature are selected as seeds, and then the seeds and their 3D connected regions, which are connected with the seeds and have similar reflection intensity and normal, are labelled as the plane. ③ In the non-DSM data of voxel structure, the voxels located in the contour buffer of the connected region with laser reflection intensity satisfying statistical characteristics are labeled as planes. In this paper, airborne LIDAR data provided by ISPRS were used to test the accuracy of the proposed algorithm. The quantitative evaluation results showed that the quality and Kappa coefficient of the proposed method were 92.5% and 89.4%, respectively, which were 9.68% and 11.62% higher than that of the traditional region-growing algorithm using only geometric features.
Keywords:airborne LIDAR  multi-valued voxel structure  three-dimensional plane extraction  regional growth  spatially connected region  normal consistency  consistency of reflection intensity  buffer analysis  
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《地球信息科学学报》浏览原始摘要信息
点击此处可从《地球信息科学学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号