| 多值体素连通区域构建下的机载LIDAR数据三维平面提取 |
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| 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,2021,23(9):1598-1607. |
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| 作者姓名： | 王丽英 王鑫宁 |
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| 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 |
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| 基金项目： | 辽宁省教育厅科学技术研究项目(LJ2019JL015) |
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| 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,将传统的平面特征点聚类转换为基于体素的连通区域构建及空间约束下的反射强度值统计,给出了机载LIDAR点云数据的多值体素结构构建方案及其在此基础上的平面提取方案,有助于基于多值体素模型理论的机载LIDAR点云数据处理及应用的发展。算法具体实现过程为：① 将机载LIDAR点云数据规则化为多值体素结构,其中,体素值为体素内激光点的平均激光反射强度、曲率及法向量;② 在体素结构DSM数据中,选取小曲率体素作为种子,并标记与其空间连通且法向及激光反射强度均一致的连通区域为平面;③ 在体素结构非DSM数据中,将位于连通区域轮廓缓冲区内的激光反射强度满足统计特性的体素标记为平面。本文采用ISPRS提供的机载LIDAR实测数据测试提出算法的精度。定量评价的结果表明本文提出方法的质量和Kappa系数分别可达92.5%和89.4%,与传统仅采用几何特征的区域生长算法相比质量及Kappa系数分别提高了9.68%和11.62%。
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| 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 |
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| 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. |
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| Authors: | WANG Liying WANG Xinning |
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| Institution: | 1. School of Geomatics, Liaoning Technical University, Fuxin 123000, China2. Heilongjiang Institute of Geomatics Engineering, Harbin 150081, China |
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| 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. |
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| Keywords: | airborne LIDAR multi-valued voxel structure three-dimensional plane extraction regional growth spatially connected region normal consistency consistency of reflection intensity buffer analysis |
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