基于建筑物激光点云边缘线自动提取提高DSM精度  

Digital Surface Model Accuracy Improvement Based on Edge Line Automatic Extraction of Building Laser Point Cloud

作　　者：苗松 王建军[1] 李云龙[1] 范媛媛 

机构地区：[1]山东理工大学机械工程学院,山东淄博255049 [2]新泽西理工大学交通工程系,新泽西州纽瓦克07102

出　　处：《激光与光电子学进展》2018年第1期393-399,共7页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(51575326);国家留学基金(201508370010);山东省自然科学基金教育厅联合专项(ZR2014JL027);山东省青年教师成长计划项目(2015);山东理工大学博士科研基金(4041-413028)

摘　　要：在机载激光雷达扫描过程中,建筑物背面的地面边缘线常常被遮挡,无法获取精确的建筑物背面边缘点信息,在利用获得的激光点云进行三维重建时,使得创建数字表面模型(DSM)的精度较低。为消除背面边缘点缺失造成的DSM精度降低,提出了一种建筑物地面缺失边缘线的自动提取算法;通过提取建筑物侧面和地面局部点云的拟合趋势面,计算两相邻局部趋势面的交线,并补充缺失部分的边缘点数据;最后采用补充了边缘点的建筑物激光点云重建了建筑物的DSM,并对边缘点补充前后的DSM精度进行了对比仿真实验。仿真结果表明,通过提取和补充建筑物的边缘点可有效提高建筑物重建DSM的高程精度。During the scanning process of airborne laser radar （LiDAR）, ground edge line in the back of the building is always shaded, edge point data of building surface are usually hard to be obtained accurately, so a digital surface model （DSM） with low precision is obtained by three dimensional reconstruction with these low accurate LiDAR point cloud data. In order to improve the DSM accuracy, we propose an edge line automatic extraction algorithm. This approach initially extracts local point cloud of building surface edge to fit local trend surface. Then two neighborhood trend surfaces are used to compute the interseetion＇s equation and add edge point cloud data. Finally, using the laser point cloud of the building with the additional extracted edge points, we rebuilt the DSM of the building, and the accuracy of the reconstructed DSM with adding the edge points is compared with that of the DSM without adding the edge points. Simulated results show that the accuracy of the DSM reconstructed by this method can be improved significantly.

关 键 词：遥感 机载激光雷达 数字表面模型 表面边缘点 局部趋势面 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]