摘要
在分析激光雷达点云空间分布特征的基础上,提出了基于斜率的激光点云平面拟合过滤算法,并利用该算法对机载激光雷达点云的特征提取进行了实验研究。结果表明,此算法能有效地拟合激光点云的连续平滑的水平平面、倾斜平面和垂直平面,在DTM、建筑屋顶和垂直墙壁等特征提取中具有较好的效果。
LIDAR is a new technology for obtaining instantly the accurate 3D information of ground and objects. A slope-based planar-fitting filtering algorithm of LIDAR point cloud is presented based on the analysis of the spatial distribution feature of LIDAR point cloud. This algorithm is used for the experimental research of feature extraction of airborne LIDAR point cloud. The experimental result shows that this algorithm is able to fit effectively continual and smooth horizontal planes, slope planes and vertical planes, and has preferable effects in the feature extraction of DTM, building tops and vertical walls.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2008年第1期25-28,共4页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(40401050,60670253)
上海市重点学科建设资助项目(T0102)
上海市博士后专项基金资助项目(05R214123,06R214129)
关键词
激光雷达
平面拟合
过滤
特征提取
LIDAR
planar-fitting
filtering
feature extraction
