基于多尺度的城区机载点云滤波方法研究  

Lidar-driven multi-scale filtering algorithm in urban areas

作　　者：钟良[1] 汤璇[2] 管海燕[3] 邬建伟[4] 

机构地区：[1]长江委长江空间信息技术工程有限公司,武汉430010 [2]武汉军械士官学校计算机系,武汉430075 [3]加拿大滑铁卢大学地理与环境学院 [4]武汉大学遥感信息工程学院,武汉430079

出　　处：《计算机工程与应用》2014年第13期205-209,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.41001257)

摘　　要：针对城市地区机载激光扫描数据(ALS)中提取数字地面模型这一问题,提出了一种基于多尺度的由粗到细的滤波算法。通过计算每个点与其周围一定邻域内激光点的几何特征值关系,将点云粗分类为平面点、边缘点和离散点;对平面点进行区域跟踪,利用强度方差将平面点分类为地面点、建筑物点以及未确定类别点;对地面点构建Delaunay三角网,反向分析未确定点以及边缘点来加密地面点集。通过实验验证了该算法对城市地区滤波的有效性。To tackle the problems on the generation of Digital Elevation Model（DEM）in urban areas, this paper proposes lidar-driven multi-scale filtering algorithm. By analyzing and calculating spatial geometric relationships of each point in a certain neighbourhood it firstly classify point clouds into three basic classes（planar, edge, and discrete points）. Thanks to urban areas featured by relatively flat piecewise planes, the planar points are further processed to obtain building, on-ground and uncertain points using region growing and global height thresholds. To improve the DEM accuracy, a Delaunay triangular network of the filtered on-ground points is built to backward search possible on-ground points in edge and uncertain points. The experiments of ISPRS datasets validate the effectiveness and robustness of the proposed coarse-to fine multi-scale filtering algorithm in urban areas.

关 键 词：机载激光扫描 离散度 高程 区域增长 后向加密 

分 类 号：TP237.3[自动化与计算机技术—检测技术与自动化装置]