基于形态学与区域生长的机载LiDAR点云数据滤波  

Filtering of Airborne LiDAR Point Cloud Data Based on Mathematical Morphology and Region Growing

作　　者：谷延超[1,2] 范东明[1,2] 余彪[1,2] 张金花[3] 

机构地区：[1]西南交通大学地球科学与环境工程学院,成都市高新区西部园区611756 [2]西南交通大学高速铁路运营安全空间信息技术国家地方联合工程实验室,成都市高新区西部园区611756 [3]四川省第三测绘工程院,成都市新军街2号610500

出　　处：《大地测量与地球动力学》2015年第5期811-815,共5页Journal of Geodesy and Geodynamics

基　　金：测绘地理信息公益性行业科研专项经费(201412010);四川省测绘地理信息局科技计划(J2013ZH02);长江学者和创新团队发展计划(IRT13092)

摘　　要：针对形态学滤波存在的地形过度腐蚀以及区域生长滤波需要大量地面种子点的问题,提出一种点云数据由粗到精的两级滤波策略。对机载LiDAR点云数据进行多尺度形态学滤波得到粗略DEM("粗滤波"),由此可提供大量的地面种子点用于区域生长,进而得到精细DEM("精滤波")。利用ISPRS提供的滤波数据进行测试,结果表明,该滤波算法对地形适应性较强,可有效保证地形特征,具有更好的稳健性。According to the phenomenon that a morphological filter erodes terrain excessively and the demand of seed ground points for region growing,a two-stage ＂rough-refined＂filtering strategy is proposed.First,a rough digital elevation model（DEM）is obtained by applying a multi-scale morphological filter to airborne LiDAR data,which is called rough filter.Then,region growing is applied to gain refined DEM based on the seed ground points derived from the rough DEM.When tested against the ISPRS LiDAR reference datasets,the experiment shows that the proposed algorithm is highly adaptable to various landscapes in reserving the detail of terrain effectively,and also is more robust.

关 键 词：机载LIDAR 多尺度形态学 区域生长 滤波 

分 类 号：P237.3[天文地球—摄影测量与遥感]