基于改进的数学形态学算法的LiDAR点云数据滤波  

Filtering of Airborn LiDAR Point Cloud Data Based on the Adaptive Mathematical Morphology

作　　者：隋立春[1] 张熠斌[1] 柳艳[1] 曲佳[1] 李伟[1] 王蒙[1] 李智临[1] 

机构地区：[1]长安大学地质工程与测绘学院,陕西西安710054

出　　处：《测绘学报》2010年第4期390-396,共7页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(40971306;40974010);国土资源大调查项目(1212010914015)

摘　　要：数学形态学在数字图像处理中有广泛的应用。首先介绍传统数学形态学算法的特点,对这一理论用于LiDAR点云数据滤波的不足进行了分析。在此基础上,对相应的算法进行扩展和改进,提出针对不同地形特点的自适应滤波算法。在数学形态学"开"算子的基础上,提出增加一个"带宽"参数用于点云数据滤波的方法。最后利用三组实际点云数据进行试验,以验证这一算法的有效性。Mathematical morphology is widely used in the digital image processing.In this paper,the characteristics of traditional mathematical morphology algorithm are introduced and the shortages of the application of this theory in the LiDAR point cloud data filtering are analyzed first.Then,on this basis,the corresponding morphological algorithms are efficiently improved and extended,and an adaptive filtering algorithm which is aimed at the characteristics of different terrain surfaces is proposed.Based on the ＂opening＂ operator of mathematical morphological,a method that a ＂bandwidth＂ parameter is added for the filtering of LiDAR point cloud is proposed.Finally,experiments are processed using three groups of actual LiDAR point cloud data and the validity of the algorithm is validated by the different presentation forms from them.

关 键 词：数学形态学 LiDAR点云数据 开算子 动态滤波 

分 类 号：P237[天文地球—摄影测量与遥感]