基于改进的数学形态学算法的LiDAR点云数据滤波被引量：84

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

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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.

作者隋立春张熠斌柳艳曲佳李伟王蒙李智临

机构地区长安大学地质工程与测绘学院

出处《测绘学报》 EI CSCD 北大核心 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)

关键词数学形态学 LiDAR点云数据开算子动态滤波 mathematical morphology LiDAR point cloud data opening operator adaptive filtering

分类号 P237 [天文地球—摄影测量与遥感]

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