孙美玲, 李永树, 陈强, 蔡国林. 基于迭代多尺度形态学开重建的城区LiDAR 滤波方法[J]. 红外与激光工程, 2015, 44(1): 363-369.
引用本文: 孙美玲, 李永树, 陈强, 蔡国林. 基于迭代多尺度形态学开重建的城区LiDAR 滤波方法[J]. 红外与激光工程, 2015, 44(1): 363-369.
Sun Meiling, Li Yongshu, Chen Qiang, Cai Guolin. Iterative multi-scale filter based on morphological opening by reconstruction for LiDAR urban data[J]. Infrared and Laser Engineering, 2015, 44(1): 363-369.
Citation: Sun Meiling, Li Yongshu, Chen Qiang, Cai Guolin. Iterative multi-scale filter based on morphological opening by reconstruction for LiDAR urban data[J]. Infrared and Laser Engineering, 2015, 44(1): 363-369.

基于迭代多尺度形态学开重建的城区LiDAR 滤波方法

Iterative multi-scale filter based on morphological opening by reconstruction for LiDAR urban data

  • 摘要: 针对形态学运算在机载LiDAR 滤波中最大窗口尺寸的选择问题,提出了一种基于形态学开重建的迭代多尺度点云滤波算法。通过循环迭代多尺度开重建运算,克服开重建对矮小地物的误判问题,自动获取开重建运算的最大窗口尺寸,解决了对城市区域滤波的窗口适宜尺寸选择问题,提高了地物与地面点分类的正确性。使用ISPRS 提供的城区样本测试数据开展实验,结果表明:其Ⅰ类、Ⅱ类及总误差均值分别达到3.10%、6.05%和4.11%,在Ⅱ类误差不显著增加的情况下,Ⅰ类误差和总误差均值同比均为最小,整体分类与自动识别性能优于常规滤波算法。

     

    Abstract: Aimed at the maximum window size problem of LiDAR morphological method on unknown region, a morphological filter of iterative multi-scale opening by reconstruction (IMORF) was proposed on the basis of traditional morphological filtering algorithms. Multi-scale opening by reconstruction (MORF) was utilized to get maximum window size automatically, which can help user settle the suitable window size problem of unknown region. MORF was used iteratively to settle the classification error of the low objects that were nearby high and large objects. The experimental results for ISPRS urban data show that IMORF can classify terrain and off-terrain points effectively, and the mean of TypeⅠ, Type Ⅱand total error are 3.10%, 6.05% and 4.11% respectively. Compared with other traditional filtering methods,the mean of Type ⅠError and Total Error of IMORF are minimum with Type ⅡError increased not obviously.

     

/

返回文章
返回