Volume 44 Issue 1
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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.

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

  • Received Date: 2014-05-13
  • Rev Recd Date: 2014-06-15
  • Publish Date: 2015-01-25
  • 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.
  • [1] Sithole G, Vosselman G. Experimental comparison of filter algorithms for bare-earth extraction from airborne laser scanning point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2004, 59(1-2): 85-101.
    [2]
    [3] Huang Xianfeng, Li Hui, Wang Xiao, et al. Filter algorithms of airborne liDAR data: review and prospects [J]. Acta Geodaetica et Cartographica Sinica, 2009, 38(5): 466-469. (in Chinese) 黄先锋, 李卉, 王潇, 等. 机载LiDAR 数据滤波方法评述[J]. 测绘学报, 2009, 38(5): 466-469.
    [4]
    [5]
    [6] Meng X, Currit N, Zhao K. Ground filtering algorithms for airborne liDAR data: a review of critical issues [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2010, 2 (3): 833-860.
    [7]
    [8] Axelsson P. DEM generation from laser scanner data using adaptive TIN models [J]. International Archives of Photogrammetry and Remote Sensing,2000, 33 (B4/1): 110-117.
    [9]
    [10] Sun Chongli. Improved hierarchical moving curved filtering method of liDAR data [J]. Infrared and Laser Engineering, 2013, 42(2): 349-354. (in Chinese) 孙崇利. 改进的多级移动曲面拟合激光雷达数据滤波方法[J]. 红外与激光工程, 2013, 42(2): 349-354.
    [11]
    [12] Chen Q. Filtering airborne laser scanning data with morphological methods [J]. Photogrammetric Engineering and Remote Sensing, 2007, 73(2): 175-185.
    [13]
    [14] Shao Y. Ground point selection and building detection from airborne LiDAR data [D]. Taiwan: National Central University, 2007.
    [15] Zhang K, Chen S C, Whitman D, et al. A progressive morphological filter for removing nonground measurement from LIDAR data [J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(4): 872-882.
    [16]
    [17]
    [18] Shen Jing. Airborne LiDAR data filtering by morphological reconstruction method [J]. Geomatics and Information Science of Wuhan University, 2011, 36(2): 167-175. (in Chinese) 沈晶. 用形态学重建方法进行机载LiDAR 数据滤波[J]. 武汉大学学报信息科学版, 2011, 36(2): 167-170.
    [19] Mongus D, Falik B. Parameter-free ground filtering of LiDAR data for automatic DTM generation [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 67: 1-12.
    [20]
    [21]
    [22] Thomas J Pingel, Keith C Clarke, William A McBride. An improved simple morphological filter for the terrain classification of airborne LiDAR data [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 77: 21-30.
    [23]
    [24] Soille P. Morphological Image Analysis, Principles and Applications[M]. 2nd ed. Berlin: Springer-Verlag, 2003.
    [25]
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Iterative multi-scale filter based on morphological opening by reconstruction for LiDAR urban data

  • 1. Faculty of Geosciences and Environmental Engineering,Southwest Jiaotong University,Chengdu 610031,China

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.

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