• DocumentCode
    179017
  • Title

    A Filtering Algorithm of Airborne LiDAR Points Cloud Based on Least Square

  • Author

    Cheng Yinglei ; Zhao Huizhen ; Qu Yayun ; Qiu Langbo

  • Author_Institution
    Inf. & Navig. Inst., Air Force Eng. Univ., Xi´an, China
  • fYear
    2014
  • fDate
    15-16 June 2014
  • Firstpage
    24
  • Lastpage
    27
  • Abstract
    Filtering algorithm based on least square method can get digital elevation model of high precision, but the filtering effect is poor if non-ground point set is big. In order to solve this problem, points of smaller elevation are used to initial curved surface fitting, which has smaller calculation compared with fitting by all points. The curved surface is closer to the ground, making it conducive to the subsequent iteration. Only ground point set is processed in the subsequent iteration, so the processing is simple. The experimental results show that the algorithm has smaller error and can filter out large part of non-ground points effectively.
  • Keywords
    curve fitting; digital elevation models; filtering theory; iterative methods; least squares approximations; optical radar; airborne LiDAR points cloud; digital elevation model; filtering algorithm; iteration; least square method; Algorithm design and analysis; Filtering; Filtering algorithms; Fitting; Laser radar; Surface fitting; Three-dimensional displays; Filtering; Least Square; Lidar; Points Cloud;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Engineering Applications (ISDEA), 2014 Fifth International Conference on
  • Conference_Location
    Hunan
  • Print_ISBN
    978-1-4799-4262-6
  • Type

    conf

  • DOI
    10.1109/ISDEA.2014.14
  • Filename
    6977537