• DocumentCode
    133895
  • Title

    DEM extraction based on SFM using remote sensing images

  • Author

    Dong Ren ; Junqiao Zhang ; Shuanghui Lei ; Le Zhang ; Haiyang Yu

  • Author_Institution
    Coll. of Comput. & Inf. Technol., China Three Gorges Univ., Yichang, China
  • fYear
    2014
  • fDate
    3-7 Aug. 2014
  • Firstpage
    779
  • Lastpage
    783
  • Abstract
    Digital Elevation Model (DEM) extraction from unmanned aerial vehicles is one of focal points in remote sensing image processing. This paper built point clouds based on Structure From Motion (SFM) techniques firstly, then excluded the outliers from the point clouds, and finally generated the regular grid DEM through different interpolation methods. At the same time, the paper proposed an improved inverse distance weighted interpolation method based on the exponent p of weighting function. As seen in the experimental results evaluated by checkpoint method, the improved inverse distance weighted interpolation got the higher accuracy than inverse distance weighted interpolation. The followed was nearest neighbor interpolation. The moving average interpolation performed the worst. The results indicated that the improved interpolation method was an effective way to extract DEM using photogrammetry techniques.
  • Keywords
    digital elevation models; feature extraction; geophysical image processing; image motion analysis; interpolation; remote sensing; DEM extraction; SFM; checkpoint method; digital elevation model; improved inverse distance weighted interpolation method; photogrammetry techniques; point clouds; remote sensing image processing; structure from motion; weighting function; Agriculture; Cameras; Feature extraction; Interpolation; Remote sensing; Three-dimensional displays; Unmanned aerial vehicles; DEM; UAV; interpolation method; inverse distance weighted interpolation; structure from motion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    World Automation Congress (WAC), 2014
  • Conference_Location
    Waikoloa, HI
  • Type

    conf

  • DOI
    10.1109/WAC.2014.6936148
  • Filename
    6936148