Laser & Optoelectronics Progress, Volume. 61, Issue 18, 1815005(2024)

Airborne Laser Point-Cloud Filtering in Complex Mountainous Terrain Utilizing Deep Global Information Fusion

Jierui Cui1,3, Yunwei Pu1,2、*, Yan Xia3, and Yichen Liu3
Author Affiliations
  • 1Faculty of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
  • 2Computing Center, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
  • 3Yunnan Water Conservancy and Hydropower Survey and Design Institute, Kunming 650021, Yunnan, China
  • show less
    References(23)

    [4] Guo J J, Chen C F, Yao X et al. A multi-feature clustering-based hierarchical filtering method for airborne LiDAR point clouds in complex landscapes[J]. Acta Geodaetica et Cartographica Sinica, 52, 1724-1737(2023).

    [5] Vosselman G. Slope based filtering of laser altimetry data[J]. International Archives of Photogrammetry and Remote Sensing, 33, 678-684(2000).

    [7] Axelsson P. DEM generation from laser scanner data using adaptive TIN models[J]. International Archives of Photogrammetry and Remote Sensing, 33, 110-117(2000).

    [11] Tao Z Y, Su J Q, Dong C Y et al. 3D LiDAR based on improved density clustering research on point cloud filtering algorithm[J]. Applied Laser, 43, 87-93(2023).

    [16] Dai L B, Wan Y, Zhang Y J. LiDAR point clouds filtering in urban areas based on multi-scale semantic segmentation[J]. Journal of Geomatics, 48, 68-72(2023).

    Tools

    Get Citation

    Copy Citation Text

    Jierui Cui, Yunwei Pu, Yan Xia, Yichen Liu. Airborne Laser Point-Cloud Filtering in Complex Mountainous Terrain Utilizing Deep Global Information Fusion[J]. Laser & Optoelectronics Progress, 2024, 61(18): 1815005

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Machine Vision

    Received: Feb. 5, 2024

    Accepted: Mar. 7, 2024

    Published Online: Sep. 14, 2024

    The Author Email: Yunwei Pu (puyunwei@126.com)

    DOI:10.3788/LOP240669

    CSTR:32186.14.LOP240669

    Topics