Infrared and Laser Engineering, Volume. 52, Issue 11, 20230212(2023)

Airborne LiDAR data classification method combining physical and geometric characteristics

Yiqiang Zhao1,2, Qi Zhang1,2, Changlong Liu3,4, Weikang Wu3,4, and Yao Li1,2、*
Author Affiliations
  • 1School of Microelectronics, Tianjin University, Tianjin 300072, China
  • 2Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin University, Tianjin 300072, China
  • 3Microsystem Center, The 54st Institute of China Electronics Technology Group Corporation, Shijiazhuang 050081, China
  • 4National Engineering Research Center for Communication Software and Special Integrated Circuit Design, Shijiazhuang 050081, China
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    References(18)

    [1] K Zhang, L J Ye, X Wen, et al. A dual attention neural network for airborne LiDAR point cloud semantic segmentation. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-17(2022).

    [4] W Li, Z Luo, Z Xiao, et al. A GCN-based method for eextracting power lines and pylons from airborne LiDAR data. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-14(2022).

    [8] [8] Zhu Shixian. Research on Critical Technology of Intensity Imaging of 905nm Pulsed Li DAR[D]. Tianjin: Tianjin University, 2018.

              Zhu Shixian. Research on critical technology of intensity imaging of 905 nm pulsed LiDAR[D]. Tianjin: Tianjin University, 2018. (in Chinese)

    [9] [9] les R Q, Hao S, Mo K C, et al. Point: deep learning on point sets f 3D classification segmentation[C]2017 IEEE Conference on Computer Vision Pattern Recognition, 2017: 7785.

    [10] [10] Qi C R, Yi L, Su H, et al. Point++: Deep hierarchical feature learning on point sets in a metric space[C]Advances in Neural Infmation Processing Systems, 2017: 5099–5108.

    [11] [11] Hu Q, Yang B, Xie L, et al. RLA: Efficient semantic segmentation of largescale point clouds [C]2020 IEEECVF Conference on Computer Vision Pattern Recognition (CVPR), 2020: 1110511114.

    [16] [16] Shinohara T, Xiu H, Matsuoka M, et al. Semantic segmentation f fullwavefm LiDAR data using local hierarchical global feature extraction[C]Sigspatial''20: 28th International Conference on Advances in Geographic Infmation Systems, 2020: 640–650.

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    Yiqiang Zhao, Qi Zhang, Changlong Liu, Weikang Wu, Yao Li. Airborne LiDAR data classification method combining physical and geometric characteristics[J]. Infrared and Laser Engineering, 2023, 52(11): 20230212

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    Paper Information

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    Received: Apr. 10, 2023

    Accepted: --

    Published Online: Jan. 8, 2024

    The Author Email: Li Yao (liyao@tju.edu.cn)

    DOI:10.3788/IRLA20230212

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