Analysis of Airborne LiDAR Point Clouds With Spectral Graph Filtering

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2018-08-01

Author

Bayram, Eda
Frossard, Pascal
Vural, Elif
Alatan, Abdullah Aydın

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Separation of ground and nonground measurements is an essential task in the analysis of light detection and ranging (LiDAR) point clouds; however, it is challenge to implement a LiDAR filtering algorithm that integrates the mathematical definition of various landforms. In this letter, we propose a novel LiDAR filtering algorithm that adapts to the irregular structure and 3-D geometry of LiDAR point clouds. We exploit weighted graph representations to analyze the 3-D point cloud on its original domain. Then, we consider airborne LiDAR data as an irregular elevation signal residing on graph vertices. Based on a spectral graph approach, we introduce a new filtering algorithm that distinguishes ground and nonground points in terms of their spectral characteristics. Our complete filtering framework consists of outlier removal, iterative graph signal filtering, and erosion steps. Experimental results indicate that the proposed framework achieves a good accuracy on the scenes with data gaps and classifies the nonground points on bridges and complex shapes satisfactorily, while those are usually not handled well by the state-of-the-art filtering methods.

Subject Keywords

Geotechnical Engineering and Engineering Geology, Electrical and Electronic Engineering, Airborne laser scanning, Graph signal processing, Light detection and ranging (LiDAR) filtering, Spectral graph filtering, Unorganized 3-D point cloud

URI

https://hdl.handle.net/11511/35378

Journal

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS

DOI

https://doi.org/10.1109/lgrs.2018.2834626

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

E. Bayram, P. Frossard, E. Vural, and A. A. Alatan, “Analysis of Airborne LiDAR Point Clouds With Spectral Graph Filtering,” IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, pp. 1284–1288, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35378.