Analysis of Airborne LiDAR Point Clouds With Spectral Graph Filtering

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Bayram E., Frossard P., Vural E., Alatan A. A.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, vol.15, pp.1284-1288, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 15
  • Publication Date: 2018
  • Doi Number: 10.1109/lgrs.2018.2834626
  • Journal Name: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1284-1288
  • Keywords: Airborne laser scanning, graph signal processing, light detection and ranging (LiDAR) filtering, spectral graph filtering, unorganized 3-D point cloud, MORPHOLOGICAL FILTER, ALGORITHMS, GENERATION
  • Middle East Technical University Affiliated: Yes

Abstract

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.