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A Denoising Method for LiDAR Full-Waveform Data

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  • Xudong Lai
  • Min Zheng

Abstract

Decomposition of LiDAR full-waveform data can not only enhance the density and positioning accuracy of a point cloud, but also provide other useful parameters, such as pulse width, peak amplitude, and peak position which are important information for subsequent processing. Full-waveform data usually contain some random noises. Traditional filtering algorithms always cause distortion in the waveform. filtering algorithm is based on Mean Shift method. It can smooth the signal iteratively and will not cause any distortion in the waveform. In this paper, an improved filtering algorithm is proposed, and several experiments on both simulated waveform data and real waveform data are implemented to prove the effectiveness of the proposed algorithm.

Suggested Citation

  • Xudong Lai & Min Zheng, 2015. "A Denoising Method for LiDAR Full-Waveform Data," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-8, July.
    • Handle: RePEc:hin:jnlmpe:164318
    DOI: 10.1155/2015/164318
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