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Mathematical Problems in Engineering
Volume 2015, Article ID 164318, 8 pages
http://dx.doi.org/10.1155/2015/164318
Research Article

A Denoising Method for LiDAR Full-Waveform Data

1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
2Collaborative Innovation Center for Geospatial Technology, Wuhan 430072, China

Received 28 February 2015; Accepted 1 July 2015

Academic Editor: Ralph B. Dinwiddie

Copyright © 2015 Xudong Lai and Min Zheng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.