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Enhanced Component Detection Algorithm of Full-waveform Lidar Data : Volume Xl-1/W1, Issue 1 (02/05/2013)

By Zhou, M.

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Book Id: WPLBN0004014360
Format Type: PDF Article :
File Size: Pages 5
Reproduction Date: 2015

Title: Enhanced Component Detection Algorithm of Full-waveform Lidar Data : Volume Xl-1/W1, Issue 1 (02/05/2013)  
Author: Zhou, M.
Volume: Vol. XL-1/W1, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus Publications
Publication Date:
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Zhang, Z., Wang, J. H., Liu, M. H., & Zhou, M. (2013). Enhanced Component Detection Algorithm of Full-waveform Lidar Data : Volume Xl-1/W1, Issue 1 (02/05/2013). Retrieved from

Description: Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China. When full-waveform LiDAR (FW-LiDAR) data are applied to extract the component feature information of interest targets, there exist a problem of components lost during the waveform decomposition procedure, which severely constrains the performance of subsequent targets information extraction. Focusing on the problem above, an enhance component detection algorithm, which combines Finite Mixed Method (FMM), Levenberg-Marquardt (LM) algorithm and Penalized Minimum Matching Distance (PMMD),is proposed in this paper. All of the algorithms for parameters initialization, waveform decomposition and missing component detection have been improved, which greatly increase the precision of component detection, and guarantee the precision of waveform decomposition that could help the weak information extraction of interest targets. The effectiveness of this method is verified by the experimental results of simulation and measured data.



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