Paper Info
Title
Minimum description length constrained LiDAR waveform decomposition
Abstract
Waveform decomposition is a necessary step for the exploitation of full waveform LiDAR data. Much effort has been focused on designing algorithms to decompose the waveform into a fixed number of components. However, the determination of the appropriate number of components in a waveform, though crucial, is rarely studied. This paper introduces an order identification method, Minimum Description Length (MDL) to estimate the number of components. MDL requires the addition of a penalty term in the model fitness to account for the over-fitting of high order models. The convexity of MDL in terms of the number of components makes it possible to find out optimal model with 2-4 iterations in most cases. We applied the MDL-based estimation method to analyze a dataset collected by a Riegl Q680i LiDAR system. The procedure is demonstrated in this paper.
Year
DOI
Venue
2014
10.1109/IGARSS.2014.6946382
IGARSS
Keywords
DocType
ISSN
EM,constrained LiDAR waveform decomposition,Order Identification,full waveform LiDAR data,MDL-based estimation method,Riegl Q680i LiDAR system,remote sensing by laser beam,optical radar,Minimum Description Length,MDL,optimal model,Waveform,LiDAR,full waveform LiDAR systems
Conference
2153-6996
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Qing-Hua Li1156388.15
Serkan Ural2172.38
John Anderson333.76
J. Shan422020.08