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Journal of Applied Remote Sensing

Graph-connected components for filtering urban LiDAR data
Author(s): Yassine Belkhouche; Prakash Duraisamy; Bill Buckles
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Paper Abstract

A graph-based approach for modeling and solving the LiDAR filtering problem in urban areas is established. Our method consists of three steps. In the first step, we construct a graph-based representation of the LiDAR data, where either the Delaunay triangulation or the K-nearest neighbors graph is used. Given a set of features extracted from LiDAR data, we introduce an algorithm to label the edges of this graph. In this second step, we define criteria to eliminate some of the graph edges and then use a connected components algorithm to detect the different components in the graph representation. Finally, these components are classified into terrain or objects. Different datasets with different characteristics have been used to analyze the performance of our method. We compared our method against two other methods, and results show that our method outperforms the other methods in most tests cases.

Paper Details

Date Published: 10 March 2015
PDF: 13 pages
J. Appl. Rem. Sens. 9(1) 096075 doi: 10.1117/1.JRS.9.096075
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Yassine Belkhouche, Univ. of Arkansas at Little Rock (United States)
Prakash Duraisamy, Rochester Institute of Technology (United States)
Bill Buckles, Univ. of North Texas (United States)

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