NDLI: Particle filter based approach to road detection in multiband SAR images

Content Provider	IEEE Xplore Digital Library
Author	Qiming Deng Lining Gao Jian Yang
Copyright Year	2009
Description	Author affiliation: Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China (Qiming Deng; Lining Gao; Jian Yang)
Abstract	Synthetic aperture radar (SAR) images are widely used for aerial and spatial image applications, such as terrain classification, target detection, etc. SAR images in different bands can provide multi-spectrum information, which is beneficial for more accurate target observation. In this paper, a new method is proposed for joint detection of roads in multiband SAR images. First, the multi-segmented polyline model is introduced to provide a more accurate description of road curve. Then, the roads in SAR images are extracted in a Bayesian tracking framework, and the particle filtering algorithm is employed to implement the tracking. Finally, a joint detection method is proposed to determine the optimal weights of particles based on the maximum likelihood (ML) criterion. The effectiveness of the proposed method is demonstrated by experimental results with real multiband SAR data.
Starting Page	684
Ending Page	688
File Size	344497
Page Count	5
File Format	PDF
ISBN	9781424427314
DOI	10.1109/APSAR.2009.5374111
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood detection Roads Radar tracking Synthetic aperture radar (SAR) road detection particle filter Data mining Particle tracking Bayesian methods Radar detection Object detection Particle filters multiband Synthetic aperture radar
Content Type	Text
Resource Type	Article

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