Zhou, Guangyi, Cui, Yi, Chen, Yilun, Yang, Jian, Rashvand, Habib F. and Yamaguchi, Yoshio (2011) Linear feature detection in polarimetric SAR images. IEEE Transactions on Geoscience and Remote Sensing, Volume 49 (Number 4). pp. 1453-1463. doi:10.1109/TGRS.2010.2081373 ISSN 0196-2892.

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Abstract

Recently, the use of linear features for processing remote-sensing images has shown its importance in applications. Unfortunately, traditional linear feature detection methods rely heavily on the image's local information which makes them vulnerable to the presence of noise in the image. This problem becomes particularly difficult for synthetic aperture radar (SAR) image applications where SAR images are corrupted by speckle noise. In order to overcome this problem, we propose a novel method that processes the polarimetric synthetic aperture radar (Pol-SAR) images by combining the multiscale image analysis with polarimetric information in a new fashion. A two-scale approach is adopted here. On a coarse level, the coarse regions of the linear features are extracted by a curvelet transform from a speckle noise reduced image obtained by the polarimetric whitening filter. On a fine level, we develop a fuzzy polarimetric detector to accurately locate the linear features inside the regions. The effectiveness of the proposed method is demonstrated using simulated Pol-SAR data acquired from both EMISAR and Convair-580 systems.

Item Type:	Journal Article
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH):	Image processing, Synthetic aperture radar
Journal or Publication Title:	IEEE Transactions on Geoscience and Remote Sensing
Publisher:	IEEE
ISSN:	0196-2892
Official Date:	April 2011
Dates:	Date Event April 2011 Published
Volume:	Volume 49
Number:	Number 4
Page Range:	pp. 1453-1463
DOI:	10.1109/TGRS.2010.2081373
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC)
Grant number:	40871157 (NSFC)

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