DocumentCode :
1345053
Title :
Detection of linear features in SAR images: application to road network extraction
Author :
Tupin, Florence ; Maitre, Henri ; Mangin, Jean-Francois ; Nicolas, Jean-Marie ; Pechersky, Eugene
Author_Institution :
Ecole Nat. Superieure des Telecommun., Paris, France
Volume :
36
Issue :
2
fYear :
1998
fDate :
3/1/1998 12:00:00 AM
Firstpage :
434
Lastpage :
453
Abstract :
The authors propose a two-step algorithm for almost unsupervised detection of linear structures, in particular, main axes in road networks, as seen in synthetic aperture radar (SAR) images. The first step is local and is used to extract linear features from the speckle radar image, which are treated as road-segment candidates. The authors present two local line detectors as well as a method for fusing information from these detectors. In the second global step, they identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects. The influence of the parameters on the road detection is studied and results are presented for various real radar images
Keywords :
Markov processes; feature extraction; geophysical signal processing; geophysical techniques; image segmentation; radar imaging; remote sensing by radar; synthetic aperture radar; Markov random field; SAR; SAR image processing; contextual knowledge; geophysical measurement technique; image segmentation; land surface; linear feature extraction; linear structure; radar imaging; radar remote sensing; road network; speckle radar image; synthetic aperture radar; terrain mapping; two-step algor; unsupervised detection; Computer vision; Data mining; Detectors; Feature extraction; Image segmentation; Radar detection; Radar imaging; Roads; Speckle; Synthetic aperture radar;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/36.662728
Filename :
662728
Link To Document :
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