Detection of linear features in SAR images: application to road network extraction

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...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 1998-03, Vol.36 (2), p.434-453
Main Authors: Tupin, F., Maitre, H., Mangin, J.-F., Nicolas, J.-M., Pechersky, E.
Format: Article
Language:English
Subjects:
Computer vision
Data mining
Detectors
Feature extraction
Image segmentation
Radar detection
Radar imaging
Roads
Speckle
Synthetic aperture radar
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Summary: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.
ISSN:0196-2892
1558-0644
DOI:10.1109/36.662728