NDLI: Urban extraction from SAR images using local statistical characteristics and gaussian markov random field mod

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Proceedings of Third International Conference on Signal Processing (ICSP'96)

Urban extraction from SAR images using local statistical characteristics and gaussian markov random field mod

Content Provider	IEEE Xplore Digital Library
Author	Gui-song Xia Chu He Lei Yu
Copyright Year	2006
Description	Author affiliation: Signal Process. Lab., Wuhan Univ. (Gui-song Xia; Chu He; Lei Yu)
Abstract	As synthesis aperture radar (SAR) represents a powerful Earth observation tool for monitoring geophysical resource globally, SAR images could be used for land description and scene analysis. Actually, various applications specifically require the detection and the analysis of urban areas from original SAR images, which is a difficult task due to the speckle signal of the images and the complexity of these scenes. In this paper, an unsupervised approach to extract urban areas from SAR images has been suggested based on local statistical characteristics and texture information described by Gaussian Markov Random field (MRF) model. First, a probability map of the urban areas is computed based on local statistical characteristics, using an ffmax operator proposed by C. Gouinaud. Then the Gaussian MRF model is adopted to describe the texture of urban zones and the parameters of the model are estimated from the original image together with the probability map. Finally, the urban areas are extracted under Bayesian framework by maximum a posterior (MAP) criterion, with modeling the urban label field by Potts model. The performance of the proposed method is evaluated by experimental results on real SAR images
File Size	523279
File Format	PDF
ISBN	0780397363
DOI	10.1109/ICOSP.2006.345576
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Markov random fields Urban areas Synthetic aperture radar Image analysis Probability Radar imaging Earth Monitoring Radar detection Signal analysis
Content Type	Text
Resource Type	Article

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