Unsupervised multiscale oil slick segmentation from SAR images using a vector HMC model

DOI10.1016/J.PATCOG.2006.04.032zbMath1119.68170OpenAlexW2027807519MaRDI QIDQ856490

Grégoire Mercier, Stéphane Derrode

Publication date: 7 December 2006

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2006.04.032

zbMATH Keywords

synthetic aperture radarunsupervised segmentationHidden Markov chainmultiscale wavelet analysisoil slick detection

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (3)

Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise ⋮ On convergence of the iterative conditional estimations ⋮ Sea SAR images analysis to detect oil slicks in Algerian coasts

Cites Work

• Unique reconstruction of band-limited signals by a Mallat-Zhong wavelet transform algorithm
• Blind separation of sources. I: An adaptive algorithm based on neuromimetic architecture
• Independent component analysis, a new concept?
• A theory for multiresolution signal decomposition: the wavelet representation
• Baum's forward-backward algorithm revisited
• Ten Lectures on Wavelets
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