Fast algorithm based on triplet Markov fields for unsupervised multi-class segmentation of SAR images

DOI10.1007/s11432-011-4215-xzbMath1267.94010OpenAlexW2062999411MaRDI QIDQ350910

Ping Xiao, Xin Wang, Yan Wu, Lu Gan, Chun Yan Liu, Ming Li

Publication date: 3 July 2013

Published in: Science China. Information Sciences (Search for Journal in Brave)

Full work available at URL: http://engine.scichina.com/doi/10.1007/s11432-011-4215-x

zbMATH Keywords

triplet Markov fieldsmulti-class segmentationnew potential energy functionpixon-representation of SAR imageQuadTree decomposition

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (1)

Improved FOCUSS method for reconstruction of cluster structured sparse signals in radar imaging

Cites Work

• Unsupervised segmentation of triplet Markov chains hidden with long-memory noise
• Multisensor triplet Markov chains and theory of evidence
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Parameter estimation in Markov random field image modeling with imperfect observations. A comparative study

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