Hidden Markov random field models for TCA image analysis

DOI10.1016/j.csda.2007.06.022zbMath1452.62709OpenAlexW2151726252WikidataQ58205276 ScholiaQ58205276MaRDI QIDQ1020889

Katy Klauenberg, Francesco Lagona

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.06.022

zbMATH Keywords

TCAEM algorithmmean field approximationhidden Markov random fieldcoupled Markov chainGabor filter

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Random fields; image analysis (62M40) Markov processes: estimation; hidden Markov models (62M05)

Related Items (3)

Mixed Hidden Markov Models for Longitudinal Data: An Overview ⋮ Model-based segmentation of spatial cylindrical data ⋮ Editorial: 2nd special issue on statistical signal extraction and filtering

Cites Work

• On the convergence properties of the EM algorithm
• EM procedures using mean field-like approximations for Markov model-based image segmentation
• On the relationship of the Markov mesh to the NSHP Markov chain
• On the estimation and testing of spatial interaction in Gaussian lattice processes
• Markov Random Fields with Higher-order Interactions
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