Multiresolution image classification by hierarchical modeling with two-dimensional hidden Markov models

DOI10.1109/18.857794zbMath1002.94002OpenAlexW2166866346MaRDI QIDQ2705922

Jia Li, Robert M. Gray, Richard A. Olshen

Publication date: 19 March 2001

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/9d4d7f0c8c08ecde9254fa9d47f49b554b723aaf

zbMATH Keywords

EM algorithmimage segmentationimage classificationmultiresolution hidden Markov model

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (8)

A study of Gaussian mixture models of color and texture features for image classification and segmentation ⋮ On the accuracy of the MAP inference in HMMs ⋮ On approximation of smoothing probabilities for hidden Markov models ⋮ Asymptotic risks of Viterbi segmentation ⋮ SAR image segmentation based on mixture context and wavelet hidden-class-label Markov random field ⋮ Multiscale stochastic modeling for tractable inference and data assimilation ⋮ On adjusted Viterbi training ⋮ The adjusted Viterbi training for hidden Markov models

Uses Software

• AS 144

This page was built for publication: Multiresolution image classification by hierarchical modeling with two-dimensional hidden Markov models