Image and signal restoration using pairwise Markov trees

This work deals with the statistical restoration of a hidden signal using pairwise Markov trees (PMT). PMT have been introduced recently in the case of a discrete hidden signal. We first show that PMT can perform better than the classical hidden Markov trees (HMT) when applied to unsupervised image...

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Bibliographic Details
Published inIEEE Workshop on Statistical Signal Processing, 2003 pp. 174 - 177
Main Authors Monfrini, E., Lecomte, J., Desbouvries, F., Pieczynski, W.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Hidden Markov models
Image processing
Image restoration
Image segmentation
Sections
Signal processing
Signal restoration
Stochastic processes
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Summary:This work deals with the statistical restoration of a hidden signal using pairwise Markov trees (PMT). PMT have been introduced recently in the case of a discrete hidden signal. We first show that PMT can perform better than the classical hidden Markov trees (HMT) when applied to unsupervised image segmentation. We next consider a PMT in a linear Gaussian model with continuous hidden data, and we give formulas of an original extension of the classical Kalman filter.
ISBN:0780379977
9780780379978
DOI:10.1109/SSP.2003.1289372