Image and signal restoration using pairwise Markov trees

Author

Monfrini, E. ; Lecomte, J. ; Desbouvries, F. ; Pieczynski, W.

Author_Institution

Univ. Claude Bernard, Villeurbanne, France

fYear

2003

fDate

28 Sept.-1 Oct. 2003

Firstpage

174

Lastpage

177

Abstract

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.

Keywords

Gaussian processes; Kalman filters; hidden Markov models; image restoration; image segmentation; statistics; trees (mathematics); Kalman filter; image restoration; image segmentation; linear Gaussian model; pairwise Markov trees; signal restoration; statistical restoration; Hidden Markov models; Image processing; Image restoration; Image segmentation; Sections; Signal processing; Signal restoration; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2003 IEEE Workshop on

Print_ISBN

0-7803-7997-7

Type

conf

DOI

10.1109/SSP.2003.1289372

Filename

1289372

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2852899