Image and signal restoration using pairwise Markov trees

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

doi:10.1109/SSP.2003.1289372

Image and signal restoration using pairwise Markov trees

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003
Publisher	IEEE Computer Society
Pages	174-177
Number of pages	4
ISBN (Electronic)	0780379977
DOIs	https://doi.org/10.1109/SSP.2003.1289372
Publication status	Published - 1 Jan 2003
Event	IEEE Workshop on Statistical Signal Processing, SSP 2003 - St. Louis, United States Duration: 28 Sept 2003 → 1 Oct 2003

Publication series

Name	IEEE Workshop on Statistical Signal Processing Proceedings
Volume	2003-January

Conference

Conference	IEEE Workshop on Statistical Signal Processing, SSP 2003
Country/Territory	United States
City	St. Louis
Period	28/09/03 → 1/10/03

Keywords

Hidden Markov models
Image processing
Image restoration
Image segmentation
Sections
Signal processing
Signal restoration
Stochastic processes

Access to Document

10.1109/SSP.2003.1289372

Cite this

Monfrini, E., Lecomte, J., Desbouvries, F., & Pieczynski, W. (2003). Image and signal restoration using pairwise Markov trees. In Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003 (pp. 174-177). Article 1289372 (IEEE Workshop on Statistical Signal Processing Proceedings; Vol. 2003-January). IEEE Computer Society. https://doi.org/10.1109/SSP.2003.1289372

@inproceedings{8aca9614d0ba4cb29ddcbb7188b7d605,

title = "Image and signal restoration using pairwise Markov trees",

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 = "Hidden Markov models, Image processing, Image restoration, Image segmentation, Sections, Signal processing, Signal restoration, Stochastic processes",

author = "E. Monfrini and J. Lecomte and F. Desbouvries and W. Pieczynski",

note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; IEEE Workshop on Statistical Signal Processing, SSP 2003 ; Conference date: 28-09-2003 Through 01-10-2003",

year = "2003",

month = jan,

day = "1",

doi = "10.1109/SSP.2003.1289372",

language = "English",

series = "IEEE Workshop on Statistical Signal Processing Proceedings",

publisher = "IEEE Computer Society",

pages = "174--177",

booktitle = "Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003",

}

Monfrini, E, Lecomte, J, Desbouvries, F & Pieczynski, W 2003, Image and signal restoration using pairwise Markov trees. in Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003., 1289372, IEEE Workshop on Statistical Signal Processing Proceedings, vol. 2003-January, IEEE Computer Society, pp. 174-177, IEEE Workshop on Statistical Signal Processing, SSP 2003, St. Louis, United States, 28/09/03. https://doi.org/10.1109/SSP.2003.1289372

Image and signal restoration using pairwise Markov trees. / Monfrini, E.; Lecomte, J.; Desbouvries, F. et al.
Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003. IEEE Computer Society, 2003. p. 174-177 1289372 (IEEE Workshop on Statistical Signal Processing Proceedings; Vol. 2003-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Image and signal restoration using pairwise Markov trees

AU - Monfrini, E.

AU - Lecomte, J.

AU - Desbouvries, F.

AU - Pieczynski, W.

PY - 2003/1/1

Y1 - 2003/1/1

N2 - 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.

AB - 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.

KW - Hidden Markov models

KW - Image processing

KW - Image restoration

KW - Image segmentation

KW - Sections

KW - Signal processing

KW - Signal restoration

KW - Stochastic processes

U2 - 10.1109/SSP.2003.1289372

DO - 10.1109/SSP.2003.1289372

M3 - Conference contribution

AN - SCOPUS:84947565260

T3 - IEEE Workshop on Statistical Signal Processing Proceedings

SP - 174

EP - 177

BT - Proceedings of the 2003 IEEE Workshop on Statistical Signal Processing, SSP 2003

PB - IEEE Computer Society

T2 - IEEE Workshop on Statistical Signal Processing, SSP 2003

Y2 - 28 September 2003 through 1 October 2003

ER -

Image and signal restoration using pairwise Markov trees

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Cite this