From global to local Bayesian parameter estimation in image restoration using variational distribution approximations

Rafael Molina*, Miguel Vega, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In this paper we present a new Bayesian methodology for the restoration of blurred and noisy images. Bayesian methods rely on image priors that encapsulate prior image knowledge and avoid the ill-posedness of the image restoration problems. Some of these priors depend on global variance parameters, unable to account for local characteristics. Here we first use variational methods to approximate probability posterior distributions for the global model to later use those distributions to define local and more realistic image models which lead to better restored images as it is shown in the experimental section.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Image Processing, ICIP 2007 Proceedings
DOIs
StatePublished - Dec 1 2006
Event14th IEEE International Conference on Image Processing, ICIP 2007 - San Antonio, TX, United States
Duration: Sep 16 2007Sep 19 2007

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume1
ISSN (Print)1522-4880

Other

Other14th IEEE International Conference on Image Processing, ICIP 2007
CountryUnited States
CitySan Antonio, TX
Period9/16/079/19/07

Keywords

  • Bayesian models
  • Image restoration
  • Parameter estimation
  • Regularization
  • Variational methods

ASJC Scopus subject areas

  • Engineering(all)

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    Molina, R., Vega, M., & Katsaggelos, A. K. (2006). From global to local Bayesian parameter estimation in image restoration using variational distribution approximations. In 2007 IEEE International Conference on Image Processing, ICIP 2007 Proceedings [4378906] (Proceedings - International Conference on Image Processing, ICIP; Vol. 1). https://doi.org/10.1109/ICIP.2007.4378906