Using logarithmic opinion pooling techniques in Bayesian blind multi-channel restoration

Bruno Amizic*, Aggelos K Katsaggelos, Rafael Molina

*Corresponding author for this work

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

2 Scopus citations

Abstract

In this paper we examine the use of logarithmic opinion pooling techniques to combine two observations models that are normally used in multi-channel image restoration techniques. The combined observation model is used together with simultaneous autoregression prior models for the image and blurs to define the joint distribution of image, blurs and observations. Assuming that all the unknown parameters are previously estimated we use variational techniques to approximate the posterior distribution of the real underlying image and the unknown blurs. We will examine the use of two approximations of the posterior distribution. Experimental results are used to validate the proposed approach.

Original languageEnglish (US)
Title of host publicationVISAPP 2008 - 3rd International Conference on Computer Vision Theory and Applications, Proceedings
Pages565-570
Number of pages6
Volume1
StatePublished - Dec 15 2008
Event3rd International Conference on Computer Vision Theory and Applications, VISAPP 2008 - Funchal, Madeira, Portugal
Duration: Jan 22 2008Jan 25 2008

Other

Other3rd International Conference on Computer Vision Theory and Applications, VISAPP 2008
CountryPortugal
CityFunchal, Madeira
Period1/22/081/25/08

Keywords

  • Bayesian framework
  • Blind multi-channel restoration
  • Logarithmic opinion pooling
  • Variational methods

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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