Share Email Print
cover

Proceedings Paper

EM algorithm-based hyperparameters estimator for Bayesian image denoising using BKF prior
Author(s): Larbi Boubchir; Bruno Durning; Eric Petit
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

This paper is devoted to a novel hyperparameters estimator for bayesian denoising of images using the Bessel K Forms prior which we recently developed. More precisely, this approach is based on the EM algorithm. The simulation results show that this estimator offers good performances and is slightly better compared to the cumulant-based estimator suggested in. A comparative study is carried to show the effectiveness of our bayesian denoiser based on EM algorithm compared to other denoisers developed in both classical and bayesian contexts. Our study has been effected on natural and medical images for gaussian and poisson noise removal.

Paper Details

Date Published: 3 February 2011
PDF: 10 pages
Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 78700W (3 February 2011); doi: 10.1117/12.872233
Show Author Affiliations
Larbi Boubchir, Lab. Images, Signaux et Systèmes Intelligents, Univ. Paris Est Créteil (France)
Bruno Durning, Lab. Images, Signaux et Systèmes Intelligents, Univ. Paris Est Créteil (France)
Eric Petit, Lab. Images, Signaux et Systèmes Intelligents, Univ. Paris Est Créteil (France)


Published in SPIE Proceedings Vol. 7870:
Image Processing: Algorithms and Systems IX
Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

© SPIE. Terms of Use
Back to Top