EM algorithm-based hyperparameters estimator for Bayesian image denoising using BKF prior

Larbi Boubchir; Bruno Durning; Eric Petit

doi:10.1117/12.872233

3 February 2011 EM algorithm-based hyperparameters estimator for bayesian image denoising using BKF prior

Larbi Boubchir, Bruno Durning, Eric Petit

Proceedings Volume 7870, Image Processing: Algorithms and Systems IX; 78700W (2011) https://doi.org/10.1117/12.872233
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

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.

Citation Download Citation

Larbi Boubchir, Bruno Durning, and Eric Petit "EM algorithm-based hyperparameters estimator for bayesian image denoising using BKF prior", Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 78700W (3 February 2011); https://doi.org/10.1117/12.872233

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