Paper Info
Title
Em Algorithm-Based Hyperparameters Estimator For Bayesian Image Denoising Using Bkf Prior
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.(1, 2) 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.(1, 2) 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.
Year
DOI
Venue
2011
10.1117/12.872233
IMAGE PROCESSING: ALGORITHMS AND SYSTEMS IX
Keywords
Field
DocType
Bayesian denoising, Wavelet transform, Bessel K Form, Hyperparameter estimation, EM Algorithm, Gaussian noise, Poisson noise
Noise reduction,Pattern recognition,Hyperparameter,Expectation–maximization algorithm,Gaussian,Artificial intelligence,Gaussian noise,Bayesian probability,Physics,Estimator,Wavelet transform
Conference
Volume
ISSN
Citations 
7870
0277-786X
3
PageRank 
References 
Authors
0.41
0
3
Name
Order
Citations
PageRank
Larbi Boubchir120619.99
bruno durning240.79
Eric Petit35812.73