Linear-Time Algorithm in Bayesian Image Denoising based on Gaussian Markov Random Field

Muneki YASUDA  Junpei WATANABE  Shun KATAOKA  Kazuyuki TANAKA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.6   pp.1629-1639
Publication Date: 2018/06/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDP7346
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
Keyword: 
Bayesian image denoising,  Gaussian Markov random field,  EM algorithm,  mean-field method,  linear-time algorithm,  

Full Text: PDF(1.3MB)
>>Buy this Article


Summary: 
In this paper, we consider Bayesian image denoising based on a Gaussian Markov random field (GMRF) model, for which we propose an new algorithm. Our method can solve Bayesian image denoising problems, including hyperparameter estimation, in O(n)-time, where n is the number of pixels in a given image. From the perspective of the order of the computational time, this is a state-of-the-art algorithm for the present problem setting. Moreover, the results of our numerical experiments we show our method is in fact effective in practice.