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LinearTime 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.E101D
No.6
pp.16291639 Publication Date: 2018/06/01
Online ISSN: 17451361
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, meanfield method, lineartime algorithm,
Full Text: PDF(1.3MB)>>
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 stateoftheart algorithm for the present problem setting. Moreover, the results of our numerical experiments we show our method is in fact effective in practice.

