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

2017-10-20Code Available0· sign in to hype

Muneki Yasuda, Junpei Watanabe, Shun Kataoka, Kazuyuki Tanaka

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Abstract

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.

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