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.
CITATION STYLE
Yasuda, M., Watanabe, J., Kataoka, S., & Tanaka, K. (2018). Linear-time algorithm in Bayesian image denoising based on gaussian markov random field. IEICE Transactions on Information and Systems, E101D(6), 1629–1639. https://doi.org/10.1587/transinf.2017EDP7346
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