Inverse Renormalization Group Transformation in Bayesian Image Segmentations
Kazuyuki Tanaka, Shun Kataoka, Muneki Yasuda, Masayuki Ohzeki · Journal of the Physical Society of Japan · 2015
A new Bayesian image segmentation algorithm is proposed by combining a loopy belief propagation with an inverse real space renormalization group transformation to reduce the computational time. In results of our experiment, we observe that the proposed method can reduce the computational time to less than one-tenth of that taken by conventional Bayesian approaches.