Abstract
Recent advances in measurement techniques allow us to obtain a large quantity of imaging data in various natural science fields. These data can be analyzed by Markov random field (MRF) models which have made progress in information science. We can estimate hyperparameters in our MRF model, which is a probabilistic one, by the framework of Bayesian inference. When our MRF model is applied to diffusion systems which often appear in the natural sciences, a hyperparameter is an important parameter which corresponds to the diffusion coefficient. Thus, in this study, we calculate not only a point estimate but also a distribution estimate of hyperparameters to evaluate estimation reliability.
