Abstract
An inference technique in which a posterior probability calculated by the Bayesian theorem is used is called Bayesian inference. We introduce an image super-resolution technique based on Bayesian inference. The compound Bayesian super-resolution proposed by Kanemura et al. is explained in particular. In Bayesian super-resolution, subpixel details can be reproduced because shifts and rotations of observed images are utilized positively. Furthermore, edge reproduction is realized by the line process in compound Bayesian super-resolution. In this paper, we describe the outline of compound Bayesian super-resolution and show experimental results.
