Image enhancement using hierarchical Bayesian image expansion super resolution

Multiframe super-resolution uses the information from a set of low resolution images to produce a high resolution output image. This process can prospectively be run several times with interim sets of enhanced images that can be further enhanced. This paper presents and discusses the results of this hierarchical technique on a sreated set of images and the results produced. When successful, this approach is able to produce a better quality image than the traditional single run super resolution approach. This provides a method for existing super resolution algorithms to further enhance image quality without modifying the underlying algorithm.