Maximum a posteriori video super-resolution with a new multichannel image prior

Super-resolution (SR) is the term used to define the process of estimating a high resolution (HR) image or a set of HR images from a set of low resolution (LR) observations. In this paper we propose a class of SR algorithms based on the maximum a posteriori (MAP) framework. These algorithms utilize a new multichannel image prior model, along with the state-of-the art image prior and observation models. Numerical experiments comparing the proposed algorithms, demonstrate the advantages of the adopted multichannel approach.