Ofer Hadar

In this paper, we present a super-resolution (SR) method based on iterative backprojections. Motion information is used for the synthesis of the restoration filter in the SR method. Both, the blur estimation and the choice of the degradation model, are based on estimated global motion. The method is applied to highly under-sampled images such as DC images ofMPEG compressed video and medical magnetic resonance (MR) images. Results of the comparison of our blur model with some common blur models are encouraging.