Artifact reduction for POCS-based super resolution with edge adaptive regularization and higher-order interpolants

In this paper we propose to improve the POCS- (projections onto convex sets) based super-resolution methods (SRR) in two ways. First, the discretization of the continuous image formation model is improved to explicitly allow for higher order interpolation methods to be used. Second, the constraint sets are modified to reduce the amount of edge ringing present in the high resolution image estimate. This effectively regularizes the inversion process. Furthermore, additional constraint sets are defined to reduce aliasing that would especially be present in underdetermined problems