Face Image Super-Resolution Reconstruction Based on Recognition and Projection onto Convex Sets

Face image super-resolution reconstruction (SRR) can be widely used in forensic analysis and video surveillance. With the recognition-based idea, the statistical characteristics of face images are investigated and incorporated into SRR. Based on the set theoretic formulation, a projection onto convex sets (POCS) algorithm is applied to find the solution to face image reconstruction. Compared with the traditional POCS based SRR methods, the proposed approach imposes some extra constraint sets to the solution. The experiment results on frontal face images show that the proposed approach gains a better performance both on noise suppression and reconstruction quality and has the advantage of simplicity in computation.