Iterative image restoration with ringing suppression using the method of POCS

Develops an iterative, space-variant, adaptive restoration algorithm incorporating both regularization and ringing suppression constraints. The algorithm is formulated using the method of projections onto convex sets (POCS). In the proposed method, regularized restoration is implemented by projecting at each iteration onto the extended Wiener solution set. Projection onto this set forces the solution to be equal to the Wiener solution at a set of frequencies over which the magnitude of the degradation transfer function is above a predetermined threshold. Ringing suppression is achieved by adaptively bounding the regional image variance in an attempt to reduce the energy of the ringing artifacts. Three corresponding convex constraint sets are defined to impose tight, moderate, and loose bounds on image variances over the uniform, texture and edge regions, respectively