Introducing Statistical Prior Knowledge to Face Image Restoration

The statistical prior knowledge for the shape and texture of a face is formulated as a constraint energy term‚which is incorporated into the regularized framework for image restoration.An iterative algorithm is given to provide a numerical solution.Besides‚an edge active measure （EAM）is defined to describe the blurring nature of an image‚which is evaluated at each step of the iteration process to determine the weight of statistical prior constraint.The unfavorable ringing effects are avoided due to the incorporated statistical prior and guidance of the evaluated EAMs.Subjective and objective comparisons of restoration results verified the effectiveness of proposed approach for image preservation and noise suppression.