In practice, we meet numerous image restoration problems, particularly those on face images. An approach to image restoration based on statistical prior of faces and image blur measure is presented in this paper. The novelty of the approach is twofold: 1) the prior on the shape and appearance of a face represented as statistical models is incorporated into the regularized image restoration formulation. Moreover, an iterative algorithm is given to provide a numerical solution. 2) an image blur measure is defined to describe the blur nature of an image. The measure is evaluated at each step of the iteration process to determine the weight of the constraint introduced by the statistical prior. Both subjective and objective comparisons of the restoration results indicate great improvements on image preservation and noise suppression.
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