A new algorithm for iterative image restoration based on the least-squares criterion, which can provide a restored image with a good appearance for a human observer, is proposed. The introduction of a nonlinear constraint matrix, which is determined by taking account of features of an input image or an intermediate processing result, solves the problem in image restoration of obtaining a result without serious deterioration of local space details and discernible noise for human eyes. It is also evident in the course of derivation of the algorithm that the procedure defined as reblur serves to suppress noise amplification in the sense of the least-squares criterion as well as to ensure convergence of the solution. Suitability of the proposed algorithm is confirmed through experiments of iterative restoration for an image degraded with a Gaussian point-spread function with noise.
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