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• W2149479098 abstract "The authors discuss the use of iterative restoration algorithms for the removal of linear blurs from photographic images that may also be assumed to be degraded by pointwise nonlinearities such as film saturation and additive noise. Iterative algorithms allow for the incorporation of various types of prior knowledge about the class of feasible solutions, can be used to remove nonstationary blurs, and are fairly robust with respect to errors in the approximation of the blurring operator. Special attention is given to the problem of convergence of the algorithms, and classical solutions such as inverse filters, Wiener filters, and constrained least-squares filters are shown to be limiting solutions of variations of the iterations. Regularization is introduced as a means for preventing the excessive noise magnification that is typically associated with ill-conditioned inverse problems such as the deblurring problem, and it is shown that noise effects can be minimized by terminating the algorithms after a finite number of iterations. The role and choice of constraints on the class of feasible solutions are also discussed." @default.
• W2149479098 created "2016-06-24" @default.
• W2149479098 creator A5030656291 @default.
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• W2149479098 date "1990-05-01" @default.
• W2149479098 modified "2023-10-16" @default.
• W2149479098 title "Iterative methods for image deblurring" @default.
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• W2149479098 doi "https://doi.org/10.1109/5.53403" @default.
• W2149479098 hasPublicationYear "1990" @default.
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