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- W2108608669 abstract "Prior techniques in digital image restoration have assumed linear relations between the original blurred image intensity, the silver density recorded on film, and the film-grain noise. In this paper a model is used which explicitly includes nonlinear relations between intensity and film density, by use of the D-log E curve. Using Gaussian models for the image and noise statistics, a maximum a posteriori (Bayes) estimate of the restored image is derived. The MAP estimate is nonlinear, and computer implementation of the estimator equations is achieved by a fast algorithm based on direct maximization of the posterior density function. An example of the restoration method implemented on a digital image is shown." @default.
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- W2108608669 date "1977-03-01" @default.
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- W2108608669 title "Bayesian Methods in Nonlinear Digital Image Restoration" @default.
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- W2108608669 doi "https://doi.org/10.1109/tc.1977.1674810" @default.
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