Abstract

Film-grain noise describes the intrinsic noise produced by a photographic emulsion during the process of image recording and reproduction. In this paper we consider the restoration of images degraded by film-grain noise. First a detailed model for the over-all photographic imaging system is presented. The model includes linear blurring effects and the signal-dependent effect of film-grain noise. The accuracy of this model is tested by simulating images according to it and comparing the results to images of similar targets that were actually recorded on film. The restoration of images degraded by film-grain noise is then considered in the context of estimation theory. A discrete Wiener filer is developed which explicitly allows for the signal dependence of the noise. The filter adaptively alters its characteristics based on the nonstationary first order statistics of an image and is shown to have advantages over the conventional Wiener filter. Experimental results for modeling and the adaptive estimation filter are presented.

© 1978 Optical Society of America

Detection of low-contrast images in film-grain noise

F. Naderi and A. A. Sawchuk
Appl. Opt. 17(18) 2883-2891 (1978)

Restoration of noisy blurred images by a smoothing spline filter

M. J. Peyrovian and A. A. Sawchuk
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Noise updating repeated Wiener filter and other adaptive noise smoothing filters using local image statistics

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Estimation in signal-dependent film-grain noise

Gary K. Froehlich, John F. Walkup, and Thomas F. Krile
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Comparison of image restoration methods

T. M. Cannon, H. J. Trussell, and B. R. Hunt
Appl. Opt. 17(21) 3384-3390 (1978)