Abstract
A number of adaptive estimators to restore images degraded by signal-dependent film grain noise have been derived. These estimators are characterized by their ability to adapt to the nonstationary properties of the image signal distribution. This adaptability results in restored images with better contrast and noise suppression properties when compared with nonadaptive estimators. Lookup tables were extensively used in order to reduce the computation time. In addition to the optimal Bayesian estimators, two suboptimal estimators were presented. Results of computer simulations conducted to evaluate the performances of the estimators using various image quality measures were also presented.
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