Estimation in signal-dependent film-grain noise

Abstract

Optimal estimators are derived for a signal-dependent film-grain noise model, and the effect of signal-dependence on the estimators's structures is investigated. Due to the mathematical complexity of these optimal estimators, various suboptimal estimators are proposed. Computer simulations are then presented which compare the optimal and suboptimal estimators with regard to mean square estimation error, sensitivity to signal-dependence, and robustness with respect to the a priori signal probability density function.