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Bayesian Restoration of Audio Signals Degraded by Impulsive Noise Modeled as Individual Pulses

Impulsive noise, also known as clicks, is a very common type of distortion in old gramophone recordings. Existing methods (both heuristic and statistical) for removal of this type of defect usually do not exploit its underlying physical generation. This work proposes a model in which each click is individually modeled, which is more physically meaningful. A Bayesian method based on the reversible-jump Metropolis-Hastings algorithm for joint detection and removal of impulsive noise in audio signals is devised. Simulations with artificial and real audio signals as well as comparisons with competing approaches are presented to illustrate and validate the proposed method.