Wavelets, Gaussian mixtures and Wiener filtering

Authors:
Albert Bijaoui
Affiliations:
Département CERGA URA CNRS 6527, Observatoire de la Côte d'Azur, B.P. 229, F-06304 Nice Cedex 4, France
Venue:
Signal Processing
Year:
2002

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Abstract

In this short communication a non-linear Wiener filtering is obtained from a Bayesian approach of the probability density function modelled as a Gaussian mixture. Its application on the wavelet denoising leads to excellent results.