Some results on the denoising problem in the elliptically distributed context

Abstract : The purpose of this paper is to revisit the denoising problem of a multivariate elliptically symmetric random vector corrupted by a multivariate elliptically symmetric noise. The investigation begins with a review of multivariate elliptically distributed random vectors and of their basic but important properties. A focus is made on the Gaussian scale mixtures, a subclass of the elliptical distributions. In the second part, the denoising problem is revisited in this elliptical context following two classical directions: the minimum mean square error and the maximum a posteriori estimation approaches. Although subject to some restrictions, this investigation extends the two recent studies by Alecu et al. and Selesnick. The practical use of the proposed estimators and some possible special behaviors are then discussed through various illustrative examples.
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Article dans une revue
IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2010, 58 (1), pp.134-150. <10.1109/TSP.2009.2030840>
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Contributeur : Steeve Zozor <>
Soumis le : mercredi 20 janvier 2010 - 14:52:36
Dernière modification le : jeudi 9 février 2017 - 15:53:43

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Steeve Zozor, Christophe Vignat. Some results on the denoising problem in the elliptically distributed context. IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2010, 58 (1), pp.134-150. <10.1109/TSP.2009.2030840>. <hal-00448934>

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