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Proceedings Paper

Bayesian iterative method for blind deconvolution
Author(s): Alessandro Neri; Gaetano Scarano; Giovanni Jacovitti
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Paper Abstract

Blind deconvolution is a typical solution to unknown LSI system inversion problems. When only the output is available, second order statistics are not sufficient to retrieve the phase of the LSI system, so that some form of higher-order analysis has to be employed. In this work, a general iterative solution based on a Bayesian approach is illustrated, and some cases both for mono and bidimensional applications are discussed. The method implies the use of non second-order statistics (rather than higher-order statistics), tuned to specific a priori statistical models. The Bayesian approach yields specific solutions corresponding to known techniques, such as MED deconvolution employed in seismic processing, and more sophisticated procedures for non-independent identically distributed (for instance Markovian) inputs.

Paper Details

Date Published: 1 December 1991
PDF: 13 pages
Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); doi: 10.1117/12.49777
Show Author Affiliations
Alessandro Neri, Univ. of Rome (Italy)
Gaetano Scarano, Istituto di Acustica (Italy)
Giovanni Jacovitti, Univ. of Rome (Italy)

Published in SPIE Proceedings Vol. 1565:
Adaptive Signal Processing
Simon Haykin, Editor(s)

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