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Proceedings Paper

Nonlinear shrinkage estimation with complex Daubechies wavelets
Author(s): Jean-Marc Lina; Brenda MacGibbon
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Paper Abstract

One of the main advantages of the discrete wavelet representation is the near-optimal estimation of signals corrupted with noise. After the seminal work of De Vore and Lucier (1992) and Donoho and Johnstone (1995), new techniques for choosing appropriate threshold and/or shrinkage functions have recently been explored by Bayesian and likelihood methods. This work is motivated by a Bayesian approach and is based on the complex representation of signals by the Symmetric Daubechies Wavelets. Applications for two dimensional signals are discussed.

Paper Details

Date Published: 30 October 1997
PDF: 13 pages
Proc. SPIE 3169, Wavelet Applications in Signal and Image Processing V, (30 October 1997); doi: 10.1117/12.279680
Show Author Affiliations
Jean-Marc Lina, Univ. de Montreal and Atlantic Nuclear Services Ltd. (Canada)
Brenda MacGibbon, Univ. du Quebec a Montreal and Ecole des Hautes Etudes Commerciales (Canada)


Published in SPIE Proceedings Vol. 3169:
Wavelet Applications in Signal and Image Processing V
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

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