Non-Linear Shrinkage Estimation with Complex Daubechies Wavelets (1997)
| Venue: | PROCEEDINGS OF SPIE, WAVELET APPLICATIONS IN SIGNAL AND IMAGE PROCESSING V |
| Citations: | 6 - 0 self |
BibTeX
@INPROCEEDINGS{Lina97non-linearshrinkage,
author = {J.-M. Lina and B. MacGibbon},
title = {Non-Linear Shrinkage Estimation with Complex Daubechies Wavelets},
booktitle = {PROCEEDINGS OF SPIE, WAVELET APPLICATIONS IN SIGNAL AND IMAGE PROCESSING V},
year = {1997},
pages = {67--79},
publisher = {}
}
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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.
