Nonlinear Wavelet Shrinkage with Bayes Rules and Bayes Factors

Advisor(s)
Editor(s)
Associated Organization(s)
Organizational Unit
Wallace H. Coulter Department of Biomedical Engineering
The joint Georgia Tech and Emory department was established in 1997
Organizational Unit
Series
Supplementary to:
Abstract
Wavelet shrinkage, the method proposed by the seminal work of Donoho and Johnstone is a disarmingly simple and efficient way of denoising data. Shrinking wavelet coefficients was proposed from several optimality criteria. In this article a wavelet shrinkage by coherent Bayesian inference in the wavelet domain is proposed. The methods are tested on standard Donoho-Johnstone test functions.
Sponsor
Date
1998-03
Extent
Resource Type
Text
Resource Subtype
Article
Post-print
Rights Statement
Rights URI