A Bayesian transformation model for wavelet shrinkage

Wavelet shrinkage estimators, in general, make the additive normal noise assumption and disregard the nonlinear nature of contamination. We develop Bayesian wavelet shrinkage estimators (based on the power transformations in the linear model) to accommodate a broad class of noise models in image pro...

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Veröffentlicht in:	IEEE transactions on image processing 2003-12, Vol.12 (12), p.1512-1521
Hauptverfasser:	Ray, S., Mallick, B.K.
Format:	Artikel
Sprache:	eng
Schlagworte:	Additive noise Applied sciences Bayesian analysis Bayesian methods Computational modeling Computer simulation Contamination Estimators Exact sciences and technology Image processing Information, signal and communications theory Markov random fields Monte Carlo methods Noise Probability distribution Shrinkage Signal processing Studies Synthetic aperture radar Telecommunications and information theory Transformations Wavelet Wavelet coefficients
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