Bayesian and regularization methods for hyperparameter estimation in image restoration

In this paper, we propose the application of the hierarchical Bayesian paradigm to the image restoration problem. We derive expressions for the iterative evaluation of the two hyperparameters applying the evidence and maximum a posteriori (MAP) analysis within the hierarchical Bayesian paradigm. We...

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Veröffentlicht in:	IEEE transactions on image processing 1999-02, Vol.8 (2), p.231-246
Hauptverfasser:	Molina, R., Katsaggelos, A.K., Mateos, J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Bayesian analysis Bayesian methods Degradation Estimating Exact sciences and technology Image analysis Image processing Image restoration Information, signal and communications theory Iterative algorithms Iterative methods Lead Least squares approximation Mathematical analysis Parameter estimation Regularization Signal processing Telecommunications and information theory Testing
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