Maximum Likelihood for Bayesian Estimator Based on alpha-Stable For Image

Xu Huang; Allan Madoc

doi:10.1109/ICME.2002.1035880

Maximum Likelihood for Bayesian Estimator Based on alpha-Stable For Image

Xu Huang, Allan Madoc

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

66 Citations (Scopus)

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Abstract

A maximum likelihood for Bayesian estimator based on /spl alpha/-stable is discussed. Closer to a realistic situation, and unlike previous methods used for the Bayesian estimator, for the case discussed here it is not necessary to know the variance of the noise. The parameters relative to Bayesian estimators of the model built up are carefully investigated after a discussion of /spl alpha/-stable 3D simulations for a maximum likelihood. The Bayesian estimator then is established. As an example, an improved Bayesian estimator that is a natural extension of the Wiener solution and other wavelet denoising (soft and hard threshold methods), is presented to illustrate our discussion.

Original language	English
Title of host publication	2002 IEEE Internatioanl Conference on Multimedia and Expo
Place of Publication	Switzerland
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	709-712
Number of pages	4
ISBN (Print)	0-7803-7305-7
DOIs	https://doi.org/10.1109/ICME.2002.1035880
Publication status	Published - 2002
Event	2002 IEEE International Conference on Multimedia and Expo - Duration: 26 Aug 2002 → 29 Aug 2002

Conference

Conference	2002 IEEE International Conference on Multimedia and Expo
Period	26/08/02 → 29/08/02

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10.1109/ICME.2002.1035880

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title = "Maximum Likelihood for Bayesian Estimator Based on alpha-Stable For Image",

abstract = "A maximum likelihood for Bayesian estimator based on /spl alpha/-stable is discussed. Closer to a realistic situation, and unlike previous methods used for the Bayesian estimator, for the case discussed here it is not necessary to know the variance of the noise. The parameters relative to Bayesian estimators of the model built up are carefully investigated after a discussion of /spl alpha/-stable 3D simulations for a maximum likelihood. The Bayesian estimator then is established. As an example, an improved Bayesian estimator that is a natural extension of the Wiener solution and other wavelet denoising (soft and hard threshold methods), is presented to illustrate our discussion.",

author = "Xu Huang and Allan Madoc",

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note = "2002 IEEE International Conference on Multimedia and Expo ; Conference date: 26-08-2002 Through 29-08-2002",

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AU - Huang, Xu

AU - Madoc, Allan

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AB - A maximum likelihood for Bayesian estimator based on /spl alpha/-stable is discussed. Closer to a realistic situation, and unlike previous methods used for the Bayesian estimator, for the case discussed here it is not necessary to know the variance of the noise. The parameters relative to Bayesian estimators of the model built up are carefully investigated after a discussion of /spl alpha/-stable 3D simulations for a maximum likelihood. The Bayesian estimator then is established. As an example, an improved Bayesian estimator that is a natural extension of the Wiener solution and other wavelet denoising (soft and hard threshold methods), is presented to illustrate our discussion.

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DO - 10.1109/ICME.2002.1035880

M3 - Conference contribution

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BT - 2002 IEEE Internatioanl Conference on Multimedia and Expo

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Switzerland

T2 - 2002 IEEE International Conference on Multimedia and Expo

Y2 - 26 August 2002 through 29 August 2002

ER -

Maximum Likelihood for Bayesian Estimator Based on alpha-Stable For Image

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