Bayesian image restoration using a wavelet-based subband decomposition

Rafael Molina; Aggelos K. Katsaggelos; Javier Abad

Bayesian image restoration using a wavelet-based subband decomposition

Rafael Molina^*, Aggelos K. Katsaggelos, Javier Abad

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

In this paper the subband decomposition of a single channel image restoration problem is examined. The decomposition is carried out in the image model (prior model) in order to take into account the frequency activity of each band of the original image. The hyperparameters associated with each band together with the original image are rigorously estimated within the Bayesian framework. Finally, the proposed method is tested and compared with other methods on real images.

Original language	English (US)
Pages (from-to)	3257-3260
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	6
State	Published - Jan 1 1999

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering
Acoustics and Ultrasonics

Cite this

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title = "Bayesian image restoration using a wavelet-based subband decomposition",

abstract = "In this paper the subband decomposition of a single channel image restoration problem is examined. The decomposition is carried out in the image model (prior model) in order to take into account the frequency activity of each band of the original image. The hyperparameters associated with each band together with the original image are rigorously estimated within the Bayesian framework. Finally, the proposed method is tested and compared with other methods on real images.",

author = "Rafael Molina and Katsaggelos, {Aggelos K.} and Javier Abad",

year = "1999",

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language = "English (US)",

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T1 - Bayesian image restoration using a wavelet-based subband decomposition

AU - Molina, Rafael

AU - Katsaggelos, Aggelos K.

AU - Abad, Javier

PY - 1999/1/1

Y1 - 1999/1/1

N2 - In this paper the subband decomposition of a single channel image restoration problem is examined. The decomposition is carried out in the image model (prior model) in order to take into account the frequency activity of each band of the original image. The hyperparameters associated with each band together with the original image are rigorously estimated within the Bayesian framework. Finally, the proposed method is tested and compared with other methods on real images.

AB - In this paper the subband decomposition of a single channel image restoration problem is examined. The decomposition is carried out in the image model (prior model) in order to take into account the frequency activity of each band of the original image. The hyperparameters associated with each band together with the original image are rigorously estimated within the Bayesian framework. Finally, the proposed method is tested and compared with other methods on real images.

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M3 - Article

AN - SCOPUS:0032681806

SN - 0736-7791

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JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

ER -

Bayesian image restoration using a wavelet-based subband decomposition

Abstract

ASJC Scopus subject areas

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