Bayesian TV denoising of SAR images

Miguel Vega; Javier Mateos; Rafael Molina; Aggelos K. Katsaggelos

doi:10.1109/ICIP.2011.6115772

Bayesian TV denoising of SAR images

Miguel Vega^*, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.

Original language	English (US)
Title of host publication	ICIP 2011
Subtitle of host publication	2011 18th IEEE International Conference on Image Processing
Pages	165-168
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2011.6115772
State	Published - 2011
Event	2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium Duration: Sep 11 2011 → Sep 14 2011

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
ISSN (Print)	1522-4880

Other

Other	2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/Territory	Belgium
City	Brussels
Period	9/11/11 → 9/14/11

Keywords

Bayesian methods
SAR images denoising
despeckling
image restoration
parameter estimation

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/ICIP.2011.6115772

Cite this

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title = "Bayesian TV denoising of SAR images",

abstract = "Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.",

keywords = "Bayesian methods, SAR images denoising, despeckling, image restoration, parameter estimation",

author = "Miguel Vega and Javier Mateos and Rafael Molina and Katsaggelos, {Aggelos K.}",

year = "2011",

doi = "10.1109/ICIP.2011.6115772",

language = "English (US)",

isbn = "9781457713033",

series = "Proceedings - International Conference on Image Processing, ICIP",

pages = "165--168",

booktitle = "ICIP 2011",

note = "2011 18th IEEE International Conference on Image Processing, ICIP 2011 ; Conference date: 11-09-2011 Through 14-09-2011",

}

Vega, M, Mateos, J, Molina, R & Katsaggelos, AK 2011, Bayesian TV denoising of SAR images. in ICIP 2011: 2011 18th IEEE International Conference on Image Processing., 6115772, Proceedings - International Conference on Image Processing, ICIP, pp. 165-168, 2011 18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, 9/11/11. https://doi.org/10.1109/ICIP.2011.6115772

TY - GEN

T1 - Bayesian TV denoising of SAR images

AU - Vega, Miguel

AU - Mateos, Javier

AU - Molina, Rafael

AU - Katsaggelos, Aggelos K.

PY - 2011

Y1 - 2011

N2 - Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.

AB - Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.

KW - Bayesian methods

KW - SAR images denoising

KW - despeckling

KW - image restoration

KW - parameter estimation

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U2 - 10.1109/ICIP.2011.6115772

DO - 10.1109/ICIP.2011.6115772

M3 - Conference contribution

AN - SCOPUS:84856291575

SN - 9781457713033

T3 - Proceedings - International Conference on Image Processing, ICIP

SP - 165

EP - 168

BT - ICIP 2011

T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011

Y2 - 11 September 2011 through 14 September 2011

ER -

Bayesian TV denoising of SAR images

Abstract

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Keywords

ASJC Scopus subject areas

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