Modeling non-Rayleigh speckle distribution in SAR images

Yves Delignon; Wojciech Pieczynski

doi:10.1109/TGRS.2002.800234

Modeling non-Rayleigh speckle distribution in SAR images

Yves Delignon
, Wojciech Pieczynski

Departement Electronique
CNRS SAMOVAR UMR 5157

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

Abstract

In non-Rayleigh distributed radar images, the number of scatterers can be viewed as a Poisson distributed random variable, with the mean itself random. When this mean is Gamma distributed, then the image classically satisfies the K distribution. We add three new possible distributions for this mean: inverse Gamma, Beta of the first kind, and Beta of the second kind. We show that new intensity distributions so obtained can be estimated, with the interest of the extension validated on a real image.

Original language	English
Pages (from-to)	1430-1435
Number of pages	6
Journal	IEEE Transactions on Geoscience and Remote Sensing
Volume	40
Issue number	6
DOIs	https://doi.org/10.1109/TGRS.2002.800234
Publication status	Published - 1 Jun 2002
Externally published	Yes

Keywords

K law
Pearson system
Scatterer
Speckle
Statistical modeling of SAR images

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10.1109/TGRS.2002.800234

Cite this

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title = "Modeling non-Rayleigh speckle distribution in SAR images",

abstract = "In non-Rayleigh distributed radar images, the number of scatterers can be viewed as a Poisson distributed random variable, with the mean itself random. When this mean is Gamma distributed, then the image classically satisfies the K distribution. We add three new possible distributions for this mean: inverse Gamma, Beta of the first kind, and Beta of the second kind. We show that new intensity distributions so obtained can be estimated, with the interest of the extension validated on a real image.",

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AB - In non-Rayleigh distributed radar images, the number of scatterers can be viewed as a Poisson distributed random variable, with the mean itself random. When this mean is Gamma distributed, then the image classically satisfies the K distribution. We add three new possible distributions for this mean: inverse Gamma, Beta of the first kind, and Beta of the second kind. We show that new intensity distributions so obtained can be estimated, with the interest of the extension validated on a real image.

KW - K law

KW - Pearson system

KW - Scatterer

KW - Speckle

KW - Statistical modeling of SAR images

U2 - 10.1109/TGRS.2002.800234

DO - 10.1109/TGRS.2002.800234

M3 - Article

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JO - IEEE Transactions on Geoscience and Remote Sensing

JF - IEEE Transactions on Geoscience and Remote Sensing

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Modeling non-Rayleigh speckle distribution in SAR images

Abstract

Keywords

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