Document - Modeling SAR images with a generalization of the rayleigh distribution

2004

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Modeling SAR images with a generalization of the rayleigh distribution

Kuruoglu E. E., Zerubia J.

speckle noise SAR images generalised Rayleigh distribution Fractional lower order statistics Software Computer Graphics and Computer-Aided Design alpha stable distributions radar imagery Negative order statistics

Synthetic aperture radar (SAR) imagery has found important applications due to its clear advantages over optical satellite imagery one of them being able to operate in various weather conditions. However, due to the physics of the radar imaging process, SAR images contain unwanted artifacts in the form of a granular look which is called speckle. The assumptions of the classical SAR image generation model lead to a Rayleigh distribution model for the histogram of the SAR image. However, some experimental data such as images of urban areas show impulsive characteristics that correspond to underlying heavytailed distributions, which are clearly nonRayleigh. Some alternative distributions have been suggested such as the Weibull, lognormal, and the kdistribution which had success in varying degrees depending on the application. Recently, an alternative model namely the stable distribution has been suggested for modeling radar clutter. In this paper, we show that the amplitude distribution of the complex wave, the real and the imaginery components of which are assumed to be distributed by the stable distribution, is a generalization of the Rayleigh distribution. We demonstrate that the amplitude distribution is a mixture of Rayleighs as is the k distribution in accordance with earlier work on modeling SAR images which showed that almost all successful SAR image models could be expressed as mixtures of Rayleighs. We also present parameter estimation techniques based on negative order moments for the new model. Finally, we test the performance of the model on urban images and compare with other models such as Rayleigh, Weibull, and the k distribution.

Source: IEEE transactions on image processing 13 (2004): 527–533. doi:10.1109/TIP.2003.818017

Publisher: Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America

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@article{oai:it.cnr:prodotti:43763,
	title = {Modeling SAR images with a generalization of the rayleigh distribution},
	author = {Kuruoglu E. E. and Zerubia J.},
	publisher = {Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America},
	doi = {10.1109/tip.2003.818017},
	journal = {IEEE transactions on image processing},
	volume = {13},
	pages = {527–533},
	year = {2004}
}