Statistical modeling of SAR images: a survey.

Gui Gao

Author Information

Gui Gao: National University of Defence Technology, Changsha 410073, China. dellar@126.com

PMID: 22315568 DOI: 10.3390/s100100775

Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.

parameter estimation probability density function (PDF) statistical models synthetic aperture radar (SAR) images the product model

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Algorithms

Computer Simulation

Image Interpretation, Computer-Assisted

Models, Statistical

Radar

Journal Article Review

OpenLB
Open Library of Bioscience