A user-friendly system for synthetic aperture radar image classification based on grayscale distributional properties and context

Alejandro C. FreryCorina da C. F. YanassePedro R. VieiraSidnei J. S. SantannaCamilo D. Renno

The purpose of this paper is to present a system for the analysis and classification of Synthetic Aperture Radar (SAR) images. This system, unlike most of its competitors, allows a careful modeling of the statistical properties of the data beyond the usual Gaussian hypothesis. The modeling tools include basic descriptive measures and the choice of suited distributions, through goodness-of-fit tests, to model the data. The classification tools offer the choice between pointwise and contextual (Markovian) techniques, and the quantitative assessment of the quality of the results. The system is goal-driven, and its interfaces are solely based on pull-down menus; the user is prompted with the correct sequence of operations, whenever an invalid option is invoked. An example of the use of this system for the classification of a SAR image is presented.

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