Nonparametric Edge Detection in Speckled Imagery

Abstract

We address the issue of edge detection in Synthetic Aperture Radar imagery. In particular, we propose nonparametric methods for edge detection, and numerically compare them to an alternative method that has been recently proposed in the literature. Our results show that some of the proposed methods display superior results and are computationally simpler than the existing method. An application to real (not simulated) data is presented and discussed.

Accepted for publication in Mathematics and Computers in Simulation

References in corpus (3)

• Hypothesis Testing in Speckled Data with Stochastic Distances
• On the Use of Lee's Protocol for Speckle-Reducing Techniques
• Sampling Spatially Correlated Clutter

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• The Geodesic Distance between ${\mathcal{G}}_I^0$ Models and its Application to Region Discrimination