Nonparametric Edge Detection in Speckled Imagery
This work addresses edge detection for Synthetic Aperture Radar imagery, presenting incremental improvements in method efficiency and performance.
The paper tackled edge detection in Synthetic Aperture Radar imagery by proposing nonparametric methods, showing that some methods achieve superior results and are computationally simpler than an existing alternative, with an application to real data.
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.