Optical images-based edge detection in Synthetic Aperture Radar images
Gilberto P. Silva Junior, Alejandro C. Frery, Sandra Sandri and, Humberto Bustince, Edurne Barrenechea, C\'edric Marco-Detchart

TL;DR
This paper adapts optical image edge detection methods for PolSAR imagery, demonstrating that a modified gravitational technique with a non-standard neighborhood outperforms traditional methods in reducing noise and improving edge detection.
Contribution
It introduces a novel adaptation of gravitational edge detection for PolSAR images using a non-standard neighborhood, showing improved performance over existing techniques.
Findings
Modified gravitational edge detection yields better results.
Adapting computational intelligence methods is promising for PolSAR.
Modified method reduces speckle noise effectively.
Abstract
We address the issue of adapting optical images-based edge detection techniques for use in Polarimetric Synthetic Aperture Radar (PolSAR) imagery. We modify the gravitational edge detection technique (inspired by the Law of Universal Gravity) proposed by Lopez-Molina et al, using the non-standard neighbourhood configuration proposed by Fu et al, to reduce the speckle noise in polarimetric SAR imagery. We compare the modified and unmodified versions of the gravitational edge detection technique with the well-established one proposed by Canny, as well as with a recent multiscale fuzzy-based technique proposed by Lopez-Molina et Alejandro We also address the issues of aggregation of gray level images before and after edge detection and of filtering. All techniques addressed here are applied to a mosaic built using class distributions obtained from a real scene, as well as to the true…
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