Abstract
In areas of difficult access, such as the arctic ones, the extraction of inter- est zones (e.g. glaciers) from satellite images may be a valuable way to study and monitor their status . This work faces in particular the prob- lem of detecting different zones of glaciers from SAR (Synthetic Aperture Radar) images. In the polar regions the use of the SAR system is funda- mental because it works independently of weather and daylight. Segmentation is a process that allows an image to be divided into disjoint zones in such a way that each extracted area contains homogeneous char- acteristics. The numerical approach, here applied to detect glacier zones, is based on moving boundary modelling and is described by the eikonal equation. The upwind finite difference approximation of the eikonal equa- tion is solved by a fast marching technique, that starts from seed points in the region of interest and generates a front which evolves until the bound- ary of the region is identified.
Results from segmentation of glacier images in the Svalbard archipelago acquired by ERS2 SAR (Synthetic Aperture Radar) and Envisat (ESA Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) are presented and discussed.
Anno
2013
Autori IAC
Tipo pubblicazione
Altri Autori
Rossella Cossu, Daniela Mansutti, Malgorzata Blaszczyk
Editore
Rutgers University, Dept. of Computer Science.
Rivista
IMACS series computational and applied mathematics