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Characterization of local regularity in SAR Imagery by means of multiscale techniques: application to oil spill detection

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9 Author(s)
Marivi Tello ; Remote Sensing Laboratory (RSLAB) Universitat Politecnica de Catalunya (UPC) Barcelona, Spain ; Ramon Bonastre ; Carlos Lopez-Martinez ; Jordi J. Mallorqui
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Thanks to their capability to cover large areas, in all weather conditions, during the day as well as during the night, spaceborne Synthetic Aperture Radar (SAR) techniques constitute an extremely promising alternative to traditional surveillance methods. Nevertheless, in order to assure further usability of SAR images, specific data mining tools are still to be developed to provide an efficient automatic interpretation of SAR data. The aim of this paper is to introduce texture analysis performed in the framework of time - frequency theory, as a means to detect oil spills in the sea surface. In particular, an algorithm permitting a precise quantitative characterization of the border between the oil spill candidate and the sea, will allow a novel classification of oil spills and look-alikes.

Published in:

2007 IEEE International Geoscience and Remote Sensing Symposium

Date of Conference:

23-28 July 2007