DocumentCode :
3642544
Title :
Synthetic aperture radar feature selection for dual polarized ScanSAR data
Author :
N. Gökhan Kasapoğlu
Author_Institution :
Dept. of Electronics and Communication Engineering, Istanbul Technical University, Turkey
fYear :
2011
fDate :
6/1/2011 12:00:00 AM
Firstpage :
370
Lastpage :
374
Abstract :
Synthetic aperture radar (SAR) ScanSAR data has advantages on oceanographic remote sensing applications regarding its large coverage and sufficient resolution. However terrestrial downlink bandwidth is limited and therefore up to dual polarized (e.g., HH and HV) ScanSAR data can be achieved today´s spaceborne systems (e.g., RadarSAT-2). In this study grey level co-occurrence matrix was employed to extract SAR features for both HH and HV channels. Additionally some of band math products such as HH/HV and HH-HV were used as candidate SAR features. Selection of optimum SAR features is crucial and application dependent. In this study, selection strategies based on SAR data assimilation was introduced and relation of conventional separability criterions on SAR data assimilation and pattern recognition were discussed.
Keywords :
"Feature extraction","Sea measurements","Sea ice","Synthetic aperture radar","Data assimilation","Transforms","Data mining"
Publisher :
ieee
Conference_Titel :
Recent Advances in Space Technologies (RAST), 2011 5th International Conference on
Print_ISBN :
978-1-4244-9617-4
Type :
conf
DOI :
10.1109/RAST.2011.5966858
Filename :
5966858
Link To Document :
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