Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data
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Data
2011-10-19
Autores
Paes, Rafael L.
Pagamisse, Aylton [UNESP]
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Resumo
We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.
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decision trees, remote sensing, SAR, target detection, wavelets, Data source, Descriptors, Image descriptors, Maritime surveillance, Oblique decision tree, Ocean feature, SAR data, SAR Images, Sea surfaces, Ship wakes, Statistical parameters, Decision trees, Information technology, Plant extracts, Remote sensing, Ships, Trees (mathematics), Discrete wavelet transforms
Como citar
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 6935 LNCS, p. 582-589.