@InProceedings{GenovezFreSanBenLor:2015:OiSlDe,
author = "Genovez, Patr{\'{\i}}cia Carneiro and Freitas, Corina da Costa
and Sant'Anna, Sidnei Jo{\~a}o Siqueira and Bentz, Cristina and
Lorenzzetti, Jo{\~a}o Ant{\^o}nio",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Petrobr{\'a}s Research Center}
and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Oil slicks detection using a polarimetric region classifier",
booktitle = "Proceedings...",
year = "2015",
organization = "IEEE International Geoscience and Remote Sensing Symposium
(IGARSS)",
keywords = "Synthetic Aperture Radar (SAR), Polarimetry, Region Based
Classification, Stochastic Distances, Oil Slicks.",
abstract = "A new region based classifier for polarimetric synthetic aperture
radar data (PolSAR) was tested to evaluate its potential to
discriminate different types of oil slicks at sea surface. This
classifier uses a supervised approach to compare stochastic
distances between complex Wishart distributions and hypothesis
tests to associate confidence levels to the classification
results. The preliminary results using the Battacharyya distance
were promising, returning an overall accuracy of 90.61% at a
significance level of 5%. Future works may compare the performance
of different stochastic distances, together with the insertion of
polarimetric features to improve the oil slicks classification.",
conference-location = "Milan, Italy",
conference-year = "23-31 July",
language = "en",
urlaccessdate = "03 jun. 2024"
}