@InProceedings{BragaFreiSant:2015:MuClBa,
author = "Braga, Bruna Cristina and Freitas, Corina da Costa and Sant'Anna,
Sidnei Jo{\~a}o Siqueira",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Multisource classification based on uncertainty maps",
booktitle = "Proceedings...",
year = "2015",
organization = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "IEEE",
keywords = "Multisource classification, statistical region-based
classification, stochastic distances.",
abstract = "A new methodology to perform classification of multisource data is
proposed in this work. The technique takes into account the
classification results (a classified image and an uncertainty map)
derived from each data source in order to generate a new
classified image. It is based on a region-based classifier which
employs stochastic distances, statistical tests and reliability of
the classification to produce a final classification. Images
acquired from two distinct and independent data sources (optical
and microwave sensors) were used to validate the proposed
methodology. One LANDSAT5/TM image and one ALOS/PALSAR image from
a region on Brazilian Amazon were classified, firstly individually
and then using the proposed classification technique. The results
showed that the individual classification results can be improved
by the use of our multisource classification technique. It can be
concluded that this new method to combine information derived from
different data sources is strongly promising.",
conference-location = "Milan, Italy",
conference-year = "23-31 July",
doi = "10.1109/IGARSS.2015.7326508",
url = "http://dx.doi.org/10.1109/IGARSS.2015.7326508",
isbn = "9781479979295",
language = "en",
urlaccessdate = "19 abr. 2024"
}