@InProceedings{PessoaStepFons:2011:FeSeIm,
               author = "Pessoa, Alex Sandro Aguiar and Stephany, Stephan and Fonseca, 
                         Leila Maria Garcia",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Feature Selection and Image Classification Using Rough Sets 
                         Theory",
            booktitle = "Proceedings...",
                 year = "2011",
                pages = "2904--2907",
         organization = "Geoscience and Remote Sensing Symposium, (IGARSS).",
             keywords = "Decision support systems, digital image processing , feature 
                         selection , rough sets theory.",
             abstract = "Current generation of satellite imaging sensors include 
                         multispectral or even hyperspectral devices. The resulting 
                         multiple images that are acquired require new processing and 
                         analysis techniques. Image classification processing demands can 
                         be very high requiring feature/attribute selection in order to 
                         employ a minimum number of bands while keeping good classification 
                         accuracy. This work shows the use of the Rough Sets theory for 
                         multi-band image classification. This theory has a good and simple 
                         mathematical formalism and does not requires further informations 
                         such as the pertinence degree or the probability distribution in 
                         the classification process. The case study was performed with a 
                         7-band Landsat 5 image showing the suitability of the feature 
                         selection approach and its potential to be employed in multi or 
                         hyperspectral image classification.",
  conference-location = "Vancouver",
      conference-year = "24-29 July",
                  doi = "10.1109/IGARSS.2011.6049822",
                  url = "http://dx.doi.org/10.1109/IGARSS.2011.6049822",
                 isbn = "2153-6996 and 978-1-4577-1003-2",
                label = "lattes: 2681016875171472 1 PessoaStepFons:2011:FeSeAn",
             language = "en",
           targetfile = "ENIA_Sessao_Poster_Artigo_11_Parreira.pdf",
               volume = "1",
        urlaccessdate = "28 abr. 2024"
}