@InProceedings{OliveiraDutrRennCruz:2009:MéEsSe,
               author = "Oliveira, Joanito de Andrade and Dutra, Luciano Vieira and 
                         Renn{\'o}, Camilo Daleles and Cruz Junior, Dion{\'{\i}}sio 
                         Costa",
          affiliation = "{Universidade Federal do Rec{\^o}ncavo da Bahia} and {Instituto 
                         Nacional de Pesquisas Espaciais} and {Instituto Nacional de 
                         Pesquisas Espaciais} and {Escola de Engenharia de Agrimensura}",
                title = "M{\'e}todo Estat{\'{\i}}stico de Sele{\c{c}}{\~a}o de Canais 
                         Aplicado a Classifica{\c{c}}{\~a}o de Imagens",
            booktitle = "Anais...",
                 year = "2009",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "7007--7014",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "feature selection, image processing, multispectra image, 
                         sele{\c{c}}{\~a}o de atributos, processamento de imagens, 
                         imagens multiespectrais.",
             abstract = "With the steady increase in the number of features available from 
                         remote sensing sources, there is a growing necessity to reduce the 
                         complexity of the classification task. When data dimensionality is 
                         very high, a search strategy should be used to select the subset 
                         of features that gives the minimum classification error, 
                         considering the limited size of training data. Particularly when 
                         one deals with the very complex environment that is the urban 
                         scene, shape feature extraction is necessary to distinguish 
                         different classes of objects which have similar spectral 
                         signature. The objective of the work is to extract feature of the 
                         regions of a Landsat5 /TM image and to reduce the dimensionality, 
                         of form that does not occur loss in the efficiency in the 
                         classification process. As there is no a deterministic relation 
                         between feature selection methods and classification error, it is 
                         possible to conclude that all search strategies should be used to 
                         narrow the number of choices assessments based on classification 
                         error. The system was developed in IDL/ENVI. The results present 
                         the viability to use the methods of selection of attributes, 
                         objectifying the reduction of the dimensionality without losing 
                         the discriminatory power between the class. Further studies are 
                         being done aiming to implement evaluation methods for 
                         classification.",
  conference-location = "Natal",
      conference-year = "25-30 abr. 2009",
                 isbn = "978-85-17-00044-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2008/11.17.22.45.53",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.17.22.45.53",
           targetfile = "7007-7014.pdf",
                 type = "Processamento de Imagens",
        urlaccessdate = "15 jun. 2024"
}