@InProceedings{DutraIiMasc:1984:EvEnJM,
               author = "Dutra, Luciano Vieira and Ii, Fernando Augusto Mitsuo and 
                         Mascarenhas, Nelson Delfino D'Avila",
                title = "Evaluation of entropy and JM-distance criterions as features 
                         selection methods using spectral and spatial features derived from 
                         Landsat images",
            booktitle = "Anais...",
                 year = "1984",
                pages = "580",
         organization = "International Congress of Photogrammetry and Remote Sensing, 15.",
             keywords = "PROCESSAMENTO DIGITAL DE IMAGENS, ENTROPIA, DIGITAL PROCESSING AND 
                         CORRECTION, ENTROPY.",
             abstract = "This research had the purpose of evaluating the performance of 
                         entropy and JM-distance feature selection methods, using LANDSAT 
                         satellite images. A study area near Ribeirao Preto in Sao Paulo 
                         state was selected, with predominance in sugar cane. Eight 
                         features were extracted from the 4 origird bords of LANDSAT image, 
                         using low-pass and high-pass filtering to obtain spatial features. 
                         There were 5 training sites in order to acquire the necessary 
                         parameters. Two groups of four channels were selected from 12 
                         channels using JM-distance and entropy criterions. The number of 
                         selected channels was defined by physical restrictions of the 
                         image analyser and computacional costs. The evaluation was 
                         performed by extracting the confusion matrix for training and 
                         tests areas, with a maximum likelihood classifier, and by defining 
                         performance indexes based on those matrixes for each group of 
                         channels. The results showed that in spatial features and 
                         supervides classification, the entropy criterion is better ins the 
                         sense that allows a more accurate and generalized definition of 
                         class signature. On the other hand, JM-distance criterion strongly 
                         reduces the misclassification within training areas.",
  conference-location = "Rio de Janeiro, BR",
      conference-year = "18-29 June 1984",
                label = "602",
             language = "en",
         organisation = "ISPRS",
           targetfile = "INPE 3122.pdf",
        urlaccessdate = "08 maio 2024"
}