@InProceedings{KortingCastFons:2011:DiSeAl,
               author = "Korting, Thales Sehn and Castejon, Emiliano Ferreira and Fonseca, 
                         Leila Maria Garcia",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Divide and Segment – An alternative for parallel segmentation",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Vinhas, L{\'u}bia and Davis J{\'u}nior, Clodoveu Augusto",
                pages = "97--104",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 12. (GEOINFO).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Remote sensing images with large sizes are usual. They also 
                         include several spectral channels, increasing the volume of 
                         information. To get valuable information from data automatically, 
                         computers need higher amounts of memory and efficient processing 
                         techniques. Segmentation is a key technique to deal with remote 
                         sensing. It identifies regions in images. Therefore, it deals with 
                         large amounts of information. Even with current computational 
                         power, some image sizes exceed the memory limits, which need 
                         different solutions. An alternative to overcome such limits is to 
                         employ divide and conquer strategy, splitting the image into 
                         tiles, and segmenting each one individually. However, arises the 
                         problem of merging neighboring tiles and keeping the homogeneity 
                         in such regions. In this work, we propose an alternative to create 
                         the tiles, by defining noncrisp borders between tiles, but 
                         adaptive borders for the tiles. By applying our method, we avoid 
                         the postprocessing of neighboring regions, and therefore speed up 
                         the final segmentation.",
  conference-location = "Campos do Jord{\~a}o",
      conference-year = "27-29 nov. 2011",
                 issn = "2179-4820",
             language = "en",
                  ibi = "8JMKD3MGP8W/3B25HBP",
                  url = "http://urlib.net/ibi/8JMKD3MGP8W/3B25HBP",
           targetfile = "thales.pdf",
        urlaccessdate = "2024, Apr. 28"
}