@Article{SilvaJúniorFrSaBuBaMa:2015:OpImEd,
               author = "Silva J{\'u}nior, Gilberto Pedro da and Frery, Alejandro C. and 
                         Sandri, Sandra Aparecida and Bustince, Humberto and Barrenechea, 
                         Edume and Marco-Detchart, Cedric",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Optical images-based edge detection in Synthetic Aperture Radar 
                         images",
              journal = "Knowledge Based Systems",
                 year = "2015",
               volume = "87",
                pages = "38--46",
                month = "Oct.",
             keywords = "Edge detection, SAR images, Computational Intelligence, 
                         Gravitational method.",
             abstract = "We address the issue of adapting optical images-based edge 
                         detection techniques for use in Polarimetric Synthetic Aperture 
                         Radar (PoISAR) imagery. We modify the gravitational edge detection 
                         technique (inspired by the Law of Universal Gravity) proposed by 
                         Lopez-Molina et al., using the non-standard neighbourhood 
                         configuration proposed by Fu et al., to reduce the speckle noise 
                         in polarimetric SAR imagery. We compare the modified and 
                         unmodified versions of the gravitational edge detection technique 
                         with the well-established one proposed by Canny, as well as with a 
                         recent multiscale fuzzy-based technique proposed by Lopez-Molina 
                         et al. We also address the issues of aggregation of gray level 
                         images before and after edge detection and of filtering. All 
                         techniques addressed here are applied to a mosaic built using 
                         class distributions obtained from a real scene, as well as to the 
                         true PoISAR image; the mosaic results are assessed using 
                         Baddeley's Delta Metric. Our experiments show that modifying the 
                         gravitational edge detection technique with a non-standard 
                         neighbourhood configuration produces better results than the 
                         original technique, as well as the other techniques used for 
                         comparison. The experiments show that adapting edge detection 
                         methods from Computational Intelligence for use in PoISAR imagery 
                         is a new field worthy of exploration.",
                  doi = "10.1016/j.knosys.2015.07.030",
                  url = "http://dx.doi.org/10.1016/j.knosys.2015.07.030",
                 issn = "0950-7051",
             language = "en",
           targetfile = "2015-silva junior.pdf",
        urlaccessdate = "27 abr. 2024"
}