@InProceedings{TorresFrer:2013:SAImDe,
               author = "Torres, Leonardo Jos{\'e} Ten{\'o}rio Mour{\~a}o and Frery, 
                         Alejandro C{\'e}sar",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federal de Alagoas (UFAL)}",
                title = "SAR Image Despeckling Algorithms using Stochastic Distances and 
                         Nonlocal Means",
            booktitle = "Proceedings...",
                 year = "2013",
               editor = "Falc{\~a}o, Alexandre and Paulovich, Fernando",
                pages = "1--6",
         organization = "Conference on Graphics, Patterns and Images, 26. (SIBGRAPI).",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "Imagens SAR, Speckle reduction, Stochastic distances, Information 
                         theory.",
             abstract = "This paper presents two approaches for filter design based on 
                         stochastic distances for intensity speckle reduction. A window is 
                         defined around each pixel, overlapping samples are compared and 
                         only those which pass a goodness-of-fit test are used to compute 
                         the filtered value. The tests stem from stochastic divergences 
                         within the Information Theory framework. The technique is applied 
                         to intensity Synthetic Aperture Radar (SAR) data with homogeneous 
                         regions using the Gamma model. The first approach uses a 
                         Nagao-Matsuyama-type procedure for setting the overlapping 
                         samples, and the second uses the nonlocal method. The proposals 
                         are compared with the Improved Sigma filter and with anisotropic 
                         diffusion for speckled data (SRAD) using a protocol based on Monte 
                         Carlo simulation. Among the criteria used to quantify the quality 
                         of filters, we employ the equivalent number of looks, and line and 
                         edge preservation. Moreover, we also assessed the filters by the 
                         Universal Image Quality Index and by the Pearson correlation 
                         between edges. Applications to real images are also discussed. The 
                         proposed methods show good results.",
  conference-location = "Arequipa, Peru",
      conference-year = "5-8 Aug. 2013",
                label = "lattes: 7832536123089184 1 TorresFrer:2013:SAImDe",
             language = "en",
           targetfile = "Torres_sar.pdf",
                  url = "http://www.ucsp.edu.pe/sibgrapi2013/eproceedings",
        urlaccessdate = "2024, Apr. 28"
}