@Article{TorresSantFreiFrer:2014:SpRePo,
               author = "Torres, Leonardo and Sant'Anna, Sidnei Jo{\~a}o de Siqueira and 
                         Freitas, Corina da Costa and Frery, Alejandro C.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and Universidade Federal de Alagoas - 
                         UFAL, CPMAT-LaCCAN, Av. Lourival Melo Mota, s/n, Tabuleiro dos 
                         Martins, 57072-900 Macei{\'o} - AL, Brazil",
                title = "Speckle reduction in polarimetric SAR imagery with stochastic 
                         distances and nonlocal means",
              journal = "Pattern Recognition",
                 year = "2014",
               volume = "47",
               number = "1, SI",
                pages = "141--157",
                month = "Jan.",
             keywords = "Hypothesis testing, Information theory, Multiplicative noise, 
                         PolSAR imagery, Speckle reduction, Stochastic distances, Synthetic 
                         aperture radar.",
             abstract = "This paper presents a technique for reducing speckle in 
                         Polarimetric Synthetic Aperture Radar (PolSAR) imagery using 
                         nonlocal means and a statistical test based on stochastic 
                         divergences. The main objective is to select homogeneous pixels in 
                         the filtering area through statistical tests between 
                         distributions. This proposal uses the complex Wishart model to 
                         describe PolSAR data, but the technique can be extended to other 
                         models. The weights of the location-variant linear filter are 
                         function of the p-values of tests which verify the hypothesis that 
                         two samples come from the same distribution and, therefore, can be 
                         used to compute a local mean. The test stems from the family of 
                         (h-Ęsymbol) divergences which originated in Information Theory. 
                         This novel technique was compared with the Boxcar, Refined Lee and 
                         IDAN filters. Image quality assessment methods on simulated and 
                         real data are employed to validate the performance of this 
                         approach. We show that the proposed filter also enhances the 
                         polarimetric entropy and preserves the scattering information of 
                         the targets. © 2013 Elsevier Ltd. All rights reserved.",
                  doi = "10.1016/j.patcog.2013.04.001",
                  url = "http://dx.doi.org/10.1016/j.patcog.2013.04.001",
                 issn = "0031-3203",
                label = "scopus",
             language = "en",
        urlaccessdate = "2024, Apr. 27"
}