@Article{SilvaFreiSantFrer:2013:ClSePo,
               author = "Silva, Wagner Barreto da and Freitas, Corina da Costa and 
                         Sant'Anna, Sidnei Jo{\~a}o Siqueira and Frery, Alejandro Cesar",
          affiliation = "Instituto Militar de Engenharia, Se{\c{c}}{\~a}o de Engenharia 
                         Cartogr{\'a}fica, Rio de Janeiro, 22290270 Brazil. and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and h Universidade Federal de Alagoas, 
                         Centro de Inform{\'a}tica, Macei{\'o}, AL, 57072-970 Brazil.",
                title = "Classification of Segments in PolSAR Imagery by Minimum Stochastic 
                         Distances Between Wishart Distributions",
              journal = "IEEE Journal of Selected Topics in Applied Earth Observations and 
                         Remote Sensing",
                 year = "2013",
               volume = "6",
               number = "3",
                pages = "1263--1273",
                month = "Jul.",
             keywords = "hypothesis tests, polarimetry, region-based classification, 
                         stochastic distances, Wishart distribution.",
             abstract = "A new classifier for Polarimetric SAR (PolSAR) images is proposed 
                         and assessed in this paper. Its input consists of segments, and 
                         each one is assigned the class which minimizes a stochastic 
                         distance. Assuming the complexWishart model, several stochastic 
                         distances are obtained from the h - phi family of divergences, and 
                         they are employed to derive hypothesis test statistics that are 
                         also used in the classification process. This article also 
                         presents, as a novelty, analytic expressions for the test 
                         statistics based on the following stochastic distances between 
                         complex Wishart models: Kullback-Leibler, Bhattacharyya, 
                         Hellinger, R{\'e}nyi, and Chi-Square; also, the test statistic 
                         based on the Bhattacharyya distance between multivariate Gaussian 
                         distributions is presented. The classifier performance is 
                         evaluated using simulated and real PolSAR data. The simulated data 
                         are based on the complex Wishart model, aiming at the analysis of 
                         the proposal with controlled data. The real data refer to a 
                         complex L-band image, acquired during the 1994 SIR-C mission. The 
                         results of the proposed classifier are compared with those 
                         obtained by aWishart per-pixel/contextual classifier, and we show 
                         the better performance of the region-based classification. The 
                         influence of the statistical modeling is assessed by comparing the 
                         results using the Bhattacharyya distance between multivariate 
                         Gaussian distributions for amplitude data. The results with 
                         simulated data indicate that the proposed classification method 
                         has very good performance when the data follow the Wishart model. 
                         The proposed classifier also performs better than the 
                         per-pixel/contextual classifier and the Bhattacharyya Gaussian 
                         distance using SIR-C PolSAR data.",
                  doi = "10.1109/jstars.2013.2248132",
                  url = "http://dx.doi.org/10.1109/jstars.2013.2248132",
                 issn = "1939-1404",
                label = "lattes: 2549014594120288 2 SilvaFreiSantFrer:2013:ClSePo",
             language = "en",
           targetfile = "06477176.pdf",
        urlaccessdate = "27 abr. 2024"
}