@Article{CarvalhoBinsSant:2019:AnStDi,
               author = "Carvalho, Naiallen Carolyne Rodrigues Lima and Bins, Leonardo 
                         Sant'Anna and Sant'Anna, Sidnei Jo{\~a}o Siqueira",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Analysis of stochastic distances and wishart mixture models 
                         applied on PolSAR images",
              journal = "Remote Sensing",
                 year = "2019",
               volume = "11",
               number = "24",
                pages = "e2994",
             keywords = "stochastic distance, Wishart Mixture Model, PolSAR classification, 
                         Expectation Maximization, K-means.",
             abstract = "This paper address unsupervised classification strategies applied 
                         to Polarimetric Synthetic Aperture Radar (PolSAR) images. We 
                         analyze the performance of complex Wishart distribution, which is 
                         a widely used model for multi-look PolSAR images, and the 
                         robustness of five stochastic distances (Bhattacharyya, 
                         Kullback-Leibler, R{\'e}nyi, Hellinger and Chi-square) between 
                         Wishart distributions. Two unsupervised classification strategies 
                         were chosen: the Stochastic Clustering (SC) algorithm, which is 
                         based on the K-means algorithm but uses stochastic distance as the 
                         similarity metric, and the Expectation-Maximization (EM) algorithm 
                         forWishart Mixture Model. With the aim of assessing the 
                         performance of all algorithms presented here, we performed a Monte 
                         Carlo simulation over a set of simulated PolSAR images. A second 
                         experiment was conducted using the study area of Tapaj{\'o}s 
                         National Forest and the surrounding area, in Brazilian Amazon 
                         Forest. The PolSAR images were obtained by the satellite PALSAR. 
                         The results, in both experiments, suggest that the EM algorithm 
                         and the SC with Hellinger and the SC with Bhattacharyya distance 
                         provide a better classification performance. We also analyze the 
                         initialization problem for SC and EM algorithms, and we 
                         demonstrate how the initial centroid choice influences the final 
                         classification result.",
                  doi = "10.3390/rs11242994",
                  url = "http://dx.doi.org/10.3390/rs11242994",
                 issn = "2072-4292",
             language = "en",
           targetfile = "carvalho_analysis.pdf",
        urlaccessdate = "23 abr. 2024"
}