@InProceedings{DoblasPrietoFreSiqCarShi:2021:AsNoMe,
               author = "Doblas Prieto, Juan and Frery, Alejandro C. and Siqueira, 
                         Sant'Anna Sidnei Jo{\~a}o and Carneiro, Arian Ferreira and 
                         Shimabukuro, Yosio Edemir",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Victoria 
                         University of Wellington} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Assessment of nonlocal means stochastic distances speckle 
                         reduction for SAR time series",
            booktitle = "Proceedings...",
                 year = "2021",
         organization = "International Geoscience and Remote Sensing Symposium (IGARSS)",
            publisher = "IEEE",
              address = "Breussels",
             keywords = "Speckle filters, SAR timeseries, Quality, Assessment.",
             abstract = "Implementation of complex SAR speckle filtering algorithms is 
                         usually limited to experimental settings, that make use of 
                         heavy-duty computers or processing clusters. Operational 
                         applications of SAR imagery, such as those used to map 
                         flashflooded areas, or to flag on-going deforestation, usually are 
                         not able to take advantage of these advanced filtering techniques. 
                         Here we introduce SDNLM3D, a fast and effective 3D filtering 
                         algorithm based on the non-local paradigm, suitable to be applied 
                         on cloud environments, such as the Google Earth Engine (GEE). A 
                         systematic, real-world based benchmark of more than 700 variations 
                         of the SDNLM3D revealed that the optimized version of the SDNLM3D 
                         filter outperforms the usual filters used operationally.",
  conference-location = "Online",
      conference-year = "12-16 July",
             language = "en",
           targetfile = "doblas_2021.pdf",
        urlaccessdate = "2024, Apr. 28"
}