@InProceedings{DutraLimaKörtShim:2019:EvReTe,
               author = "Dutra, Andeise Cerqueira and Lima, Luciana Shigihara and 
                         K{\"o}rting, Thales Sehn and Shimabukuro, Yosio Edemir",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Evaluation of restoration technique in complex landscape areas",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "2223--2226",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Linear spectral mixing model, supervised classification, Landsat-5 
                         TM, image restoration.",
             abstract = "In remote sensing images, the problems related to spatial 
                         resolution, image degradation and pixel mixture could particularly 
                         affect heterogeneous areas. Restoration is a technique that aims 
                         to correct radiometric distortions and, combined with a resampling 
                         filter, generates images in a finer grid with improved visual 
                         quality. This study aims to evaluate the effectiveness of 
                         restoration technique to improve quantitative measurements of 
                         classification in complex landscape areas. For this purpose, a 
                         Landsat 5 Thematic Mapper image with 30 m spatial resolution was 
                         processed using restoration and resampling techniques, resulting 
                         in a 15 m spatial resolution image. Preliminary results applying a 
                         linear spectral mixing model, followed by supervised 
                         classification indicated that the restored image showed better 
                         visual quality, thus allowing to detect targets in the scene with 
                         more details. However, a quantitative comparison between processed 
                         and original images, resulted in slight differences (±0.003) in 
                         classification accuracy.",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3U9HQM8",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U9HQM8",
           targetfile = "97814.pdf",
                 type = "Processamento de imagens",
        urlaccessdate = "27 abr. 2024"
}