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@InProceedings{NacifFern:2017:MuSuPa,
               author = "Nacif, Felippe Leit{\~a}o and Fernandes, Leandro Augusto Frata",
          affiliation = "{Universidade Federal Fluminense} and {Universidade Federal 
                         Fluminense}",
                title = "Multi-Frame super-resolu{\c{c}}{\~a}o a partir de uma {\'u}nica 
                         imagem por estereoscopia",
            booktitle = "Proceedings...",
                 year = "2017",
               editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and 
                         Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and 
                         Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba, 
                         Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo 
                         and Vital, Creto and Pagot, Christian Azambuja and Petronetto, 
                         Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
         organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "super-resolu{\c{c}}{\~a}o, lentes estereosc{\'o}picas, 
                         iterative back projection.",
             abstract = "Super-resolution (SR) is a set of techniques that estimates a 
                         high-resolution (HR) image from one or more low-resolution (LR) 
                         images. Single-frame SR usually relies on learn-based methods to 
                         enhance a LR image. Multi-frame SR, on the other hand, may not 
                         assume previous knowledge of the scene and use information 
                         extracted from multiple LR images taken from slightly different 
                         viewpoints to estimate a HR view. We present a multi-frame SR 
                         approach that uses a stereoscopic camera lens attachment to 
                         capture two overlapped views of the scene at the same time with 
                         the same image sensor. We adapt the classic Iterative Back 
                         Projection (IBP) SR algorithm to estimate a SR color image from 
                         two color LR views. We virtually modeled the proposed lens 
                         attachment and demonstrate that, by using only two overlapped 
                         views, our approach achieves qualitatively better results than 
                         other multi-frame SR techniques.",
  conference-location = "Niter{\'o}i, RJ",
      conference-year = "Oct. 17-20, 2017",
             language = "pt",
                  ibi = "8JMKD3MGPAW/3PJQBDS",
                  url = "http://urlib.net/rep/8JMKD3MGPAW/3PJQBDS",
           targetfile = "2017___Nacif__Fernandes___SIBGRAPI___WUW.pdf",
        urlaccessdate = "2021, Jan. 21"
}


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