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@InProceedings{HomemMartMasc:2007:SuImRe,
               author = "Homem, Murillo Rodrigo Petrucelli and Martins, Ana Lu{\'{\i}}sa 
                         Dine and Mascarenhas, Nelson Delfino d'{\'A}vila",
          affiliation = "Departamento de Computa{\c{c}}{\~a}o, Universidade Federal de 
                         S{\~a}o Carlos and Departamento de Computa{\c{c}}{\~a}o, 
                         Universidade Federal de S{\~a}o Carlos and Departamento de 
                         Computa{\c{c}}{\~a}o, Universidade Federal de S{\~a}o Carlos",
                title = "Super-Resolution Image Reconstruction using the Discontinuity 
                         Adaptive ICM",
            booktitle = "Proceedings...",
                 year = "2007",
               editor = "Gon{\c{c}}alves, Luiz and Wu, Shin Ting",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 20. 
                         (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "Super resolution image reconstruction, sub-pixel image 
                         registration.",
             abstract = "We propose a Bayesian approach for the super resolution image 
                         reconstruction (SRIR) problem using a Markov random field (MRF) 
                         for image characterization. SRIR consists in using a set of 
                         low-resolution (LR) images from the same scene to generate a 
                         high-resolution (HR) estimate of the original object. Using a 
                         Bayesian formulation, it is possible to incorporate previously 
                         known spatial information about the HR image to be estimated. In 
                         our approach, the iterated conditional modes (ICM) algorithm is 
                         used to find the maximum a posteriori (MAP) solution, and a 
                         discontinuity adaptive framework is used to overcome the 
                         oversmoothness inherent to MAP-MRF formulations. To evaluate the 
                         capability of the algorithm in reconstructing the actual image, we 
                         used the universal image quality index (UIQI). According to this 
                         index, the proposed method produced accurate results.",
  conference-location = "Belo Horizonte",
      conference-year = "Oct. 7-10, 2007",
             language = "en",
           targetfile = "icm-mrph.pdf",
        urlaccessdate = "2020, Oct. 26"
}


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