@InProceedings{ContatoNazParPonBat:2016:ImNoVi,
               author = "Contato, Welinton Andrey and Nazare, Tiago Santana and Paranhos da 
                         Costa, Gabriel de Barros and Ponti, Moacir and Batista Neto, 
                         Jo{\~a}o do Espirito Santo",
          affiliation = "{Instituto de Ci{\^e}ncias Matem{\'a}ticas e de 
                         Computa{\c{c}}{\~a}o - USP} and {Instituto de Ci{\^e}ncias 
                         Matem{\'a}ticas e de Computa{\c{c}}{\~a}o - USP} and {Instituto 
                         de Ci{\^e}ncias Matem{\'a}ticas e de Computa{\c{c}}{\~a}o - 
                         USP} and {Instituto de Ci{\^e}ncias Matem{\'a}ticas e de 
                         Computa{\c{c}}{\~a}o - USP} and {Instituto de Ci{\^e}ncias 
                         Matem{\'a}ticas e de Computa{\c{c}}{\~a}o - USP}",
                title = "Improving Non-Local Video Denoising with Local Binary Patterns and 
                         Image Quantization",
            booktitle = "Proceedings...",
                 year = "2016",
               editor = "Aliaga, Daniel G. and Davis, Larry S. and Farias, Ricardo C. and 
                         Fernandes, Leandro A. F. and Gibson, Stuart J. and Giraldi, Gilson 
                         A. and Gois, Jo{\~a}o Paulo and Maciel, Anderson and Menotti, 
                         David and Miranda, Paulo A. V. and Musse, Soraia and Namikawa, 
                         Laercio and Pamplona, Mauricio and Papa, Jo{\~a}o Paulo and 
                         Santos, Jefersson dos and Schwartz, William Robson and Thomaz, 
                         Carlos E.",
         organization = "Conference on Graphics, Patterns and Images, 29. (SIBGRAPI)",
            publisher = "IEEE Computer Society´s Conference Publishing Services",
              address = "Los Alamitos",
             keywords = "local binary patterns, most significant bits, non-local means, 
                         video denoising.",
             abstract = "The most challenging aspect of video and image denoising is to 
                         preserve texture and small details, while filtering out noise. To 
                         tackle such problem, we present two novel variants of the 3D 
                         Non-Local Means (NLM3D) which are suitable for videos and 3D 
                         images. The first proposed algorithm computes texture patterns for 
                         each pixel by using the LBP-TOP descriptor to modify the NLM3D 
                         weighting function. It also uses MSB (Most Significant Bits) 
                         quantization to improve robustness to noise. The second proposed 
                         algorithm filters homogeneous and textured regions differently. It 
                         analyses the percentage of non-uniform LBP patterns of a region to 
                         determine whether or not the region exhibits textures and/or small 
                         details. Quantitative and qualitative experiments indicate that 
                         the proposed approaches outperform well known methods for the 
                         video denoising task, especially in the presence of textures and 
                         small details.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
                  doi = "10.1109/SIBGRAPI.2016.041",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2016.041",
             language = "en",
                  ibi = "8JMKD3MGPAW/3M42622",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3M42622",
           targetfile = "PID4356503.pdf",
        urlaccessdate = "2024, Apr. 28"
}