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@InProceedings{AcevedoRued:2005:ReInCo,
               author = "Acevedo, Daniel Germ{\'a}n and Ruedin, Ana Mar{\'{\i}}a Clara",
          affiliation = "{University of Buenos Aires}",
                title = "Reduction of interband correlation for Landsat image 
                         compression.",
            booktitle = "Proceedings...",
                 year = "2005",
               editor = "Rodrigues, Maria Andr{\'e}ia Formico and Frery, Alejandro 
                         C{\'e}sar",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 18. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Multispectral satellite image, correlation, wavelet, lossless 
                         compression.",
             abstract = "We present a lossless compressor for multispectral images that 
                         exploits interband correlations. Each band is divided into blocks, 
                         to which a wavelet transform is applied. The wavelet coefficients 
                         are predicted by means of a linear combination of coefficients 
                         belonging to the same orientation and spatial location. The 
                         prediction errors are then encoded with an entropy - based coder. 
                         Our original contributions are i) the inclusion, among the 
                         candidates for prediction, of coefficients of the same location 
                         from other spectral bands, ii) the calculation of weights tuned to 
                         the landscape being processed, iii) a fast block classification 
                         and a different band-ordering for each landscape. Our compressor 
                         reduces the size of an image to about a fourth of its original 
                         size. Our method is equivalent to LOCO-I, on 3 of the images 
                         tested it was superior. It is superior to other lossless 
                         compressors: WinZip, JPEG2000 and PNG.",
  conference-location = "Natal",
      conference-year = "9-12 Oct. 2005",
             language = "en",
           targetfile = "acevedod_lsatcompression.pdf",
        urlaccessdate = "2020, Nov. 29"
}


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