@techreport{TR-IC-14-02,
   number = {IC-14-02},
   author  =  {Ambra Melloni and Marco Tagliasacchi and Stefano Tubaro
                   and  Filipe de O.Costa and Marina Oikawa and Zanoni
                   Dias and Siome Goldenstein and Anderson Rocha},
   title = {Signal Processing Analysis applied to Image Phylogeny},
   month = {January},
   year = {2014},
   institution   =   {Dipartimento   di  Elettronica,  Informazione  e 
                   Bioingegneria (Politecnico di Milano) and Institute
                   of Computing (University of Campinas)},
   note = {In English, 9 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       This  work  is  a  report about the effect of denoising filters
       applied  to image phylogeny, as conclusion of the collaboration
       between  Politecnico  di  Milano and UNICAMP, inside the REWIND
       project.   The   purpose  of  image  phylogeny  is  discovering 
       dependencies  among  a  group of images representing similar or
       equal  contents  in  order to construct a tree describing image
       relationships.   We   applied  a  family  of  image  processing 
       techniques  to  a  set  of  images, in order to create parental
       relationship.  Operating  in the wavelet domain, it is possible
       to  apply  denoise filters in the images, separating each image
       in two contributions: a component part (the denoised image) and
       a randomness part (the noise). We evaluate the effectiveness of
       this  method for three different database, using subsets of the
       image  processing  functions:  in  this  report,  we  show that
       geometric transformation imperfections influence the results of
       denoising  algorithm  highly,  when  reconstructing  trees  for 
       component and randomness parts.
  }
}