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@PHDTHESIS{Thakur:765565,
      author       = {Thakur, Uday Singh},
      othercontributors = {Ohm, Jens-Rainer and Bull, David},
      title        = {{P}erceptual video coding using steerable pyramids},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      reportid     = {RWTH-2019-07494},
      pages        = {1 Online-Ressource (xiv, 98 Seiten) : Illustrationen,
                      Diagramme},
      year         = {2018},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University 2019; Dissertation, Rheinisch-Westfälische
                      Technische Hochschule Aachen, 2018},
      abstract     = {In the context of this thesis we are mainly focused on
                      developing coding tools for static and dynamic textures.
                      Both static and dynamic textures are challenging to code for
                      the current generation video codecs. Former is characterized
                      with high amount of spatial variations which are randomly
                      distributed over the textured region. At low bitrates such a
                      content often shows relatively higher blocking and blurring
                      artefacts as compared to a non-textured content. As a
                      proposed solution to this problem, texture synthesis based
                      on steerable pyramids is used at the decoder side for
                      generating artificial textures using coded parameters. The
                      results provided in this thesis prove that a much better
                      visual quality is achievable at low bitrates when compared
                      to the HEVC. Dynamic textures are characterized with complex
                      motion patterns e.g. water waves, leaves swirling in the
                      wind etc. Due to highly dynamic nature of the motion in such
                      a content, motion compensation often fails to find a good
                      predictor and as a result B-pictures are expensive to code.
                      Under low bit-rate conditions, heavy blocking and blurring
                      artefacts are often observed in the B-pictures. In our
                      proposed solution for the dynamic textures we target those
                      pictures that are most susceptible to these artefacts (i.e.
                      pictures corresponding to two highest temporalids) and code
                      these pictures in a reduced resolution format. At the
                      decoder side these pictures are up-sampled with
                      high-frequency synthesis using information from the
                      neighboring full resolution pictures. The results provide a
                      concrete evidence that our model outperforms JEM at the same
                      rate as our overall perceptual quality is better in majority
                      cases when viewing dynamic textures.},
      cin          = {613210},
      ddc          = {621.3},
      cid          = {$I:(DE-82)613210_20140620$},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2019-07494},
      url          = {https://publications.rwth-aachen.de/record/765565},
}