% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Scharr:33894,
      author       = {Scharr, H. and Spies, H.},
      title        = {{A}ccurate optical flow in noisy image sequences using flow
                      adapted anisotropic diffusion},
      journal      = {Signal processing: image communication},
      volume       = {20},
      issn         = {0923-5965},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {PreJuSER-33894},
      pages        = {537 - 553},
      year         = {2005},
      note         = {Record converted from VDB: 12.11.2012},
      abstract     = {In this paper, we combine 3D anisotropic diffusion and
                      motion estimation for image denoising and improvement of
                      motion estimation. We compare different continuous isotropic
                      nonlinear and anisotropic diffusion processes, which can be
                      found in literature, with a process especially designed for
                      image sequence denoising for motion estimation. All of these
                      processes initially improve motion estimation due to
                      reduction of noise and high frequencies. But while all the
                      well known processes rapidly destroy or hallucinate motion
                      information, the process brought forward here shows
                      considerably less information loss or violation even at
                      motion boundaries. We show the superior behavior of this
                      process. Further we compare the performance of a standard
                      finite difference diffusion scheme with several schemes
                      using derivative filters optimized for rotation invariance.
                      Using the discrete scheme with least smoothing artifacts we
                      demonstrate the denoising capabilities of this approach. We
                      exploit the motion estimation to derive an automatic
                      stopping criterion. (c) 2005 Elsevier B.V. All rights
                      reserved.},
      keywords     = {J (WoSType)},
      cin          = {ICG-III},
      ddc          = {004},
      cid          = {I:(DE-Juel1)VDB49},
      pnm          = {Chemie und Dynamik der Geo-Biosphäre},
      pid          = {G:(DE-Juel1)FUEK257},
      shelfmark    = {Engineering, Electrical $\&$ Electronic},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000230258500004},
      doi          = {10.1016/j.image.2005.03.005},
      url          = {https://juser.fz-juelich.de/record/33894},
}