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SUMMARY:Structural adaptation - a statistical concept for image denoising 
 - Joerg Polzehl (Weierstraß-Institut für Angewandte Analysis und Stochas
 tik)
DTSTART:20171205T100000Z
DTEND:20171205T110000Z
UID:TALK96580@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Images are often characterized by their homogeneity structure\
 ,i.e.\, discontinuities and smoothness within homogeneous regions\, and in
 tensity distributions that depend on the image generating experiment. Stru
 ctural adaptation employs such qualitative assumptions on the homogeneitys
 tructure in a sequential multi-scale procedure that controls localbias and
  variance while implicitly recovering discontinuities. I&#39\;ll discuss t
 he basic principles of the procedure\, the model dependent but data-indepe
 ndent selection of it&#39\;s parameters by a propagation condition and its
  mainproperties. Generalizations include patch based procedures and method
 s for noise quantification.I&#39\;ll use examples from 2D and 3D imaging\,
  aswell as from diffusion MR (5D) and quantitative MR (multiple 3D)for ill
 ustration.&nbsp\;  <br><br><br><br>
LOCATION:Seminar Room 2\, Newton Institute
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