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CATEGORIES:Cambridge Analysts' Knowledge Exchange
SUMMARY:Infimal convolution of Total Generalized Variation
  functionals for spatio-temporal regularization of
  image sequences - Martin Holler (University of Gr
 az)
DTSTART;TZID=Europe/London:20150311T160000
DTEND;TZID=Europe/London:20150311T170000
UID:TALK57874AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/57874
DESCRIPTION:Variational methods for image processing heavily r
 ely on appropriate regularization functionals. Whi
 le this topic is well investigated in the still im
 age context\, the question of suitable regularizat
 ion for image sequences is still quite open\, but 
 not less important. In this talk\, we present a ne
 w approach for spatio-temporal regularization of i
 mage sequences. When considering for instance the 
 spatio-temporal Total Variation (TV) or Total Gene
 ralized Variation (TGV) functional\, the scale of 
 space with respect to time is not given a-priori a
 nd in fact defines a trade-off between spatial and
  temporal regularization. This can be exploited to
  further improve reconstruction quality by optimal
 ly balancing between two different scales via the 
 infimal convolution of such functionals (ICTGV). W
 e present the analysis of the resulting regulariza
 tion term and its application for dynamic MRI reco
 nstruction and the artifact-free decompression of 
 MPEG compressed videos.
LOCATION:MR14\, Centre for Mathematical Sciences
CONTACT:Davide Piazzoli
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