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SUMMARY:Optimising the image optimisers via nonlinear PDE constrained opti
 misation - Oxbridge PDE Days - Dr Carola-Bibiane Schönlieb\, DAMTP
DTSTART:20140321T150000Z
DTEND:20140321T160000Z
UID:TALK51586@talks.cam.ac.uk
CONTACT:36127
DESCRIPTION:When assigned with the task of reconstructing an image from gi
 ven data the first challenge one faces is the derivation of a truthful ima
 ge and data model. Such a model can be determined by the a-priori knowledg
 e about the image\, the data and their relation to each other. The source 
 of this knowledge is either our understanding of the type of images we wan
 t to reconstruct and of the physics behind the acquisition of the data or 
 we can thrive to learn parametric models from the data itself. The common 
 question arises: how can we optimise our model choice?\nAfter a critical d
 iscussion of different image and data models we will turn towards deriving
  an optimal image reconstruction model using PDE constrained optimisation.
  In this framework we will consider optimal parameter derivation for total
  variation denoising with multiple noise distributions and optimising tota
 l generalised variation regularisation for its application in photography.
 \nJoint work with Luca Calatroni\, Jan Lellmann\, Juan Carlos De Los Reyes
  and Tuomo Valkonen.\n\nhttp://www.maths.cam.ac.uk/postgrad/cca/oxbridgepd
 e2014.html
LOCATION:MR2
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