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UID:124@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20140219T140000
DTEND;TZID=Europe/Paris:20140219T150000
DTSTAMP:20140204T130000Z
URL:https://www.i2m.univ-amu.fr/evenements/sparse-x-ray-tomography-using-b
 ayesian-inversion/
SUMMARY: (...): Sparse X-ray tomography using Bayesian inversion
DESCRIPTION:: "A sparsity promoting reconstruction method is studied in the
  context of X-ray tomography with limited X-ray projection data. The recon
 struction method is based on minimizing a sum of $ l^2$-norm and a $l^1$-n
 orm. Especially considered is the  $l^1$-norm of wavelet coefficients. Dep
 ending on the viewpoint this method can be considered either a) as the inv
 erse problem of  finding a Bayesian MAP estimate with Besov $B_{11}^1$ spa
 ce prior or b) as a deterministic regularization with Besov norm penalty.A
  tailored large-scale primal-dual interior-point method is used to solve t
 he associated constrained minimization problem. The selection of the regul
 arization parameter (or prior parameter\, depending on the viewpoint) is p
 erformed by a novel technique called the S-curve method. Numerical results
  are presented both from simulated and from real\, experimental data."http
 ://venda.uef.fi/inverse/FrontPage/People/Kati%20NiinimakiKati_Niinimäki
CATEGORIES:Groupe de travail,Analyse Spectrale et Problèmes Inverses
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DTSTART:20131027T020000
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