000176915 001__ 176915
000176915 005__ 20190316235352.0
000176915 037__ $$aCONF
000176915 245__ $$aRobust joint reconstruction of misaligned images using semi-parametric dictionaries
000176915 269__ $$a2012
000176915 260__ $$c2012
000176915 336__ $$aConference Papers
000176915 520__ $$aWe propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Theoretical results about the convergence of the algorithm are presented. The method is used here for joint reconstruction of misaligned images.
000176915 6531_ $$aParametric dictionary
000176915 6531_ $$aMulti-view imaging
000176915 6531_ $$aCompressed sensing
000176915 700__ $$0242927$$g179918$$aPuy, Gilles
000176915 700__ $$aVandergheynst, Pierre$$g120906$$0240428
000176915 7112_ $$dJune 30, 2012$$cEdinburgh, Scotland$$aICML Workshop on Sparsity, Dictionaries and Projections in Machine Learning and Signal Processing
000176915 8564_ $$uhttp://www.di.ens.fr/~obozinski/ICML2012workshop/$$zURL
000176915 8564_ $$uhttps://infoscience.epfl.ch/record/176915/files/ICML12-puyetal-submitted.pdf$$zn/a$$s686126$$yn/a
000176915 8564_ $$uhttps://infoscience.epfl.ch/record/176915/files/Presentation.pdf$$zn/a$$s4133050$$yn/a
000176915 909C0 $$xU10380$$0252392$$pLTS2
000176915 909CO $$qGLOBAL_SET$$pconf$$ooai:infoscience.tind.io:176915$$pSTI
000176915 917Z8 $$x179918
000176915 917Z8 $$x179918
000176915 917Z8 $$x179918
000176915 917Z8 $$x179918
000176915 937__ $$aEPFL-CONF-176915
000176915 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000176915 980__ $$aCONF