000086966 001__ 86966
000086966 005__ 20190416055648.0
000086966 02470 $$2ISI$$a000188360200023
000086966 037__ $$aCONF
000086966 245__ $$aVery low bit rate image coding using redundant dictionaries
000086966 269__ $$a2003
000086966 260__ $$bSPIE$$c2003
000086966 336__ $$aConference Papers
000086966 490__ $$aLecture Notes in Computer Science
000086966 520__ $$aVery low bit rate image coding is an important problem regarding applications such as storage on low memory devices or streaming data on the internet. The state of the art in image compression is to use 2-D wavelets. The advantages of wavelet bases lie in their multiscale nature and in their ability to sparsely represent functions that are piecewise smooth. Their main problem on the other hand, is that in 2-D wavelets are not able to deal with the natural geometry of images, i.e they cannot sparsely represent objects that are smooth away from regular submanifolds. In this paper we propose an approach based on building a sparse representation of images in a redundant geometrically inspired library of functions, followed by suitable coding techniques. Best N-term non- linear approximations in general dictionaries is, in most cases, a NP-hard problem and sub-optimal approaches have to be followed. In this work we use a greedy strategy, also known as Matching Pursuit to compute the expansion. Finally the last step in our algorithm is an enhancement layer that encodes the residual image: in our simulation we have used a genuine embedded wavelet codec.
000086966 6531_ $$aapproximation
000086966 6531_ $$aCoding
000086966 6531_ $$adictionaries
000086966 6531_ $$aGreedy
000086966 6531_ $$aImage
000086966 6531_ $$aLTS2
000086966 6531_ $$aMatching
000086966 6531_ $$aPursuit
000086966 6531_ $$aRedundant
000086966 6531_ $$arepresentation
000086966 6531_ $$aSparse
000086966 6531_ $$aWavelet
000086966 700__ $$0240763$$g137687$$aPeotta, L.
000086966 700__ $$0241529$$g141038$$aGranai, L.
000086966 700__ $$aVandergheynst, P.$$g120906$$0240428
000086966 773__ $$j5207$$tProceedings of the SPIE, Wavelets: Applications in Signal and Image Processing X$$q228-239
000086966 8564_ $$uhttps://infoscience.epfl.ch/record/86966/files/Peotta2003_45.pdf$$zn/a$$s1255773
000086966 909C0 $$xU10380$$0252392$$pLTS2
000086966 909CO $$ooai:infoscience.tind.io:86966$$qGLOBAL_SET$$pconf$$pSTI
000086966 937__ $$aEPFL-CONF-86966
000086966 970__ $$aPeotta2003_45/LTS
000086966 973__ $$sPUBLISHED$$aEPFL
000086966 980__ $$aCONF