000032976 001__ 32976
000032976 005__ 20180501105821.0
000032976 0247_ $$2doi$$a10.5075/epfl-thesis-2500
000032976 02471 $$2nebis$$a4259968
000032976 037__ $$aTHESIS_LIB
000032976 041__ $$aeng
000032976 088__ $$a2500
000032976 245__ $$aDirectional multiresolution image representations
000032976 269__ $$a2002
000032976 260__ $$aLausanne$$bEPFL$$c2002
000032976 300__ $$a208
000032976 336__ $$aTheses
000032976 502__ $$aRichard Baraniuk, Stéphane Mallat, Thierry Pun, Michaël Unser, Rüdiger Urbanke
000032976 520__ $$aEfficient representation of visual information lies at the foundation of many image processing tasks, including compression, filtering, and feature extraction. Efficiency of a representation refers to the ability to capture significant information of an object of interest in a small description. For practical applications, this representation has to be realized by structured transforms and fast algorithms. Recently, it has become evident that commonly used separable transforms (such as wavelets) are not necessarily best suited for images. Thus, there is a strong motivation to search for more powerful schemes that can capture the intrinsic geometrical structure of pictorial information. This thesis focuses on the development of new "true" two-dimensional representations for images. The emphasis is on the discrete framework that can lead to algorithmic implementations. The first method constructs multiresolution, local and directional image expansions by using non-separable filter banks. This discrete transform is developed in connection with the continuous-space curvelet construction in harmonic analysis. As a result, the proposed transform provides an efficient representation for two-dimensional piecewise smooth signals that resemble images. The link between the developed filter banks and the continuous-space constructions is set up in a newly defined directional multiresolution analysis. The second method constructs a new family of block directional and orthonormal transforms based on the ridgelet idea, and thus offers an efficient representation for images that are smooth away from straight edges. Finally, directional multiresolution image representations are employed together with statistical modeling, leading to powerful texture models and successful image retrieval systems.
000032976 586__ $$aEPFL, 2001
000032976 700__ $$0244021$$aDo, Minh N.$$g114014
000032976 720_2 $$0240184$$aVetterli, Martin$$edir.$$g107537
000032976 8564_ $$uhttp://vpaa.epfl.ch/page14975-fr.html$$zAward
000032976 8564_ $$s5583584$$uhttps://infoscience.epfl.ch/record/32976/files/EPFL_TH2500.pdf$$yTexte intégral / Full text$$zTexte intégral / Full text
000032976 909C0 $$0252056$$pLCAV$$xU10434
000032976 909CO $$ooai:infoscience.tind.io:32976$$pDOI2$$pDOI$$pIC$$pthesis
000032976 918__ $$aIC$$cISC
000032976 919__ $$aLCAV1
000032976 920__ $$a2001-12-11$$b2001
000032976 970__ $$a2500/THESES
000032976 973__ $$aEPFL$$sPUBLISHED
000032976 980__ $$aTHESIS