représentation and scalable coding using redundant dictionaries.

Rahmoune, Adel

Type de document Thèse
Langue eng
Titre représentation and scalable coding using redundant dictionaries. [ressource textuelle, sauf manuscrits]
Auteur(s) Rahmoune, Adel (Auteur)
Frossard, P. (Directeur de thèse)
Ecole Polytéchnique Fédéralede Lausanne (Editeur (scientifique))
Adresse bib. [s.l] : [s.n],2005
Collation 178 p. : ilI. ; 30 cm.
Notes de thèse Doctorat : Sciences : Lausanne. Ecole Polytéchnique Fédéralede Lausanne : Ecole Polytéchnique Fédéralede Lausanne : 2005
Indexation libre Cable
vidéo
Image
Résumé Computer or effcient representation for either images sequences is key operation to performing image and video processing tasks, such as compression , analysis, etc. The efficiency of an approximation is evaluted by the sparsity measure of the approximation, i.e. The sparsest the represantation is, more efficient ti is. for image processing tasks, it is often disired to decompose the image in to a linear combination of few visual primitives or features selected from a marge collection of waveforms, called the dictionary. These primitives are usually designed in such a way to achieve some good approximation performances by assuming a given class of function to model image. A common class of fuctions for image modeling is the set of function having discontinuities along smooth contours or boundaries, delinneating smooth geometrical redions.

Rahmoune, Adel
représentation and scalable coding using redundant dictionaries. [ressource textuelle, sauf manuscrits] / Adel Rahmoune; Dir. P. Frossard; Ed. Ecole Polytéchnique Fédéralede Lausanne.-[s.l] : [s.n],2005.-178 p. : ilI. ; 30 cm.
- Doctorat : Sciences : Lausanne. Ecole Polytéchnique Fédéralede Lausanne : 2005.

Computer or effcient representation for either images sequences is key operation to performing image and video processing tasks, such as compression , analysis, etc. The efficiency of an approximation is evaluted by the sparsity measure of the approximation, i.e. The sparsest the represantation is, more efficient ti is. for image processing tasks, it is often disired to decompose the image in to a linear combination of few visual primitives or features selected from a marge collection of waveforms, called the dictionary. These primitives are usually designed in such a way to achieve some good approximation performances by assuming a given class of function to model image. A common class of fuctions for image modeling is the set of function having discontinuities along smooth contours or boundaries, delinneating smooth geometrical redions.

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210  $a[s.l]$c[s.n]$d2005
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330  $aComputer or effcient representation for either images sequences is key operation to performing image and video processing tasks, such as compression , analysis, etc. The efficiency of an approximation is evaluted by the sparsity measure of the approximation, i.e. The sparsest the represantation is, more efficient ti is. for image processing tasks, it is often disired to decompose  the image in to  a linear combination  of few visual primitives or features selected from a marge collection of waveforms, called the dictionary. These primitives are usually designed in such a way to achieve some good approximation performances by assuming a given class of function to model image. A common class of fuctions for image modeling is the set of function having discontinuities along smooth contours or boundaries, delinneating smooth geometrical redions.
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712  $aEcole Polytéchnique Fédéralede Lausanne$4340$4727
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Type de document	Thèse
Langue	eng
Titre	représentation and scalable coding using redundant dictionaries. [ressource textuelle, sauf manuscrits]
Auteur(s)	Rahmoune, Adel (Auteur) Frossard, P. (Directeur de thèse) Ecole Polytéchnique Fédéralede Lausanne (Editeur (scientifique))
Adresse bib.	[s.l] : [s.n],2005
Collation	178 p. : ilI. ; 30 cm.
Notes de thèse	Doctorat : Sciences : Lausanne. Ecole Polytéchnique Fédéralede Lausanne : Ecole Polytéchnique Fédéralede Lausanne : 2005
Indexation libre	Cable vidéo Image
Résumé	Computer or effcient representation for either images sequences is key operation to performing image and video processing tasks, such as compression , analysis, etc. The efficiency of an approximation is evaluted by the sparsity measure of the approximation, i.e. The sparsest the represantation is, more efficient ti is. for image processing tasks, it is often disired to decompose the image in to a linear combination of few visual primitives or features selected from a marge collection of waveforms, called the dictionary. These primitives are usually designed in such a way to achieve some good approximation performances by assuming a given class of function to model image. A common class of fuctions for image modeling is the set of function having discontinuities along smooth contours or boundaries, delinneating smooth geometrical redions.