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IEEE Journal of Selected Topics in Signal Processing 5, 5 (2011) 896-911

A Review of Adaptive Image Representations

Gabriel Peyré 1

(2011)

Improving the modeling of natural im- ages is important to go beyond the state of the art for many image processing tasks such as compression, denoising, inverse problems and texture synthesis. Natural images are composed of intricate patterns such as regular areas, edges, junctions, oriented os- cillations and textures. Processing efficiently such a wide range of regularities requires methods that are adaptive to the geometry of the image. This adap- tivity can be achieved using sparse representations in a redundant dictionary. The geometric adaptivity is important to search for efficient representations in a structured dictionary. Another way to capture this geometry is through non-local interactions be- tween patches in the image. The resulting non-local energies can be used to perform an adaptive im- age restoration. This paper reviews these emerging technics and shows the interplay between sparse and non-local regularizations.

1 :	CEntre de REcherches en MAthématiques de la DEcision (CEREMADE)
	CNRS : UMR7534 – Université Paris IX - Paris Dauphine

Domaine

:

Informatique/Traitement du signal et de l'image Sciences de l'ingénieur/Traitement du signal et de l'image

Mots Clés : Adaptivity – sparse regularization – non-local regularization – best basis – triangulations – dictionary learning – approximation – denoising – inverse problems – texture synthesis

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Contributeur : Gabriel Peyré <>

Soumis le : Lundi 20 Septembre 2010, 15:45:45

Dernière modification le : Mercredi 23 Mai 2012, 21:55:32