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ICASSP
2009
IEEE
13 years 11 months ago
A low complexity Orthogonal Matching Pursuit for sparse signal approximation with shift-invariant dictionaries
We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift-invariant signal dictionari...
Boris Mailhé, Rémi Gribonval, Fr&eac...
TSP
2008
124views more  TSP 2008»
13 years 4 months ago
Dictionary Preconditioning for Greedy Algorithms
This article introduces the concept of sensing dictionaries. It presents an alteration of greedy algorithms like thresholding or (Orthogonal) Matching Pursuit which improves their...
Karin Schnass, Pierre Vandergheynst
CORR
2007
Springer
183views Education» more  CORR 2007»
13 years 5 months ago
Compressed Sensing and Redundant Dictionaries
This article extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, whic...
Holger Rauhut, Karin Schnass, Pierre Vandergheynst
ICIP
2005
IEEE
14 years 6 months ago
The M-term pursuit for image representation and progressive compression
This paper introduces a sparse signal representation algorithm in redundant dictionaries, called the M-Term Pursuit (MTP), with an application to image representation and scalable ...
Adel Rahmoune, Pierre Vandergheynst, Pascal Frossa...
ICASSP
2011
IEEE
12 years 8 months ago
SSIM-inspired image denoising using sparse representations
Perceptual image quality assessment (IQA) and sparse signal representation have recently emerged as high-impact research topics in the field of image processing. Here we make one...
Abdul Rehman, Zhou Wang, Dominique Brunet, Edward ...