168 search results - page 27 / 34 » Bayesian Compressive Sensing for clustered sparse signals |
ICCV
2009
IEEE
13 years 5 months ago
2009
IEEE
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
CORR
2007
Springer
13 years 7 months ago
2007
Springer
We consider signals and operators in finite dimension which have sparse time-frequency representations. As main result we show that an S-sparse Gabor representation in Cn with re...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
ECCV
2010
Springer
14 years 21 days ago
2010
Springer
Abstract. Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals and images that enables sampling rates significantly below the classical Ny...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
This paper proposes a distributed representation algorithm for multi-view images that are jointly reconstructed at the decoder. Compressed versions of each image are first obtain...