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ICASSP
2011
IEEE
12 years 8 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad
ICIP
2010
IEEE
13 years 2 months ago
Automatic target recognition based on simultaneous sparse representation
In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extr...
Vishal M. Patel, Nasser M. Nasrabadi, Rama Chellap...
ICASSP
2008
IEEE
13 years 11 months ago
Insights into the stable recovery of sparse solutions in overcomplete representations using network information theory
In this paper, we examine the problem of overcomplete representations and provide new insights into the problem of stable recovery of sparse solutions in noisy environments. We es...
Yuzhe Jin, Bhaskar D. Rao
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 5 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
JVCIR
2010
162views more  JVCIR 2010»
13 years 3 months ago
Tetrolet transform: A new adaptive Haar wavelet algorithm for sparse image representation
In order to get an efficient image representation we introduce a new adaptive Haar wavelet transform, called Tetrolet Transform. Tetrolets are Haar-type wavelets whose supports ar...
Jens Krommweh