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» Recovery of Sparsely Corrupted Signals
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ICIP
2010
IEEE
13 years 4 months ago
Filterbank-based universal demosaicking
Recent advances in spatio-spectral sampling and panchromatic pixels have contributed to increased spatial resolution and enhanced noise performance. As such, it is necessary to co...
Jing Gu, Patrick J. Wolfe, Keigo Hirakawa
ICASSP
2011
IEEE
12 years 11 months ago
Compressed sensing based method for ECG compression
Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals that enables sampling rates significantly below the classical Nyquist rate. Based on...
Luisa F. Polania, Rafael E. Carrillo, Manuel Blanc...
CORR
2008
Springer
178views Education» more  CORR 2008»
13 years 7 months ago
Model-Based Compressive Sensing
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals that can be well approximated by just K N elements from a...
Richard G. Baraniuk, Volkan Cevher, Marco F. Duart...
ICASSP
2011
IEEE
12 years 11 months ago
Efficient image reconstruction under sparsity constraints with application to MRI and bioluminescence tomography
Most bioimaging modalities rely on indirect measurements of the quantity under investigation. The image is obtained as the result of an optimization problem involving a physical m...
Matthieu Guerquin-Kern, Jean-Charles Baritaux, Mic...
CISS
2010
IEEE
12 years 11 months ago
On the LASSO and Dantzig selector equivalence
—Recovery of sparse signals from noisy observations is a problem that arises in many information processing contexts. LASSO and the Dantzig selector (DS) are two well-known schem...
Muhammad Salman Asif, Justin K. Romberg