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CORR
2011
Springer
164views Education» more  CORR 2011»
12 years 11 months ago
Noise Folding in Compressed Sensing
The literature on compressed sensing has focused almost entirely on settings where the signal is noiseless and the measurements are contaminated by noise. In practice, however, th...
Ery Arias-Castro, Yonina C. Eldar
ICIP
2009
IEEE
13 years 5 months ago
Informative sensing of natural images
The theory of compressed sensing tells a dramatic story that sparse signals can be reconstructed near-perfectly from a small number of random measurements. However, recent work ha...
Hyun Sung Chang, Yair Weiss, William T. Freeman
PERCOM
2010
ACM
13 years 6 months ago
Resilient image sensor networks in lossy channels using compressed sensing
—Data loss in wireless communications greatly affects the reconstruction quality of a signal. In the case of images, data loss results in a reduction in quality of the received i...
Scott Pudlewski, Arvind Prasanna, Tommaso Melodia
ICIP
2009
IEEE
13 years 5 months ago
Randomness-in-Structured Ensembles for compressed sensing of images
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
Abdolreza A. Moghadam, Hayder Radha
CORR
2010
Springer
165views Education» more  CORR 2010»
13 years 8 months ago
Compressed Sensing for Sparse Underwater Channel Estimation: Some Practical Considerations
We examine the use of a structured thresholding algorithm for sparse underwater channel estimation using compressed sensing. This method shows some improvements over standard algo...
Sushil Subramanian