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» Reconstructing sparse signals from their zero crossings
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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
ECCV
2008
Springer
14 years 9 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
ICASSP
2011
IEEE
12 years 11 months ago
Linear time decoding of real-field codes over high error rate channels
This paper proposes a novel algorithm for decoding real-field codes over erroneous channels, where the encoded message is corrupted by sparse errors, i.e., impulsive noise. The m...
Zaixing He, Takahiro Ogawa, Miki Haseyama
ICA
2007
Springer
13 years 9 months ago
Gradient Convolution Kernel Compensation Applied to Surface Electromyograms
Abstract. This paper introduces gradient based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyograp...
Ales Holobar, Damjan Zazula
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