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DCC
2006
IEEE
14 years 7 months ago
Distributed Sampling and Compression of Scenes with Finite Rate of Innovation in Camera Sensor Networks
We study the problem of distributed sampling and compression in sensor networks when the sensors are digital cameras that acquire a 3-D visual scene of interest from different vie...
Nicolas Gehrig, Pier Luigi Dragotti
ICASSP
2011
IEEE
12 years 11 months ago
Compressive power spectral density estimation
In this paper, we consider power spectral density estimation of bandlimited, wide-sense stationary signals from sub-Nyquist sampled data. This problem has recently received attent...
Michael A. Lexa, Mike E. Davies, John S. Thompson,...
CORR
2011
Springer
176views Education» more  CORR 2011»
13 years 2 months ago
Matched Filtering from Limited Frequency Samples
In this paper, we study a simple correlation-based strategy for estimating the unknown delay and amplitude of a signal based on a small number of noisy, randomly chosen frequency-...
Armin Eftekhari, Justin K. Romberg, Michael B. Wak...
CVPR
2007
IEEE
14 years 9 months ago
Robust Estimation of Texture Flow via Dense Feature Sampling
Texture flow estimation is a valuable step in a variety of vision related tasks, including texture analysis, image segmentation, shape-from-texture and texture remapping. This pap...
Yu-Wing Tai, Michael S. Brown, Chi-Keung Tang
SCALESPACE
2007
Springer
14 years 1 months ago
Best Basis Compressed Sensing
This paper proposes an extension of compressed sensing that allows to express the sparsity prior in a dictionary of bases. This enables the use of the random sampling strategy of c...
Gabriel Peyré