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...
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,...
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...
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...
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...