An application of compressive sensing (CS) theory in imagebased robust face recognition is considered. Most contemporary face recognition systems suffer from limited abilities to ...
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
We consider the problem of recursively and causally reconstructing time sequences of sparse signals (with unknown and time-varying sparsity patterns) from a limited number of noisy...
: We demonstrate that sub-wavelength optical images borne on partially-spatially-incoherent light can be recovered, from their far-field or from the blurred image, given the prior ...
Yoav Shechtman, Yonina C. Eldar, Alexander Szameit...
Both compressed sensing (CS) and parallel imaging effectively reconstruct magnetic resonance images from undersampled data. Combining both methods enables imaging with greater und...
Daniel S. Weller, Jonathan R. Polimeni, Leo Grady,...