Compressive-sensing cameras are an important new class of sensors that have different design constraints than standard cameras. Surprisingly, little work has explored the relation...
In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measure...
Spectral imaging is of interest in many applications, including wide-area airborne surveillance, remote sensing, and tissue spectroscopy. Coded aperture spectral snapshot imaging ...
Previous compressive sensing papers have considered the example of recovering an image with sparse gradient from a surprisingly small number of samples of its Fourier transform. T...
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty