This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...
Abstract--In this paper we address the task of accurately reconstructing a distributed signal through the collection of a small number of samples at a data gathering point using Co...
Riccardo Masiero, Giorgio Quer, Michele Rossi, Mic...
1 minimization can be used to recover sufficiently sparse unknown signals from compressed linear measurements. In fact, exact thresholds on the sparsity, as a function of the ratio...
We present a novel iterative nonlinear filtering framework, termed multilateral filtering, based on the idea of generic local similarity. A set of local features is computed for e...
—We show that, via temporal modulation, one can observe and capture a high-speed periodic video well beyond the abilities of a low-frame-rate camera. By strobing the exposure wit...