The 2- 1 compressed sensing minimization problem can be solved efficiently by gradient projection. In imaging applications, the signal of interest corresponds to nonnegative pixel...
Zachary T. Harmany, Daniel Thompson, Rebecca Wille...
For compressive sensing, we endeavor to improve the recovery performance of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlyin...
Saikat Chatterjee, Dennis Sundman, Mikael Skoglund
We provide two compressive sensing (CS) recovery algorithms based on iterative hard-thresholding. The algorithms, collectively dubbed as algebraic pursuits (ALPS), exploit the res...
This paper links two a priori different topics, group testing and traitor tracing. Group testing, as an instantiation of a compressed sensing problem over binary data, is indeed e...
In this work we propose a method for estimating disparity maps from very few measurements. Based on the theory of Compressive Sensing, our algorithm accurately reconstructs dispar...