Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sens...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Abstract—In this paper, we introduce the cellphonebased indirect sensing problem. While participatory sensing aims at monitoring of a phenomenon by deploying a dense set of senso...
Murat Demirbas, Carole Rudra, Atri Rudra, Murat Al...
This paper addresses the problem of generating a superresolution (SR) image from a single low-resolution input image. We approach this problem from the perspective of compressed s...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma