Session C1 - Computational Harmonic Analysis and Compressive Sensing - Semi-plenary talk
July 17, 14:30 ~ 15:20 - Room B3
Enhancing Resolution in Undersampled Physical Imaging
Duke University, USA - firstname.lastname@example.org
Compressed sensing MRI was first proposed by Lustig and Donoho, and it is now starting to appear in commercial systems. Candes, Tao and Romberg used Incoherence between measurements and representations of signals to develop performance guarantees for compressed sensing. We demonstrate here that fidelity and resolution in physical imaging systems can be improved by taking advantage of shared asymptotic characteristics of signals and measurement devices. We present new experimental results, explaining why and how improvements are possible.
Joint work with Bogdan Roman, University of Cambridge, UK, Ben Adcock, Simon Fraser University, Canada, Daniel Nietlispach, University of Cambridge, UK, Mark Bostock, University of Cambridge, UK, Irene Calvo-Almazan, University of Cambridge, UK, Martin Graves, University of Cambridge, UK and Anders Hansen, University of Cambridge, UK.