University of Cambridge > Talks.cam > Signal Processing and Communications Lab Seminars > Exploiting Asymptotic Structure for Resolution Enhancement in Physical Imaging Systems

Exploiting Asymptotic Structure for Resolution Enhancement in Physical Imaging Systems

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If you have a question about this talk, please contact Dr Ramji Venkataramanan.

Signal recovery from undersampled data is of great importance to physical imaging systems. We identify and model two asymptotic phenomena that manifest in imaging systems. The first, asymptotic sparsity, is associated with models of signals, and the second, asymptotic incoherence, is associated with models of measurement and representation. We show that compressed sensing behaves differently at different resolution, and develop sampling principles that are aligned with these asymptotic phenomena and that enable the the full power of compressed sensing methods to be brought to bear upon four different physical imaging systems: Magnetic Resonance Imaging, Fluorescence Microscopy, Nuclear Magnetic Resonance, and Helium Atom Scattering. In each of these systems the proposed multilevel sampling method enables enhanced resolution at length scales of interest.

This talk is part of the Signal Processing and Communications Lab Seminars series.

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