• DocumentCode
    3731746
  • Title

    Superresolution without separation

  • Author

    Geoffrey Schiebinger;Elina Robeva;Benjamin Recht

  • Author_Institution
    Deparment of Statistics, University of California, Berkeley, USA
  • fYear
    2015
  • Firstpage
    45
  • Lastpage
    48
  • Abstract
    This paper provides a theoretical analysis of diffraction-limited superresolution, demonstrating that arbitrarily close point sources can be resolved in ideal situations. Precisely, we assume that the incoming signal is a linear combination of M shifted copies of a known waveform with unknown shifts and amplitudes, and one only observes a finite collection of evaluations of this signal. We characterize properties of the base waveform such that the exact translations and amplitudes can be recovered from 2M + 1 observations. This recovery is achieved by solving a a weighted version of basis pursuit over a continuous dictionary. Our methods combine classical polynomial interpolation techniques with contemporary tools from compressed sensing.
  • Keywords
    "Signal resolution","Spatial resolution","Imaging","Conferences","Interpolation","Optimization"
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015 IEEE 6th International Workshop on
  • Type

    conf

  • DOI
    10.1109/CAMSAP.2015.7383732
  • Filename
    7383732