On reconstruction from non-uniform spectral data

Adityavikram Viswanathan, Anne Gelb, Douglas Cochran, Rosemary Renaut

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


This paper addresses the reconstruction of compactly supported functions from non-uniform samples of their Fourier transform. We briefly investigate the consequences of acquiring non-uniform spectral data. We summarize two often applied reconstruction methods, convolutional gridding and uniform re-sampling, and investigate the reconstruction accuracy as it relates to sampling density. Finally, we provide preliminary results from employing spectral re-projection methods in the reconstruction.

Original languageEnglish (US)
Pages (from-to)487-513
Number of pages27
JournalJournal of Scientific Computing
Issue number1-3
StatePublished - Oct 2010


  • Convolutional gridding
  • Non-harmonic Fourier reconstruction
  • Sampling density
  • Spectral re-projection

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Numerical Analysis
  • Engineering(all)
  • Computational Theory and Mathematics
  • Computational Mathematics
  • Applied Mathematics


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