Abstract

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
Volume45
Issue number1-3
DOIs
StatePublished - Oct 1 2010

Keywords

  • 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

Fingerprint Dive into the research topics of 'On reconstruction from non-uniform spectral data'. Together they form a unique fingerprint.

  • Cite this