The fast sinc transform and image reconstruction from nonuniform samples in k-space

Leslie Greengard, June Yub Lee, Souheil Inati

Research output: Contribution to journalArticlepeer-review


A number of problems in image reconstruction and image processing can be addressed, in principle, using the sinc kernel. Since the sinc kernel decays slowly, however, it is generally avoided in favor of some more local but less precise choice. In this paper, we describe the fast sinc transform, an algorithm which computes the convolution of arbitrarily spaced data with the sinc kernel in O(N logN) operations, where N denotes the number of data points. We briefly discuss its application to the construction of optimal density compensation weights for Fourier reconstruction and to the iterative approximation of the pseudoinverse of the signal equation in MRI.

Original languageEnglish (US)
Pages (from-to)121-131
Number of pages11
JournalCommunications in Applied Mathematics and Computational Science
Issue number1
StatePublished - 2006


  • Density compensation weights
  • Fast transform
  • Fourier analysis
  • Image reconstruction
  • Iterative methods
  • Magnetic resonance imaging (MRI)
  • Nonuniform fast Fourier transform
  • Sinc interpolation

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Applied Mathematics


Dive into the research topics of 'The fast sinc transform and image reconstruction from nonuniform samples in k-space'. Together they form a unique fingerprint.

Cite this