On the computation of the coherent point-spread function using a low-complexity representation

Saeed Bagheri, Daniela Pucci De Parias, George Barbastathis, Mark A. Neifeld

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Computation of the coherent point-spread function (PSF) involves evaluation of the diffraction integral, which is an integration of a highly oscillating function. This oscillation becomes severe as the value of defocus increases and thus makes PSF computation a costly task. We present a novel algorithm for computing the PSF, which works efficiently for any arbitrarily large value of defocus. It is theoretically proved that the complexity of our new algorithm does not depend on the value of defocus. We also develop an implementation scheme for the new algorithm. Using this implementation we experimentally demonstrate the low complexity of our method. We quantify the rapid convergence and numerical stability of this method over all ranges of defocus. Finally, we compare the computational cost of this method, in terms of time and memory, with other numerical methods such as direct numerical integration and the Fast Fourier Transform.

Original languageEnglish (US)
Title of host publicationOptical Information Systems IV
StatePublished - 2006
EventOptical Information Systems IV - San Diego, CA, United States
Duration: Aug 16 2006Aug 17 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherOptical Information Systems IV
Country/TerritoryUnited States
CitySan Diego, CA


  • Diffraction
  • Fourier transforms
  • Numerical approximation and analysis
  • Point-spread function

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'On the computation of the coherent point-spread function using a low-complexity representation'. Together they form a unique fingerprint.

Cite this