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Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Editor: Stephen A. Burns
  • Vol. 24, Iss. 6 — Jun. 1, 2007
  • pp: 1580–1600

AIDA: an adaptive image deconvolution algorithm with application to multi-frame and three-dimensional data

Erik F. Y. Hom, Franck Marchis, Timothy K. Lee, Sebastian Haase, David A. Agard, and John W. Sedat  »View Author Affiliations

JOSA A, Vol. 24, Issue 6, pp. 1580-1600 (2007)

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We describe an adaptive image deconvolution algorithm (AIDA) for myopic deconvolution of multi-frame and three-dimensional data acquired through astronomical and microscopic imaging. AIDA is a reimplementation and extension of the MISTRAL method developed by Mugnier and co-workers and shown to yield object reconstructions with excellent edge preservation and photometric precision [ J. Opt. Soc. Am. A 21, 1841 (2004) ]. Written in Numerical Python with calls to a robust constrained conjugate gradient method, AIDA has significantly improved run times over the original MISTRAL implementation. Included in AIDA is a scheme to automatically balance maximum-likelihood estimation and object regularization, which significantly decreases the amount of time and effort needed to generate satisfactory reconstructions. We validated AIDA using synthetic data spanning a broad range of signal-to-noise ratios and image types and demonstrated the algorithm to be effective for experimental data from adaptive optics–equipped telescope systems and wide-field microscopy.

© 2007 Optical Society of America

OCIS Codes
(010.1080) Atmospheric and oceanic optics : Active or adaptive optics
(100.1830) Image processing : Deconvolution
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(180.0180) Microscopy : Microscopy
(180.6900) Microscopy : Three-dimensional microscopy

ToC Category:
Image Processing

Original Manuscript: June 6, 2006
Revised Manuscript: October 19, 2006
Manuscript Accepted: December 7, 2006
Published: May 9, 2007

Virtual Issues
Vol. 2, Iss. 7 Virtual Journal for Biomedical Optics

Erik F. Y. Hom, Franck Marchis, Timothy K. Lee, Sebastian Haase, David A. Agard, and John W. Sedat, "AIDA: an adaptive image deconvolution algorithm with application to multi-frame and three-dimensional data," J. Opt. Soc. Am. A 24, 1580-1600 (2007)

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