Fast algorithms for phase diversity-based blind deconvolution

Curtis R. Vogel, Tony F. Chan, Robert J. Plemmons

Research output: Contribution to journalConference articlepeer-review

70 Scopus citations


Phase diversity is a technique for obtaining estimates of both the object and the phase, by exploiting the simultaneous collection of two short-exposure optical images, one of which has been formed by further blurring regularized variant of the Gauss-Newton optimization method for phase diversity-based estimated when a Gaussian likelihood fit-to-data criterion is applied. Simulation studies are provided to demonstrate that the method is remarkably robust and numerically efficient.

Original languageEnglish (US)
Pages (from-to)994-1005
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 1998
Externally publishedYes
EventAdaptive Optical System Technologies - Kona, HI, United States
Duration: Mar 23 1998Mar 23 1998


  • Blind deconvolution
  • Phase diversity
  • Phase retrieval
  • Quasi-Newton methods

ASJC Scopus subject areas

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


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