Blind deconvolution using least squares minimisation

Ngai Fong Law, R. G. Lane

Research output: Journal article publicationJournal articleAcademic researchpeer-review

31 Citations (Scopus)

Abstract

Blind deconvolution of blurred images has been demonstrated by a number of authors. The quantitative performance of these algorithms is less well known, in particular the sensitivity of the reconstruction to the inherent ambiguities in blind deconvolution and the effect of noise. We consider in detail two algorithms based on a least squares optimisation approach. The performance of these two algorithms is also discussed with regard to superresolving an image corrupted by an unknown blurring function, using an example recently published in the literature [J. Opt. Soc. Am. A 11 (1994) 2401].
Original languageEnglish
Pages (from-to)341-352
Number of pages12
JournalOptics Communications
Volume128
Issue number4-6
DOIs
Publication statusPublished - 15 Jul 1996
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Physical and Theoretical Chemistry
  • Electrical and Electronic Engineering

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