Journal of the Optical Society of America A · 1995 · 516 citations · 10 references
EngineeringBiomedical EngineeringComputer ScienceBiomedical ImagingDiagnostic ImagingDigital ImagingDigital Image ProcessingDigital Signal ProcessingImage ProcessingImage ReconstructionImage RestorationBlind DeconvolutionBlind Image RestorationDeconvolutionDeconvolution TechniquesPoint Spread FunctionPoint Spread Function AnalysisPoint Spread Function EstimationPoint Spread Function Modeling
The paper presents a blind deconvolution algorithm based on the Richardson–Lucy method. The algorithm extends Richardson–Lucy blind deconvolution by incorporating parameterized point‑spread functions and is benchmarked against a Wiener‑filter approach. In noisy conditions the method outperforms other blind deconvolution techniques, achieving PSF estimation within 1 % error and reconstructing objects nearly as well as when the PSF is known.
A blind deconvolution algorithm based on the Richardson–Lucy deconvolution algorithm is presented. Its performance in the presence of noise is found to be superior to that of other blind deconvolution algorithms. Results are presented and compared with results obtained from implementation of a Weiner filter blind deconvolution algorithm. The algorithm is developed further to incorporate functional forms of the point-spread function with unknown parameters. In the presence of noise the point-spread function can be evaluated with 1.0% error, and the object can be reconstructed with a quality near that of the deconvolution process with a known point-spread function.
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<i>Numerical Recipes, The Art of Scientific Computing</i>
William H. Press, Brian P. Flannery, Saul A. Teukolsky et al. · American Journal of Physics · 1987 · 10.1K citations
Phase retrieval algorithms: a comparison
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