Publication | Open Access
Noise-reduction algorithms for optimization-based imaging through multi-mode fiber
11
Citations
16
References
2014
Year
Image ReconstructionEngineeringAdvanced ImagingObr AlgorithmSurgeryNoise-reduction AlgorithmsEndoscopic ImagingNoise ReductionImage AnalysisNoise AmplificationSignal ReconstructionComputational ImagingRadiologyHealth SciencesReconstruction TechniqueMedical ImagingInverse ProblemsRandom Sampling PatternsFiber OpticSignal ProcessingBiomedical ImagingMedical Image Analysis
Three modifications are shown to improve resolution and reduce noise amplification in endoscopic imaging through multi-mode fiber using optimization-based reconstruction (OBR). First, random sampling patterns are replaced by sampling patterns designed to have more nearly equal singular values. Second, the OBR algorithm uses a point-spread function based on the estimated spatial frequency spectrum of the object. Third, the OBR algorithm gives less weight to modes having smaller singular values. In simulations for a step-index fiber supporting 522 spatial modes, the modifications yield a 20% reduction in image error (l(2) norm) in the noiseless case, and a further 33% reduction in image error at a 22-dB shot noise-limited SNR as compared to the original method using random sampling patterns and OBR.
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