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Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography

  Articoli su Riviste JCR/ISI  (anno 2013)

Autori:  Bianco V., Paturzo M., Memmolo P., Finizio A., Ferraro P., Javidi B

Affiliazione Autori:  CNR - National Institute of Optics, Via Campi Flegrei, 34, Pozzuoli (NA) I-80078, Italy; Center for Advanced Biomaterials for Health Care, Istituto Italiano di Tecnologia, L. Barsanti e Matteucci (NA), 53, I-80125, Italy; ECE Department, University of Connecticut, U-157, Storrs, Connecticut 06269, USA

Riassunto:  Holographic imaging may become severely degraded by a mixture of speckle and incoherent additive noise. Bayesian approaches reduce the incoherent noise, but prior information is needed on the noise statistics. With no prior knowledge, one-shot reduction of noise is a highly desirable goal, as the recording process is simplified and made faster. Indeed, neither multiple acquisitions nor a complex setup are needed. So far, this result has been achieved at the cost of a deterministic resolution loss. Here we propose a fast non-Bayesian denoising method that avoids this trade-off by means of a numerical synthesis of a moving diffuser. In this way, only one single hologram is required as multiple uncorrelated reconstructions are provided by random complementary resampling masks. Experiments show a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement. At the same time, we preserve the resolution of the unprocessed image. (C) 2013 Optical Society of America

Rivista/Giornale:  OPTICS LETTERS
Volume n.:  38 (5)      Pagine da: 619  a: 621
DOI: 10.1364/OL.38.000619

*Impact Factor della Rivista: (2013) 3.179   *Citazioni: 52
data tratti da "WEB OF SCIENCE" (marchio registrato di Thomson Reuters) ed aggiornati a:  14/07/2019

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