Scientific Results

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

Year: 2013

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

Autors Affiliation: 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

Abstract: 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

Journal/Review: OPTICS LETTERS

Volume: 38 (5)      Pages from: 619  to: 621

KeyWords: Image processing : Image enhancement; Imaging systems : Noise in imaging syste; Holography : Digital holography
DOI: 10.1364/OL.38.000619

Citations: 69
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2022-01-16
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