Non-Bayesian noise reduction in digital holography by random resampling masks

Vittorio Bianco; Melania Paturzo; Pasquale Memmolo; Andrea Finizio; Bahram Javidi; Pietro Ferraro

doi:10.1117/12.2020865

13 May 2013 Non-Bayesian noise reduction in digital holography by random resampling masks

Vittorio Bianco, Melania Paturzo, Pasquale Memmolo, Andrea Finizio, Bahram Javidi, Pietro Ferraro

Proceedings Volume 8788, Optical Measurement Systems for Industrial Inspection VIII; 878831 (2013) https://doi.org/10.1117/12.2020865
Event: SPIE Optical Metrology 2013, 2013, Munich, Germany

Abstract

Images from coherent laser sources are severely degraded by a mixture of speckle and incoherent additive noise. In digital holography, Bayesian approaches reduce the incoherent noise, but prior information are needed about the noise statistics. On the other hand, non-Bayesian techniques presents the shortcomings of resolution loss or very complex acquisition systems, required to record multiple uncorrelated holograms to be averaged. Here we propose a fast non- Bayesian method which performs a numerical synthesis of a moving diffuser in order to reduce the noise. The method does not depend on prior knowledge of the noise statistics and the proposed technique is one-shot, as only one single hologram capture is required. Indeed, starting from a single acquisition multiple uncorrelated reconstructions are provided by random sparse resampling masks, which can be incoherently averaged. Experiments show a significant improvement, close to the theoretical bound. Noteworthy, this is achieved while preserving the resolution of the unprocessed image.

Citation Download Citation

Vittorio Bianco, Melania Paturzo, Pasquale Memmolo, Andrea Finizio, Bahram Javidi, and Pietro Ferraro "Non-Bayesian noise reduction in digital holography by random resampling masks", Proc. SPIE 8788, Optical Measurement Systems for Industrial Inspection VIII, 878831 (13 May 2013); https://doi.org/10.1117/12.2020865

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