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Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography |
Optics Letters, Vol. 38, Issue 5, pp. 619-621 (2013)
http://dx.doi.org/10.1364/OL.38.000619
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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.
© 2013 Optical Society of America
OCIS Codes
(100.2980) Image processing : Image enhancement
(110.4280) Imaging systems : Noise in imaging systems
(090.1995) Holography : Digital holography
ToC Category:
Holography
History
Original Manuscript: December 6, 2012
Revised Manuscript: January 23, 2013
Manuscript Accepted: January 23, 2013
Published: February 21, 2013
Citation
V. Bianco, M. Paturzo, P. Memmolo, A. Finizio, P. Ferraro, and B. Javidi, "Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography," Opt. Lett. 38, 619-621 (2013)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-38-5-619
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