Pitkäaho, Tomi and Naughton, Thomas J. (2014) Speckle Noise Reduction in Michelson Digital Holography Using Known or Unknown Reference Linear Phases and Image Processing. In: Fringe 2013. Springer, pp. 649-652. ISBN 9783642363580

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Abstract

Speckle is caused by the illumination of an optically rough surface by coherent light [1] which can cause problems in digital holography. Speckle in a reconstruction reduces visibility of details and may impede important measurements of an object. Speckle can be reduced by capturing multiple holograms and summing the reconstructed intensities [2-4]. Digital signal processing methods, which are applied after capture, have also been proposed [5–8]. With respect to three-dimensional (3D) objects, we solve this problem by outof- plane rotating the reference mirror in discrete steps, capturing a hologram each time, and introducing image processing to rectify the resulting shifted diffraction fields. Each rotation amount need not be known and so can be generated by a very fast unstable device. This reference beam rotation is different from [4], where the object beam is rotated at different angles. Changing the angle of incidence of the reference beam changes the phase implicitly captured in the hologram, and results in a different speckle pattern in each reconstructed object. The positions of the object and the camera remain the same so there is no change in perspective between holograms, allowing integration of an arbitrary number of them using the full rotation range allowed by the space-bandwidth product of the camera. The intensities of numerical reconstructions are averaged after image processing registration steps, which produces speckle-reduced reconstructions that closely match theoretical predictions for statistically independent speckle fields.

Item Type:	Book Section
Additional Information:	This is the postprint version of the published chapter, which is available at DOI: 10.1007/978-3-642-36359-7_120
Keywords:	Speckle Noise Reduction; Michelson Digital Holography; Reference Linear Phases; Image Processing;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	6533
Identification Number:	https://doi.org/10.1007/978-3-642-36359-7_120
Depositing User:	Thomas Naughton
Date Deposited:	04 Nov 2015 16:59
Publisher:	Springer
Refereed:	Yes
URI:	http://link.springer.com
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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