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Proceedings Paper

Image reconstruction by phase retrieval with transverse translation diversity
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Paper Abstract

Measuring a series of far-field intensity patterns from an object, taken after a transverse translation of the object with respect to a known illumination pattern, has been shown to make the problem of image reconstruction by phase retrieval much more robust. However, previously reported reconstruction algorithms [Phys. Rev. Lett. 93, 023903 (2004)] rely on an accurate knowledge of the translations and illumination pattern for a successful reconstruction. We developed a nonlinear optimization algorithm that allows optimization over the translations and illumination pattern, dramatically improving the reconstructions if the system parameters are inaccurately known [Opt. Express 16, 7264 (2008)]. In this paper we compare reconstructions obtained with these algorithms under realistic experimental scenarios.

Paper Details

Date Published: 5 September 2008
PDF: 9 pages
Proc. SPIE 7076, Image Reconstruction from Incomplete Data V, 70760A (5 September 2008); doi: 10.1117/12.792622
Show Author Affiliations
Manuel Guizar-Sicairos, Institute of Optics, Univ. of Rochester (United States)
James R. Fienup, Institute of Optics, Univ. of Rochester (United States)

Published in SPIE Proceedings Vol. 7076:
Image Reconstruction from Incomplete Data V
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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