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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 7, Iss. 2 — Feb. 1, 2012

Sampling and processing for compressive holography [Invited]

Sehoon Lim, Daniel L. Marks, and David J. Brady  »View Author Affiliations


Applied Optics, Vol. 50, Issue 34, pp. H75-H86 (2011)
http://dx.doi.org/10.1364/AO.50.000H75


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Abstract

Compressive holography applies sparsity priors to data acquired by digital holography to infer a small number of object features or basis vectors from a slightly larger number of discrete measurements. Compressive holography may be applied to reconstruct three-dimensional (3D) images from two-dimensional (2D) measurements or to reconstruct 2D images from sparse apertures. This paper is a tutorial covering practical compressive holography procedures, including field propagation, reference filtering, and inverse problems in compressive holography. We present as examples 3D tomography from a 2D hologram, 2D image reconstruction from a sparse aperture, and diffuse object estimation from diverse speckle realizations.

© 2011 Optical Society of America

OCIS Codes
(100.6950) Image processing : Tomographic image processing
(110.6150) Imaging systems : Speckle imaging
(110.1758) Imaging systems : Computational imaging
(090.1995) Holography : Digital holography

ToC Category:
Invited ISP Papers

History
Original Manuscript: August 15, 2011
Revised Manuscript: September 3, 2011
Manuscript Accepted: September 7, 2011
Published: November 10, 2011

Virtual Issues
Vol. 7, Iss. 2 Virtual Journal for Biomedical Optics
Digital Holography and 3D Imaging 2011 (2011) Applied Optics

Citation
Sehoon Lim, Daniel L. Marks, and David J. Brady, "Sampling and processing for compressive holography [Invited]," Appl. Opt. 50, H75-H86 (2011)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ao-50-34-H75

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