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Compressive holography of diffuse objects
Author(s) -
Kerkil Choi,
Ryoichi Horisaki,
Joonku Hahn,
Sehoon Lim,
Daniel L. Marks,
Timothy J. Schulz,
David J. Brady
Publication year - 2010
Publication title -
applied optics
Language(s) - English
Resource type - Journals
ISSN - 0003-6935
DOI - 10.1364/ao.49.0000h1
Subject(s) - speckle pattern , holography , optics , compressed sensing , speckle imaging , inference , speckle noise , digital holography , covariance , scattering , computer science , physics , artificial intelligence , mathematics , statistics
We propose an estimation-theoretic approach to the inference of an incoherent 3D scattering density from 2D scattered speckle field measurements. The object density is derived from the covariance of the speckle field. The inference is performed by a constrained optimization technique inspired by compressive sensing theory. Experimental results demonstrate and verify the performance of our estimates.

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