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Proceedings Paper

Three dimension holographic image sensing and recognition using Bayesian receivers
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Paper Abstract

We propose a statistical approach to detect a three-dimensional object using digital holography. The proposed algorithm uses the statistical properties of the speckle noise to find a probabilistic model for the likelihood function of the presence of the three-dimensional object in the scene. Phase shifting holography is used to generate the optical hologram of the 3D object and inverse Fresnel diffraction is used to reconstruct the 3D object. The complex wave generated from the inverse Fresnel integral is used as an input to the proposed algorithm. We show that the reconstructed 3D scene can be modeled as an object buried in a background complex Gaussian noise and the object is multiplied by a complex Gaussian noise. Analytical analysis and simulations show that the proposed technique is able detect the three dimensional coordinates of the distorted target object.

Paper Details

Date Published: 26 October 2005
PDF: 13 pages
Proc. SPIE 5986, Unmanned/Unattended Sensors and Sensor Networks II, 598607 (26 October 2005); doi: 10.1117/12.640850
Show Author Affiliations
Sherif Kishk, Mansoura Univ. (Egypt)
Bahram Javidi, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 5986:
Unmanned/Unattended Sensors and Sensor Networks II
Edward M. Carapezza, Editor(s)

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