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Proceedings Paper

Three-dimensional sensing, imaging, and recognition of objects having a small number of photons
Author(s): Inkyu Moon; Bahram Javidi
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Paper Abstract

In this paper we overview the statistical method to three-dimensionally recognize very small number of photon-counted objects by using integral imaging (II). A conventional Poisson probability density function is assumed for modeling the distribution of very small number of photons count observation. For three-dimensional (3D) recognition of the small number of photon counted images, the photon limited elemental images set of a 3D object is obtained using the II technique. Then, the virtual geometrical ray propagation algorithm and the parametric maximum likelihood estimator are applied to the photon limited elemental image set in order to reconstruct the irradiance of the original 3D scene pixels. The sampling distributions for the statistical parameters of the reconstructed image are determined. Finally, hypothesis testing for the equality of the statistical parameters between reference and input data sets is performed for statistical classification of populations on the basis of sampling distribution information. Kolmogorov-Smirnov test is conducted and statistical p-value is measured. It is shown in experiments that very small number of photons counted image can be recognizable by the integral imaging and statistical sampling methods.

Paper Details

Date Published: 30 April 2009
PDF: 8 pages
Proc. SPIE 7339, Enabling Photonics Technologies for Defense, Security, and Aerospace Applications V, 733908 (30 April 2009); doi: 10.1117/12.822118
Show Author Affiliations
Inkyu Moon, Chosun Univ. (Korea, Republic of)
Bahram Javidi, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 7339:
Enabling Photonics Technologies for Defense, Security, and Aerospace Applications V
Michael J. Hayduk; Peter J. Delfyett; Andrew R. Pirich; Eric J. Donkor, Editor(s)

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