Open Access Paper
29 April 2009 Three-dimensional sensing, imaging, and recognition of objects having a small number of photons
Inkyu Moon, Bahram Javidi
Author Affiliations +
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Inkyu Moon and Bahram Javidi "Three-dimensional sensing, imaging, and recognition of objects having a small number of photons", Proc. SPIE 7339, Enabling Photonics Technologies for Defense, Security, and Aerospace Applications V, 733908 (29 April 2009); https://doi.org/10.1117/12.822118
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KEYWORDS
Photons

3D image processing

3D image reconstruction

3D modeling

Imaging systems

Integral imaging

Detection and tracking algorithms

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