Journal of the Optical Society of Korea

Optical Society of Korea (한국광학회)
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Photon Counting Linear Discriminant Analysis with Integral Imaging for Occluded Target Recognition

  • Yeom, Seok-Won (School of Computer and Communication Engineering, Daegu University) ;
  • Javidi, Bahram (Department of Electrical and Computer Engineering, University of Connecticut)
  • Received : 2008.04.24
  • Accepted : 2008.06.03
  • Published : 2008.06.25
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Abstract

This paper discusses a photon-counting linear discriminant analysis (LDA) with computational integral imaging (II). The computational II method reconstructs three-dimensional (3D) objects on the reconstruction planes located at arbitrary depth-levels. A maximum likelihood estimation (MLE) can be used to estimate the Poisson parameters of photon counts in the reconstruction space. The photon-counting LDA combined with the computational II method is developed in order to classify partially occluded objects with photon-limited images. Unknown targets are classified with the estimated Poisson parameters while reconstructed irradiance images are trained. It is shown that a low number of photons are sufficient to classify occluded objects with the proposed method.

Keywords

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  1. Resolution-enhanced Reconstruction of 3D Object Using Depth-reversed Elemental Images for Partially Occluded Object Recognitionz vol.13, pp.1, 2009, https://doi.org/10.3807/JOSK.2009.13.1.139
  2. Three-Dimensional Object Reconstruction and Recognition Using Computational Integral Imaging and Statistical Pattern Analysis vol.48, pp.9, 2009, https://doi.org/10.1143/JJAP.48.09LB05