학술논문

Photon Counting Linear Discriminant Analysis with Integral Imaging for Occluded Target Recognition
Document Type
Academic Journal
Source
Current Optics and Photonics. 2008-06 12(2):88-92
Subject
photon counting recognition
photon counting linear discriminant analysis(LDA)
integral imaging
computational reconstruction
occluded target recognition
pattern classification
Language
Korean
ISSN
2508-7266
2508-7274
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.