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14 May 2010 Three-dimensional (3D) visualization and recognition using truncated photon counting model and integral imaging
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Abstract
In this paper, a statistical approach for three-dimensional (3D) visualization and recognition of photon-starved events based on a parametric estimator is overviewed. A truncated Poisson probability density function is considered for modeling the distribution of a few photons count observation. For 3D visualization and recognition of photon-starved events, an integral imaging, maximum likelihood estimator (MLE) and statistical inference algorithms are employed. It is shown in experiments that the parametric MLE using a truncated Poisson model for estimating the average number of photons for each voxel of a 3D object has a small estimation error compared with the MLE using a Poisson model and 3D recognition performance for photon-starved events can be enhanced by using the presented method.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Inkyu Moon "Three-dimensional (3D) visualization and recognition using truncated photon counting model and integral imaging", Proc. SPIE 7690, Three-Dimensional Imaging, Visualization, and Display 2010 and Display Technologies and Applications for Defense, Security, and Avionics IV, 76900N (14 May 2010); https://doi.org/10.1117/12.849516
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