Three-dimensional (3D) visualization and recognition using truncated photon counting model and integral imaging

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationThree-Dimensional Imaging, Visualization, and Display 2010 and Display Technologies and Applications for Defense, Security, and Avionics IV
DOIs
StatePublished - 2010
EventThree-Dimensional Imaging, Visualization, and Display 2010 and Display Technologies and Applications for Defense, Security, and Avionics IV - Orlando, FL, United States
Duration: 6 Apr 20108 Apr 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7690
ISSN (Print)0277-786X

Conference

ConferenceThree-Dimensional Imaging, Visualization, and Display 2010 and Display Technologies and Applications for Defense, Security, and Avionics IV
Country/TerritoryUnited States
CityOrlando, FL
Period6/04/108/04/10

Keywords

  • And photon counting imaging
  • Three-dimensional image processing
  • Three-dimensional image recognition

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