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Proceedings Paper

Three dimensional photon counting integral imaging based on Bayesian adaptive reconstruction
Author(s): Jiajia Qi; Xiaoyong Jiang; Yuanjin Chen; Weiji He; Guohua Gu; Qian Chen
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Paper Abstract

Aiming at the problem of three dimensional reconstruction of photon-limited objects, a new method of Bayesian adaptive estimation is proposed based on the photon counting integral imaging (II) system to improve the quality of reconstructed depth slice images. Firstly, an array of photon counting elemental images is obtained by the photon counting II system. Then, a local adaptive mean factor is introduced into the Bayesian framework as a form of exponential prior distribution. Finally, elemental images estimated by the posterior mean are back propagated to reconstruct depth slice images. The experimental results reconstructed by the proposed method achieve higher peak signal-to-noise ratio than the traditional Bayesian method under photon-starved conditions.

Paper Details

Date Published: 9 August 2018
PDF: 9 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108063P (9 August 2018); doi: 10.1117/12.2503130
Show Author Affiliations
Jiajia Qi, Nanjing Univ. of Science and Technology (China)
Xiaoyong Jiang, Beijing Institute of Radio Metrology and Measurement (China)
Yuanjin Chen, The 214 Institute of China North Industries Group Corp. (China)
Weiji He, Nanjing Univ. of Science and Technology (China)
Guohua Gu, Nanjing Univ. of Science and Technology (China)
Qian Chen, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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