Three dimensional photon counting integral imaging based on Bayesian adaptive reconstruction

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.