Aloni Doron, Stern Adrian, Javidi Bahram
Electro Optical Unit, Ben Gurion University of the Negev, Beer-Sheva 84105, Israel.
Opt Express. 2011 Sep 26;19(20):19681-7. doi: 10.1364/OE.19.019681.
Recent works have demonstrated that three-dimensional (3D) object reconstruction is possible from integral images captured in severely photon starved conditions. In this paper we propose an iterative approach to implement a maximum likelihood expectation maximization estimator with several types of regularization for 3D reconstruction from photon counting integral images. We show that the proposed algorithms outperform the previously reported approaches for photon counting 3D integral imaging reconstruction. To the best of our knowledge, this is the first report on using iterative statistical reconstruction techniques for 3D photon counting integral imaging.
最近的研究表明，在严重光子饥饿条件下捕获的积分图像可以实现三维（3D）物体重建。在本文中，我们提出了一种迭代方法，用于实现具有几种正则化类型的最大似然期望最大化估计器，以从光子计数积分图像进行三维重建。我们表明，所提出的算法在光子计数三维积分成像重建方面优于先前报道的方法。据我们所知，这是关于使用迭代统计重建技术进行三维光子计数积分成像的首次报道。
