Abstract
In this paper, we review three-dimensional (3D) photon counting imaging with axially distributed sensing. Under severely photon-starved conditions, we have proposed various imaging and algorithmic approaches to reconstruct a scene in 3D, which are not possible by using conventional imaging system due to lack of sufficient number of photons. In this paper, we present an overview of optical sensing and imaging system along with dedicated algorithms for reconstructing 3D scenes by photon counting axially distributed sensing, which may be implemented by moving a single image sensor along its optical axis. To visualize the 3D image, statistical estimation methods and computational reconstruction of axially distributed sensing is applied.
Highlights
Under severely photon-starved conditions, scenes recorded optically may not be properly reconstructed by conventional imaging systems
Photon counting imaging, 3D images can be visualized by statistical estimations, such as maximum likelihood estimation [2] and Bayesian approaches [4]
Photon counting detection under such conditions can be modeled using a Poisson distribution since photon events may occur rarely in unit time and space [14]. Using this mathematical photon counting imaging model, 3D visualization and object recognition can be performed under photon-starved conditions
Summary
Under severely photon-starved conditions, scenes recorded optically may not be properly reconstructed by conventional imaging systems. 3D information can be recorded and reconstructed under photon-starved conditions with photon counting integral imaging [7,8,9,10,11,12,13]. To obtain the 3D information with high resolution from the scenes and remove the requirement of lateral parallax of image sensor by integral imaging [11], axially distributed sensing (ADS) may be used [12]. To obtain the 3D information with high resolution from the scenes and remove the requirement of lateral parallax image sensorcounting by integral imaging axially distributed sensing (ADS). Work on 3D reconstruction using 3D photon counting ADS along with some experiments to illustrate
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