Abstract

Photon-counting integral imaging has been introduced recently, and its applications in three-dimensional (3D) object sensing, visualization, recognition, and classification under photon-starved conditions have been demonstrated. This paper sheds light on the underlying information-theoretic foundation behind the ability of photon-counting integral imaging in performing complex tasks with far fewer photons than conventional imaging systems. A metric for photon-information content is formulated in the context of 3D photon-counting imaging, and its properties are investigated. It is shown that there is an inherent trade-off between imaging fidelity, measured by the entropy-normalized mutual information associated with a given imaging system, and the amount of information in each photon used in the imaging process, as represented by the photon-number–normalized mutual information. The dependence of this trade-off on photon statistics, correlation in the 3D image, and the signal-to-noise ratio of the photon-detection system is also investigated.

© 2012 Optical Society of America

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