When vision is provided through thermal-imaging systems field-of-view is reduced, effectively the soldier must operate with severe tunnel vision and so there is a requirement for a system which provides automated warning and immersive imaging. We present a computational multi-aperture thermal infrared (MA-TIR) imaging system with single-photon range imaging to provide enhanced video-rate detection of obscured biological signatures in clutter. Our multi-camera computational imaging system creates a 360° panoramic image, and we employ synthetic baseline integral imaging (SBII) for the construction of three-dimensional thermal scenes, including detection of occluded objects. We further fuse thermal imaging with covert time-correlated single-photon counting (TCSPC) LIDAR to provide the complementary capability of video-rate ranging with the ability to detect and classify targets through clutter, particularly based on movement signatures. Finally, we demonstrate the ability to discriminate between biological scene components and static clutter based on temporal modulations of picosecond resolution TCSPC returns.
We describe how the use of multiple-camera imaging systems provides an interesting alternative imaging modality to conventional single-aperture imaging, but with a different challenge: to computationally integrate diverse images while demonstrating an overall system benefit. We report the use of super-resolution with arrays of nominally identical longwave infrared cameras to yield high-resolution imaging with reduced track length, while various architectures enable foveal imaging, 4π and 3D imaging through the exploitation of integral imaging techniques. Strikingly, multi-camera spectral imaging using a camera array can uniquely demonstrate video-rate imaging, high performance and low cost.