Computational Imaging is an emerging technology in the field of computer vision which enables optical sensing with new perception capacities and sensing approaches. In contrast to classical approaches, computational imaging uses a strong mathematical model on both part of the imaging process: The data acquisition and the data analysis. In this paper, we present examples where the principles of computational imaging are adapted to active imaging and laser gated viewing. While classical active imaging rely on the projection of a remote line of sight scene with a sensor system with specific resolution (sensor array size) and measures the time of flight due to a predefined sampling rate, we demonstrate the super-resolution time of flight or range measurement and spatial sampling beyond the sensor resolution. Further, we demonstrate the analysis of scattered photons to enhance the perception range and to obtain information on non-line-of-sight targets which are hidden from direct view.
Martin Laurenzis, "Computational sensing approaches for enhanced active imaging," Proc. SPIE 10796, Electro-Optical Remote Sensing XII, 107960H (Presented at SPIE Security + Defence: September 13, 2018; Published: 9 October 2018); https://doi.org/10.1117/12.2325566.
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