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We present a theoretical and computational model for simulating Single-Photon Avalanche Diode (SPAD) array images in the context of time-of-flight Lidar. We confirm the accuracy of out model by experimental verification. Further, we demonstrate that our simulated data can be used to train bespoke neural networks facilitating a number of enhanced imaging capabilities including, super-resolution, human-activity recognition, and long range SPAD Lidar.
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Stirling Scholes, German Mora-Martin, Istvan Gyongy, Gerald Buller, Jonathan Leach, "Generation of photo-realistic SPAD-lidar data," Proc. SPIE 13200, Electro-Optical and Infrared Systems: Technology and Applications XXI, 132000D (1 November 2024); https://doi.org/10.1117/12.3031447