We introduce a new, brain-inspired method for extracting high-resolution images of optically dynamic objects obscured by dense scattering media by combining a dynamic vision sensor (DVS) with neuromorphic computing techniques. Spike trains generated by the optical detection hardware form the principal currency for downstream neuromorphic processing, registering only photons emanating from the object while static background from the ambient media is suppressed. The information encoded in each pixel of the camera provides the spiking inputs into a deep spiking neural network via an autoencoder. Results from benchtop experiments suggest the neuromorphic approach as an efficient alternative to existing methods, with applications across medical imaging, optical communication, and microscopy.
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