Brain-inspired optical imaging: a neuromorphic computing approach for image reconstruction of dynamic targets obscured by dense turbid media

Ning Zhang; Arto Nurmikko

doi:10.1117/12.3000089

13 March 2024 Brain-inspired optical imaging: a neuromorphic computing approach for image reconstruction of dynamic targets obscured by dense turbid media

Ning Zhang, Arto Nurmikko

Author Affiliations +

Proceedings Volume 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences; 1285705 (2024) https://doi.org/10.1117/12.3000089
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

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.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ning Zhang and Arto Nurmikko "Brain-inspired optical imaging: a neuromorphic computing approach for image reconstruction of dynamic targets obscured by dense turbid media", Proc. SPIE 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences, 1285705 (13 March 2024); https://doi.org/10.1117/12.3000089

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