Lensless computational imaging through deep learning
Author(s)Sinha, Ayan T; Lee, Justin; Li, Shuai; Barbastathis, George
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Deep learning has been proven to yield reliably generalizable solutions to numerous classification and decision tasks. Here, we demonstrate for the first time to our knowledge that deep neural networks (DNNs) can be trained to solve end-to-end inverse problems in computational imaging. We experimentally built and tested a lensless imaging system where a DNN was trained to recover phase objects given their propagated intensity diffraction patterns.
DepartmentInstitute for Medical Engineering and Science; Massachusetts Institute of Technology. Department of Mechanical Engineering
Optical Society of America
Sinha, Ayan et al. “Lensless Computational Imaging through Deep Learning.” Optica 4, 9 (September 2017): 1117 © 2017 Optical Society of America