Image transmission through a flexible multimode fiber by deep learning
2020
When multimode optical fibers are perturbed, the data that is transmitted through them is scrambled. This presents a major difficulty for many possible applications, such as multimode fiber based telecommunication and endoscopy. To overcome this challenge we present a deep learning approach that generalizes over mechanical perturbations. Using our approach, we are able to successfully reconstruct the input images from intensity-only measurements of speckle patterns at the output of a 1.5 meter-long randomly perturbed multimode fiber. We explain the model's success by hidden correlations in the speckle of random fiber conformations.
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