For ever more efficient optical fibres

By applying a computer program that mimics the way the human brain learns to identify objects, EPFL scientists are now able to reconstruct images that have been degraded by passing through an optical fiber. EPFL researchers have taught a type of machine learning algorithm to reconstruct images that became blurred while being transmitted through an optical fiber. The work could increase the amount of information transmitted through telecommunications networks, improve endoscopic imaging used in medical diagnosis and enhance the capacity and quality of optical fibers. "We use modern deep neural network architectures to retrieve the input images from the scrambled output of the fiber," said Demetri Psaltis, the head of EPFL's Optics Laboratory, who led the research in collaboration with colleague Christophe Moser from the Laboratory of Applied Photonics Devices. "We demonstrate that this is possible even for fibers 1 kilometer long," he added, calling the work an important milestone. Their research has now been published in the journal . Deciphering the blur Optical fibers have long been used to transmit information with light.