Exploiting holographically encoded variance to transmit labelled images through a multimode optical fiber.

Artificial intelligence has emerged as promising tool to decode an image transmitted through a multimode fiber (MMF) by applying deep learning techniques. By transmitting thousands of images through the MMF, deep neural networks (DNNs) are able to decipher the seemingly random output speckle patterns and unveil the intrinsic input-output relationship. High fidelity reconstruction is obtained for datasets with a large degree of homogeneity, which underutilizes the capacity of the combined MMF-DNN system. Here, we show that holographic modulation can encode an additional layer of variance on the output speckle pattern, improving the overall transmissive capabilities of the system. Operatively, we have implemented this by adding a holographic label to the original dataset and injecting the resulting phase image into the fiber facet through a Fourier transform lens. The resulting speckle pattern dataset can be clustered primarily by holographic label, and can be reconstructed without loss of fidelity. As an application, we describe how color images may be segmented into RGB components and each color component may then be labelled by distinct hologram. A ResUNet architecture was then used to decode each class of speckle patterns and reconstruct the color image without the need for temporal synchronization between sender and receiver.

Optimizing the internal phase reference to shape the output of a multimode optical fiber.

Pre-shaping light to achieve desired amplitude distributions at the tip of a multimode fiber (MMF) has emerged as a powerful method allowing a wide range of imaging techniques to be implemented at the distal facet. Such techniques rely on measuring the transmission matrix of the optically turbid waveguide which scrambles the coherent input light into an effectively random speckle pattern. Typically, this is done by measuring the interferogram between the output speckle and a reference beam. In recent years, an optical setup where the reference beam passes through the MMF has become an attractive configuration because of the high interferometric stability of the common optical path. However, the merits and drawbacks of an internal reference beam remain controversial. The measurement of the transmission matrix is known to depend on the choice of internal reference and has been reported to result in "blind spots" due to phase singularities of the reference beam. Here, we describe how the focussing efficiency of the calibration can be increased by several percent by optimising the choice of internal reference beam.