Deep Learning-Based Image Classification through a Multimode Fiber in the Presence of Wavelength Drift

Abstract

Deep neural networks (DNNs) are employed to recover information after its propagation through a multimode fiber (MMF) in the presence of wavelength drift. The intensity distribution of the speckle patterns generated at the output of an MMF when an input wavefront propagates along its length is highly sensitive to wavelength changes. We use a tunable laser to implement a wavelength drift with a controlled bandwidth, aiming to estimate the DNN’s performance in different cases and identify the limitations. We find that when the DNNs are trained with a dataset which includes the noise induced by wavelength changes, successful classification of a speckle pattern can be performed even for a large wavelength bandwidth drift. A single training step is found to be sufficient for high classification accuracy, removing the need for time-consuming recalibration at each wavelength.

Controlling light propagation in multimode fibers for imaging, spectroscopy, and beyond

“…28). Further, neural networks have been used to reconstruct image information in fibers which are subjected to bending [132][133][134][198][199][200][201][202][203] and spectral correlation [204].…”

Roadmap on wavefront shaping and deep imaging in complex media

“…Another source of perturbation is the drift in the wavelength of the laser source that decorrelates the output intensity with time. In a study conducted by Kakkava et al [209][210][211], it was shown that the DNNs can correct for the decorrelation rendered by the wavelength change of the fiber with an extended bandwidth.…”

Artificial Intelligence in Classical and Quantum Photonics

“…In 2020, Kakkava et al. [ 153 ] proposed an alternative approach for recovering the information through the MMF system in the presence of a wavelength drift in the light source using DNNs. Indeed, perturbations of the system caused by wavelength, thermal or mechanical drift, may be catastrophic for a calibration‐based technique such as TM.…”