Light Propagation Prediction through Multimode Optical Fibers with a Deep Neural Network
Optics
2018-12-10 v1 Machine Learning
Abstract
This work demonstrates a computational method for predicting the light propagation through a single multimode fiber using a deep neural network. The experiment for gathering training and testing data is performed with a digital micro-mirror device that enables the spatial light modulation. The modulated patterns on the device and the captured intensity-only images by the camera form the aligned data pairs. This sufficiently-trained deep neural network frame has very excellent performance for directly inferring the intensity-only output delivered though a multimode fiber. The model is validated by three standards: the mean squared error (MSE), the correlation coefficient (corr) and the structural similarity index (SSIM).
Cite
@article{arxiv.1812.02814,
title = {Light Propagation Prediction through Multimode Optical Fibers with a Deep Neural Network},
author = {Pengfei Fan and Liang Deng and Lei Su},
journal= {arXiv preprint arXiv:1812.02814},
year = {2018}
}