Anti-perturbation Multimode Fiber Imaging Based on the Active Measurement of the Fiber Configuration,ACS Photonics

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Anti-perturbation Multimode Fiber Imaging Based on the Active Measurement of the Fiber Configuration
ACS Photonics ( IF 6.5 ) Pub Date : 2023-06-30 , DOI: 10.1021/acsphotonics.3c00390
Runze Zhu ₁ , Junxian Luo ₂ , Xinxin Zhou ₁ , Haogong Feng ₁ , Fei Xu ₁

Affiliation

Multimode fiber (MMF) imaging is an emerging field of fiber imaging technology in the last few decades. However, its high sensitivity to dynamic perturbance limits its practical applications. In this study, we propose an anti-perturbation scheme for MMF imaging based on the active measurement of the fiber configuration. We fabricate an imaging device composed of the MMF and fiber Bragg grating array to measure the MMF configuration parameters in real time and record the object–speckle pairs in different configurations for neural network training. Image reconstruction subjected to dynamic perturbations can be realized using deep learning, and the experimental results show that the introduction of fiber configuration parameters can improve the quality of anti-perturbation imaging. In addition, we realize speckle prediction using the configuration parameters and a trained neural network. The predicted speckle can be applied to flexible MMF compressive imaging. Our work proposes a new scheme for flexible MMF imaging and provides an important reference for the practical application of MMF imaging.

中文翻译：

基于光纤配置主动测量的抗扰动多模光纤成像

多模光纤（MMF）成像是近几十年来光纤成像技术的一个新兴领域。然而，其对动态扰动的高敏感性限制了其实际应用。在本研究中，我们提出了一种基于光纤配置主动测量的 MMF 成像抗扰动方案。我们制作了由多模光纤和光纤布拉格光栅阵列组成的成像装置，实时测量多模光纤的配置参数，并记录不同配置下的物体-散斑对，用于神经网络训练。利用深度学习可以实现动态扰动下的图像重建，实验结果表明光纤配置参数的引入可以提高抗扰动成像的质量。此外，我们使用配置参数和经过训练的神经网络实现散斑预测。预测的散斑可应用于灵活的MMF压缩成像。我们的工作提出了一种灵活的MMF成像新方案，为MMF成像的实际应用提供了重要参考。

更新日期：2023-06-30

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