Binary amplitude-only image reconstruction through a MMF based on an AE-SNN combined deep learning model
H Chen, Z He, Z Zhang, Y Geng, W Yu - Optics Express, 2020 - opg.optica.org
The obstacle of imaging through multimode fibers (MMFs) is encountered due to the fact that
the inherent mode dispersion and mode coupling lead the output of the MMF to be scattered …
the inherent mode dispersion and mode coupling lead the output of the MMF to be scattered …
Multimode optical fiber transmission with a deep learning network
Multimode fibers (MMFs) are an example of a highly scattering medium, which scramble the
coherent light propagating within them to produce seemingly random patterns. Thus, for …
coherent light propagating within them to produce seemingly random patterns. Thus, for …
High-fidelity imaging through multimode fibers via deep learning
J Zhao, X Ji, M Zhang, X Wang, Z Chen… - Journal of Physics …, 2021 - iopscience.iop.org
Imaging through multimode fibers (MMFs) is a challenging task. Some approaches, eg
transmission matrix or digital phase conjugation, have been developed to realize imaging …
transmission matrix or digital phase conjugation, have been developed to realize imaging …
Seeing through multimode fibers with physics-assisted deep learning
H Gao, H Hu, Y Zhang, W Zhang, T Yan - Optics & Laser Technology, 2023 - Elsevier
High-fidelity image transmission through multimode fiber is critical for the biomedical
imaging and telecommunications industries. However, mode coupling and modal dispersion …
imaging and telecommunications industries. However, mode coupling and modal dispersion …
Deep learning-based multimode fiber imaging in multispectral and multipolarimetric channels
R Zhu, H Feng, F Xu - Optics and Lasers in Engineering, 2023 - Elsevier
Multimode optical fiber (MMF) imaging is an emerging fiber imaging technology that has
been developed during the last decade. In this work, we demonstrate deep-learning-based …
been developed during the last decade. In this work, we demonstrate deep-learning-based …
Deep learning image transmission through a multimode fiber based on a small training dataset
An improved deep neural network incorporating attention mechanism and DSSIM loss
function (AM_U_Net) is used to recover input images with speckles transmitted through a …
function (AM_U_Net) is used to recover input images with speckles transmitted through a …
Imaging through multimode fibres with physical prior
C Zhang, Y Shi, Z Yao, X Sui, Q Cheng - arXiv preprint arXiv:2311.03062, 2023 - arxiv.org
Imaging through perturbed multimode fibres based on deep learning has been widely
researched. However, existing methods mainly use target-speckle pairs in different …
researched. However, existing methods mainly use target-speckle pairs in different …
Deep learning for efficiently imaging through the localized speckle field of a multimode fiber
Y Chen, B Song, J Wu, W Lin, W Huang - Applied Optics, 2023 - opg.optica.org
Due to the occurrence of redundant speckle, multimode fiber (MMF) imaging is extremely
challenging. Our work studies the relationship between the effective feature distribution of …
challenging. Our work studies the relationship between the effective feature distribution of …
High-speed multimode fiber imaging system based on conditional generative adversarial network
The multimode fiber (MMF) has great potential to transmit high-resolution images with less
invasive methods in endoscopy due to its large number of spatial modes and small core …
invasive methods in endoscopy due to its large number of spatial modes and small core …
Image reconstruction through a multimode fiber with a simple neural network architecture
Multimode fibers (MMFs) have the potential to carry complex images for endoscopy and
related applications, but decoding the complex speckle patterns produced by mode-mixing …
related applications, but decoding the complex speckle patterns produced by mode-mixing …