Dynamic perturbation mitigation via polarization difference neural network for high-fidelity ring core fiber image transmission

Ring core fibers (RCFs) offer unique advantages in fiber image transmission, as their weakly-coupled orbital angular momentum mode groups result in high resolution images. However, severe image distortion is still exhibited during fiber transmission when subjected to strong disturbances. Here, we present a novel approach with a differential neural network, namely the polarization speckle differential imaging (PSDI) method, to significantly enhance both the robustness and image resolution of RCF-based imaging systems. When the fibers are disturbed, the PSDI method establishes the perturbation mapping relationship between two polarization speckles and utilizes a differential method to eliminate the perturbation effect in the speckles. This approach mitigates environmental disturbances, resulting in an enhancement of the imaging system's robustness in dynamic environments. By addressing the limitations of conventional techniques, this research represents a significant advancement in the field of fiber imaging technology, with potential applications ranging from endoscopy to high-resolution imaging in complex and dynamic settings.

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Publication Details

Journal
Optics Express
Published
2024-08-23
DOI
https://doi.org/10.1364/oe.528518
Citations
1
Primary Topic
Random lasers and scattering media
Type
article
Field-Weighted Citation Impact
0.28

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Dynamic perturbation mitigation via polarization difference neural network for high-fidelity ring core fiber image transmission

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Optics Express
Random lasers and scattering media
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article

Dynamic perturbation mitigation via polarization difference neural network for high-fidelity ring core fiber image transmission

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article en
1 citations

Abstract

Ring core fibers (RCFs) offer unique advantages in fiber image transmission, as their weakly-coupled orbital angular momentum mode groups result in high resolution images. However, severe image distortion is still exhibited during fiber transmission when subjected to strong disturbances. Here, we present a novel approach with a differential neural network, namely the polarization speckle differential imaging (PSDI) method, to significantly enhance both the robustness and image resolution of RCF-based imaging systems. When the fibers are disturbed, the PSDI method establishes the perturbation mapping relationship between two polarization speckles and utilizes a differential method to eliminate the perturbation effect in the speckles. This approach mitigates environmental disturbances, resulting in an enhancement of the imaging system's robustness in dynamic environments. By addressing the limitations of conventional techniques, this research represents a significant advancement in the field of fiber imaging technology, with potential applications ranging from endoscopy to high-resolution imaging in complex and dynamic settings.

Optics ExpressVol. 32(19)
Beijing University of Posts and Telecommunications (CN), Photonics (United States) (US), Convergence (US), State Key Laboratory of Information Photonics and Optical Communications
National Natural Science Foundation of China, Beijing Municipal Natural Science Foundation, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Climate action
Openalex Percentile: Top 55%
Random lasers and scattering media
0.28
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