Real-time imaging through dynamic scattering media enabled by fixed optical modulations

Fuente: arXiv
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Hauptverfasser: Li, Yuegang, Wang, Junjie, Xiao, Tailong, Zheng, Ze, Huang, Jingzheng, He, Ming, Fan, Jianping, Zeng, Guihua
Format: Preprint
Veröffentlicht: 2025
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author Li, Yuegang
Wang, Junjie
Xiao, Tailong
Zheng, Ze
Huang, Jingzheng
He, Ming
Fan, Jianping
Zeng, Guihua
author_facet Li, Yuegang
Wang, Junjie
Xiao, Tailong
Zheng, Ze
Huang, Jingzheng
He, Ming
Fan, Jianping
Zeng, Guihua
contents Dynamic scattering remains a significant challenge to the practical deployment of anti-scattering imaging. Existing methods, such as transmission matrix measurements, iterative wavefront shaping, and optical phase conjugation, depend on a quasi-static assumption, requiring the object and scattering medium to remain stable during a single imaging process to enable one-to-one compensation. However, image reconstruction becomes unattainable when this assumption is violated. Here, we propose a novel imaging strategy that counteracts time-dependent scattering perturbations through a fixed modulation module. This one-to-many compensation mechanism is realized via optical diffraction neural networks (ODNNs) trained on simulated datasets. For the first time, we reveal that its feasibility stems from the optical shower-curtain effect, and its effectiveness typically within 1-2 transport mean free paths. Our approach is not only immune to speckle decorrelation but also leverages it to enhance image quality. ODNNs generalize effectively to real-world scattering medium scenarios via multi-simulated scattering media learning and reconstruct images in real time with light-speed processing. We achieve 80 Hz imaging of moving objects in dynamic scattering media with decorrelation times < 1 ms, demonstrating applicability in large-field-of-view imaging and incoherent illumination scenarios. This work lays the foundation for high-speed, intelligent optical imaging, advancing practical anti-dynamic scattering techniques.
format Preprint
id arxiv_https___arxiv_org_abs_2508_15286
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Real-time imaging through dynamic scattering media enabled by fixed optical modulations
Li, Yuegang
Wang, Junjie
Xiao, Tailong
Zheng, Ze
Huang, Jingzheng
He, Ming
Fan, Jianping
Zeng, Guihua
Optics
Dynamic scattering remains a significant challenge to the practical deployment of anti-scattering imaging. Existing methods, such as transmission matrix measurements, iterative wavefront shaping, and optical phase conjugation, depend on a quasi-static assumption, requiring the object and scattering medium to remain stable during a single imaging process to enable one-to-one compensation. However, image reconstruction becomes unattainable when this assumption is violated. Here, we propose a novel imaging strategy that counteracts time-dependent scattering perturbations through a fixed modulation module. This one-to-many compensation mechanism is realized via optical diffraction neural networks (ODNNs) trained on simulated datasets. For the first time, we reveal that its feasibility stems from the optical shower-curtain effect, and its effectiveness typically within 1-2 transport mean free paths. Our approach is not only immune to speckle decorrelation but also leverages it to enhance image quality. ODNNs generalize effectively to real-world scattering medium scenarios via multi-simulated scattering media learning and reconstruct images in real time with light-speed processing. We achieve 80 Hz imaging of moving objects in dynamic scattering media with decorrelation times < 1 ms, demonstrating applicability in large-field-of-view imaging and incoherent illumination scenarios. This work lays the foundation for high-speed, intelligent optical imaging, advancing practical anti-dynamic scattering techniques.
title Real-time imaging through dynamic scattering media enabled by fixed optical modulations
topic Optics
url https://arxiv.org/abs/2508.15286