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Learning-based real-time imaging through dynamic scattering media

Engineering and Technology

Learning-based real-time imaging through dynamic scattering media

H. Liu, F. Wang, et al.

This groundbreaking research, conducted by Haishan Liu, Fei Wang, Ying Jin, Xianzheng Ma, Siteng Li, Yaoming Bian, and Guohai Situ, introduces a revolutionary learning-based technique for real-time, non-invasive imaging through dense scattering media. Demonstrating exceptional image quality and speed, this study pushes the boundaries of conventional imaging methods.

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~3 min • Beginner • English
Abstract
Imaging through dynamic scattering media is one of the most challenging yet fascinating problems in optics, with applications spanning from biological detection to remote sensing. In this study, we propose a comprehensive learning-based technique that facilitates real-time, non-invasive, incoherent imaging of real-world objects through dense and dynamic scattering media. We conduct extensive experiments, demonstrating the capability of our technique to see through turbid water and natural fog. The experimental results indicate that the proposed technique surpasses existing approaches in numerous aspects and holds significant potential for imaging applications across a broad spectrum of disciplines.
Publisher
Light: Science & Applications
Published On
Apr 01, 2024
Authors
Haishan Liu, Fei Wang, Ying Jin, Xianzheng Ma, Siteng Li, Yaoming Bian, Guohai Situ
Tags
dynamic scattering
non-invasive imaging
real-time
turbid water
natural fog
image quality
learning-based technique
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