Paper
30 April 2024 Active non-line-of-sight imaging through dense fog via hybrid intelligent enhancement perception system
Author Affiliations +
Proceedings Volume 13155, Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Imaging Systems; 131550G (2024) https://doi.org/10.1117/12.3015924
Event: Sixth Conference on Frontiers in Optical Imaging Technology and Applications (FOI2023), 2023, Nanjing, JS, China
Abstract
Non-line-of-sight(NLOS) imaging through fog has been extensively researched in the fields of optics and computer vision. However, due to the influence of strong backscattering and diffuse reflection generated by the dense fog on the temporal-spatial correlations of photons returning from the target object, the reconstruction quality of most existing methods is significantly reduced under dense fog conditions. In this study, we define the optical imaging process in a foggy environment and propose a hybrid intelligent enhancement perception(HIEP) system based on Time-of-Flight(ToF) methods and physics-driven Swin transformer(ToFormer) to eliminate scattering effects and reconstruct targets under heterogeneous fog with varying optical thickness. Furthermore, we assembled a prototype of the HIEP system and established the Active Non-Line-of-Sight Imaging Through Dense Fog(NLOSTDF) dataset to train the reconstruction network. The experimental results demonstrate that even in dense fog short-distance scenarios with an optical thickness of up to 2.5 and imaging distances less than 6 meters, our approach achieves clear imaging of the target scene, surpassing existing optical and computer vision methods.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Ziqin Xu, Yanxin Zhang, Haopeng Zhao, Fengchang Miao, Hao Liu, Shaohui Jin, and Mingliang Xu "Active non-line-of-sight imaging through dense fog via hybrid intelligent enhancement perception system", Proc. SPIE 13155, Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Imaging Systems, 131550G (30 April 2024); https://doi.org/10.1117/12.3015924
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