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通过物理感知学习实现透过未知不透明散射层的高效彩色成像。

Efficient color imaging through unknown opaque scattering layers via physics-aware learning.

作者信息

Zhu Shuo, Guo Enlai, Gu Jie, Cui Qianying, Zhou Chenyin, Bai Lianfa, Han Jing

出版信息

Opt Express. 2021 Nov 22;29(24):40024-40037. doi: 10.1364/OE.441326.

Abstract

Color imaging with scattered light is crucial to many practical applications and becomes one of the focuses in optical imaging fields. More physics theories have been introduced in the deep learning (DL) approach for the optical tasks and improve the imaging capability a lot. Here, an efficient color imaging method is proposed in reconstructing complex objects hidden behind unknown opaque scattering layers, which can obtain high reconstruction fidelity in spatial structure and accurate restoration in color information by training with only one diffuser. More information is excavated by utilizing the scattering redundancy and promotes the physics-aware DL approach to reconstruct the color objects hidden behind unknown opaque scattering layers with robust generalization capability by an efficient means. This approach gives impetus to color imaging through dynamic scattering media and provides an enlightening reference for solving complex inverse problems based on physics-aware DL methods.

摘要

散射光彩色成像对许多实际应用至关重要,并成为光学成像领域的研究热点之一。在深度学习(DL)方法中引入了更多物理理论用于光学任务,极大地提高了成像能力。在此,提出了一种有效的彩色成像方法,用于重建隐藏在未知不透明散射层后面的复杂物体,通过仅使用一个散射器进行训练,该方法可以在空间结构上获得高重建保真度,并在颜色信息上实现准确恢复。通过利用散射冗余挖掘更多信息,并推动基于物理感知的DL方法以有效方式重建隐藏在未知不透明散射层后面的彩色物体,具有强大的泛化能力。该方法推动了通过动态散射介质的彩色成像,并为基于物理感知DL方法解决复杂逆问题提供了具有启发性的参考。

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