期刊
OPTICS AND LASERS IN ENGINEERING
卷 160, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.optlaseng.2022.107292
关键词
Displacement-sensible imaging; Imaging through unknown diffusers; Physics-aware learning
类别
This article proposes a displacement-sensitive imaging method, which combines the optical memory effect prior and deep learning to recover hidden objects behind opaque scattering media. By utilizing speckle-correlation magnification to excavate physics priors related to depth of field, and developing a flexible deep learning framework to recover objects with different depth of field positions.
Imaging through unstable scattering scenes is a challenging task and the focus of attention. More computational techniques and optimization methods have been introduced in objects recovery hidden behind opaque scattering media. A combination of the optical memory effect (OME) prior and deep learning (DL) has been demonstrated in scalable imaging through unknown diffusers with high fidelity. Here, a displacement-sensible imaging method is proposed to reconstruct the hidden objects with unseen depth-of-field (DOF) positions, and the reconstructed objects with different displacements are aligned with the practical imaging size. Related physics priors to DOF are excavated by utilizing the speckle-correlation magnification and developing a flexible DL framework to recover the objects with variable DOF positions. This flexible physics-aware learning approach gives a heuristic to complex imaging problems with specific application scenes.
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