斑点图案
不透明度
计算机科学
人工智能
流离失所(心理学)
计算机视觉
深度学习
高保真
启发式
可扩展性
忠诚
散射
物理
光学
声学
心理学
心理治疗师
电信
数据库
作者
Shuo Zhu,Enlai Guo,Kaixuan Bai,Wenjun Zhang,Lianfa Bai,Jing Han
标识
DOI:10.1016/j.optlaseng.2022.107292
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI