Learning-based real-time method to looking through scattering medium beyond the memory effect
Abstract
Strong scattering medium brings great difficulties to optical imaging, which is also a problem in medical imaging and many other fields. Optical memory effect makes it possible to image through strong random scattering medium. However, this method also has the limitation of limited angle field-of-view (FOV), which prevents it from being applied in practice. In this paper, a kind of practical convolutional neural network called PDSNet is proposed, which effectively breaks through the limitation of optical memory effect on FOV. Experiments is conducted to prove that the scattered pattern can be reconstructed accurately in real-time by PDSNet, and it is widely applicable to retrieve complex objects of random scales and different scattering media.
Keywords
Cite
@article{arxiv.1910.11272,
title = {Learning-based real-time method to looking through scattering medium beyond the memory effect},
author = {Enlai Guo and Shuo Zhu and Yan Sun and Lianfa Bai and Jing Han},
journal= {arXiv preprint arXiv:1910.11272},
year = {2020}
}
Comments
15 pages with 9 figures