Learning complex scattering media for optical encryption: publisher’s note

2020 ◽  
Vol 45 (19) ◽  
pp. 5501
Author(s):  
Lina Zhou ◽  
Yin Xiao ◽  
Wen Chen
2020 ◽  
Vol 28 (24) ◽  
pp. 36432
Author(s):  
Qing Han ◽  
Wenjing Zhao ◽  
Aiping Zhai ◽  
Zhirun Wang ◽  
Dong Wang

2020 ◽  
Vol 45 (18) ◽  
pp. 5279 ◽  
Author(s):  
Lina Zhou ◽  
Yin Xiao ◽  
Wen Chen

OSA Continuum ◽  
2020 ◽  
Vol 3 (11) ◽  
pp. 2968
Author(s):  
Yifan Liu ◽  
Panpan Yu ◽  
Yinmei Li ◽  
Lei Gong

2002 ◽  
Vol 33 (3-4) ◽  
pp. 4
Author(s):  
M. L. German ◽  
E. P. Nogotov ◽  
V. P. Necrasov
Keyword(s):  

2020 ◽  
Vol 2020 (14) ◽  
pp. 306-1-306-6
Author(s):  
Florian Schiffers ◽  
Lionel Fiske ◽  
Pablo Ruiz ◽  
Aggelos K. Katsaggelos ◽  
Oliver Cossairt

Imaging through scattering media finds applications in diverse fields from biomedicine to autonomous driving. However, interpreting the resulting images is difficult due to blur caused by the scattering of photons within the medium. Transient information, captured with fast temporal sensors, can be used to significantly improve the quality of images acquired in scattering conditions. Photon scattering, within a highly scattering media, is well modeled by the diffusion approximation of the Radiative Transport Equation (RTE). Its solution is easily derived which can be interpreted as a Spatio-Temporal Point Spread Function (STPSF). In this paper, we first discuss the properties of the ST-PSF and subsequently use this knowledge to simulate transient imaging through highly scattering media. We then propose a framework to invert the forward model, which assumes Poisson noise, to recover a noise-free, unblurred image by solving an optimization problem.


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