Simulation of non-line-of-sight imaging system based on the light-cone transform

Wenhua Zhu; Jingjing Tan; Caiwen Ma; Xiuqin Su

doi:10.1117/12.2586651

15 January 2021 Simulation of non-line-of-sight imaging system based on the light-cone transform

Wenhua Zhu, Jingjing Tan, Caiwen Ma, Xiuqin Su

Author Affiliations +

Proceedings Volume 11761, Fourth International Conference on Photonics and Optical Engineering; 1176121 (2021) https://doi.org/10.1117/12.2586651
Event: Fourth International Conference on Photonics and Optical Engineering, 2020, Xi'an, China

Abstract

Non-line-of-sight (NLOS) imaging is an emerging technique, which can observe objects obscured by occluders. Thanks to the improvement of optical configurations, it is receiving growing interest from researchers. In this paper, we reconstruct both 2D and 3D images by adopting the light-cone transform and validated on simulated data. Numerical results are evaluated by structural similarity index (SSIM). The results showed the good performance of the algorithm in preserving the details of 2D image and reconstruction of 3D image. The structural similarity index of the reconstructed image and the reference image is more than 50%, the target is hence being identified. This work contributes to the construction of the real system.

Citation Download Citation

Wenhua Zhu, Jingjing Tan, Caiwen Ma, and Xiuqin Su "Simulation of non-line-of-sight imaging system based on the light-cone transform", Proc. SPIE 11761, Fourth International Conference on Photonics and Optical Engineering, 1176121 (15 January 2021); https://doi.org/10.1117/12.2586651

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE