Vectorial‐Optics‐Enabled Multi‐View Non‐Line‐Of‐Sight Imaging with High Signal‐To‐Noise Ratio

Author:

Wang Zewei1234,Li Xiaoyin123,Pu Mingbo1234,Chen Lianwei123,Zhang Fei123,Zhang Qi123,Zhao Zhibin1234,Yang Longfei5,Guo Yinghui1234,Luo Xiangang124ORCID

Affiliation:

1. National Key Laboratory of Optical Field Manipulation Science and Technology Institute of Optics and Electronics Chinese Academy of Sciences Chengdu 610209 China

2. State Key Laboratory of Optical Technologies on Nano‐Fabrication and Micro‐Engineering Institute of Optics and Electronics Chinese Academy of Sciences Chengdu 610209 China

3. Research Center on Vector Optical Fields Institute of Optics and Electronics Chinese Academy of Sciences Chengdu 610209 China

4. College of Materials Science and Opto‐Electronic Technology University of Chinese Academy of Sciences Beijing 100049 China

5. Tianfu Xinglong Lake Laboratory Chengdu 610299 China

Abstract

AbstractNon‐line‐of‐sight (NLOS) imaging enables the reconstruction of targets beyond the direct line of sight, which has extensive applications across various fields. However, it remains unclear how and to what extent the vectorial nature of light, which plays a critical role in optical imaging and object recognition, can enhance the imaging performance of active NLOS imaging. Here, this work proposes a method that utilizes vector optical fields (VOFs) with arbitrarily designed polarization distributions to realize NLOS imaging in challenging conditions with low signal‐to‐noise ratio (SNR). A generalized VOF reflection model is established at the relay surface for active NLOS imaging to determine the optimal illumination angle and polarization as well as the received polarization. Based on this model, the feasibility of multi‐view NLOS imaging is demonstrated with enhanced SNR of echo signals under proper VOF modulation, surpassing the limitations of conventional single‐view NLOS imaging. Simulations and experiments validate the superior performance of the proposed approach to realize accurate reconstruction and recognition of hidden objects.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Wiley

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