(Peer-Reviewed) All-optical object identification and three-dimensional reconstruction based on optical computing metasurface
Dingyu Xu 许定誉 ¹, Wenhao Xu 许文昊 ², Qiang Yang 杨强 ¹, Wenshuai Zhang 张文帅 ¹, Shuangchun Wen 文双春 ¹, Hailu Luo 罗海陆 ¹,
¹ Laboratory for Spin Photonics, School of Physics and Electronics, Hunan University, Changsha 410082, China
中国 长沙 湖南大学物理与微电子科学学院 自旋光子学实验室
² School of Physics and Chemistry, Hunan First Normal University, Changsha 410205, China
中国 长沙 湖南第一师范学院物理与化学学院
Opto-Electronic Advances, 2023-12-12
Abstract
Object identification and three-dimensional reconstruction techniques are always attractive research interests in machine vision, virtual reality, augmented reality, and biomedical engineering. Optical computing metasurface, as a two-dimensional artificial design component, has displayed the supernormal character of controlling phase, amplitude, polarization, and frequency distributions of the light beam, capable of performing mathematical operations on the input light field.
Here, we propose and demonstrate an all-optical object identification technique based on optical computing metasurface, and apply it to 3D reconstruction. Unlike traditional mechanisms, this scheme reduces memory consumption in the processing of the contour surface extraction. The identification and reconstruction of experimental results from high-contrast and low-contrast objects agree well with the real objects.
The exploration of the all-optical object identification and 3D reconstruction techniques provides potential applications of high efficiencies, low consumption, and compact systems.
Separation and identification of mixed signal for distributed acoustic sensor using deep learning
Huaxin Gu, Jingming Zhang, Xingwei Chen, Feihong Yu, Deyu Xu, Shuaiqi Liu, Weihao Lin, Xiaobing Shi, Zixing Huang, Xiongji Yang, Qingchang Hu, Liyang Shao
Opto-Electronic Advances
2025-11-25
