Underwater Binocular Meta-lens

Xiaoyuan Liu, Mu Ku Chen*, Cheng Hung Chu, Jingcheng Zhang, Borui Leng, Takeshi Yamaguchi, Takuo Tanaka*, Din Ping Tsai*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

51 Citations (Scopus)
44 Downloads (CityUHK Scholars)

Abstract

Underwater optics in all-aquatic environments is vital for environmental management, biogeochemistry, phytoplankton ecology, benthic processes, global change, etc. Many optical techniques of observational systems for underwater sensing, imaging, and applications have been developed. For the demands of compact, miniaturized, portable, lightweight, and low-energy consumption, a novel underwater binocular depth-sensing and imaging meta-optic device is developed and reported here. A GaN binocular meta-lens is specifically designed and fabricated to demonstrate underwater stereo vision and depth sensing. The diameter of each meta-lens is 2.6 mm, and the measured distance between the two meta-lens centers is 4.04 mm. The advantage of our binocular meta-lens is no need of distortion correction or camera calibration, which is necessary for traditional two-camera stereo vision systems. Based on the experimental results, we developed the generalized depth calculation formula for all-size binocular vision systems. With deep-learning support, this stereo vision system can realize the fast underwater object’s depth and image computation for real-time processing capability. Our artificial intelligent imaging results show that depth measurement accuracy is down to 50 μm. Besides the aberration-free advantage of flat meta-optic components, the intrinsic superhydrophobicity properties of our nanostructured GaN meta-lens enable an antiadhesion, stain-resistant, and self-cleaning novel underwater imaging device. This stereo vision binocular meta-lens will significantly benefit underwater micro/nanorobots, autonomous submarines, machine vision in the ocean, marine ecological surveys, etc. © 2023 The Authors. Published by American Chemical Society
Original languageEnglish
Pages (from-to)2382–2389
Number of pages8
JournalACS Photonics
Volume10
Issue number7
Online published19 Jan 2023
DOIs
Publication statusPublished - 19 Jul 2023

Funding

We thank Dr. Mitch Guijun Li and Miss. Huan Liu for their assistance in hydrophobicity measurements. We acknowledge the support from the University Grants Committee/Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. AoE/P-502/20 and GRF Projects 15303521 and 11310522), the Shenzhen Science and Technology Innovation Commission Grant (No. SGDX2019081623281169), the Department of Science and Technology of Guangdong Province (2020B1515120073), City University of Hong Kong (Project No. 9380131), and JST CREST (Grant No. JPMJCR1904).

Research Keywords

  • meta-lens
  • binocular vision
  • underwater depth sensing
  • stereo vision
  • deep learning

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

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