High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusion
Abstract Three-dimensional (3D) imaging plays a crucial role in autonomous driving, medical diagnostics, and industrial inspection by providing comprehensive spatial information. Metalens-based 3D imaging is highly valued for imaging applications thanks to its compactness, with enhanced precision re...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | npj Nanophotonics |
| Online Access: | https://doi.org/10.1038/s44310-025-00070-9 |
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| _version_ | 1849768605773725696 |
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| author | Yuzhou Song Yifei Zhang Xiaoyuan Liu Takuo Tanaka Mu Ku Chen Zihan Geng |
| author_facet | Yuzhou Song Yifei Zhang Xiaoyuan Liu Takuo Tanaka Mu Ku Chen Zihan Geng |
| author_sort | Yuzhou Song |
| collection | DOAJ |
| description | Abstract Three-dimensional (3D) imaging plays a crucial role in autonomous driving, medical diagnostics, and industrial inspection by providing comprehensive spatial information. Metalens-based 3D imaging is highly valued for imaging applications thanks to its compactness, with enhanced precision remaining a key research pursuit. Here, we present an integrated high-accuracy 3D imaging system combining binocular meta-lens with an optical clue fusion network. Our innovation lies in the synergistic fusion of physics-derived absolute stereo depth measurements and machine learning-estimated relative depth through adaptive confidence mapping - the latter effectively addressing the inherent limitations of absolute depth estimation in scenarios with insufficient matching features. This hybrid approach achieves unprecedented precision of depth estimation (error <1%) while maintaining robust performance across feature-deficient surfaces. The methodology significantly expands viable detection areas and enhances measurement reliability, accelerating practical implementations of metalens-enabled 3D imaging. |
| format | Article |
| id | doaj-art-88f9cd2b599c4ea0b65a7d0006a25e5b |
| institution | DOAJ |
| issn | 2948-216X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Nanophotonics |
| spelling | doaj-art-88f9cd2b599c4ea0b65a7d0006a25e5b2025-08-20T03:03:44ZengNature Portfolionpj Nanophotonics2948-216X2025-07-01211810.1038/s44310-025-00070-9High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusionYuzhou Song0Yifei Zhang1Xiaoyuan Liu2Takuo Tanaka3Mu Ku Chen4Zihan Geng5Institute of Data and Information, Tsinghua Shenzhen International Graduate School, Tsinghua UniversityInstitute of Data and Information, Tsinghua Shenzhen International Graduate School, Tsinghua UniversityDepartment of Electrical Engineering, City University of Hong KongInnovative Photon Manipulation Research Team, RIKEN Center for Advanced PhotonicsDepartment of Electrical Engineering, City University of Hong KongInstitute of Data and Information, Tsinghua Shenzhen International Graduate School, Tsinghua UniversityAbstract Three-dimensional (3D) imaging plays a crucial role in autonomous driving, medical diagnostics, and industrial inspection by providing comprehensive spatial information. Metalens-based 3D imaging is highly valued for imaging applications thanks to its compactness, with enhanced precision remaining a key research pursuit. Here, we present an integrated high-accuracy 3D imaging system combining binocular meta-lens with an optical clue fusion network. Our innovation lies in the synergistic fusion of physics-derived absolute stereo depth measurements and machine learning-estimated relative depth through adaptive confidence mapping - the latter effectively addressing the inherent limitations of absolute depth estimation in scenarios with insufficient matching features. This hybrid approach achieves unprecedented precision of depth estimation (error <1%) while maintaining robust performance across feature-deficient surfaces. The methodology significantly expands viable detection areas and enhances measurement reliability, accelerating practical implementations of metalens-enabled 3D imaging.https://doi.org/10.1038/s44310-025-00070-9 |
| spellingShingle | Yuzhou Song Yifei Zhang Xiaoyuan Liu Takuo Tanaka Mu Ku Chen Zihan Geng High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusion npj Nanophotonics |
| title | High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusion |
| title_full | High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusion |
| title_fullStr | High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusion |
| title_full_unstemmed | High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusion |
| title_short | High-precision three-dimensional imaging based on binocular meta-lens and optical clue fusion |
| title_sort | high precision three dimensional imaging based on binocular meta lens and optical clue fusion |
| url | https://doi.org/10.1038/s44310-025-00070-9 |
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