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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Bibliographic Details
Main Authors: Yuzhou Song, Yifei Zhang, Xiaoyuan Liu, Takuo Tanaka, Mu Ku Chen, Zihan Geng
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Nanophotonics
Online Access:https://doi.org/10.1038/s44310-025-00070-9
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Summary: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.
ISSN:2948-216X