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Optical corner detection with azimuthal Hilbert transform metasurfaces
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DOI：10.1126/sciadv.aed8301.png)
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Abstract
En 中文
Many animals efficiently interpret their environment by detecting geometric features like corners, highlighting the power of feature extraction for reducing visual complexity; similarly, with the surge in visual data, nature-inspired optical corner detection offers a promising yet still elusive solution for energy-efficient information processing and compression. Here, we propose a universal strategy for optical corner imaging with azimuthal Hilbert transformation metasurfaces. Multiple objects, regardless of their amplitude, phase, or angular characteristics, can be detected simultaneously with a single metasurface, featuring broadband and full–field-of-view properties. Trade-offs between spatial and angular resolution are assessed, offering practical guidance for implementation. We further demonstrate motion tracking as a proof-of-concept application leveraging the data-compressed corner imaging framework. This work paves the way for next-generation optical information processing technologies.
Keywords:
optical corner detection
azimuthal Hilbert transform
metasurfaces
feature extraction
motion tracking
Journal
IF:
12.5
Papers:
2.0W
Citations:
18.1W