Single-layer spatial analog meta-processor for imaging processing - Université Paris Nanterre Access content directly
Journal Articles Nature Communications Year : 2022

Single-layer spatial analog meta-processor for imaging processing

Zhuochao Wang
  • Function : Author
Guangwei Hu
Xinwei Wang
  • Function : Author
Xumin Ding
Kuang Zhang
Haoyu Li
Qun Wu
  • Function : Author
Jian Liu
  • Function : Author
Jiubin Tan
  • Function : Author
Cheng-Wei Qiu


Abstract Computational meta-optics brings a twist on the accelerating hardware with the benefits of ultrafast speed, ultra-low power consumption, and parallel information processing in versatile applications. Recent advent of metasurfaces have enabled the full manipulation of electromagnetic waves within subwavelength scales, promising the multifunctional, high-throughput, compact and flat optical processors. In this trend, metasurfaces with nonlocality or multi-layer structures are proposed to perform analog optical computations based on Green’s function or Fourier transform, intrinsically constrained by limited operations or large footprints/volume. Here, we showcase a Fourier-based metaprocessor to impart customized highly flexible transfer functions for analog computing upon our single-layer Huygens’ metasurface. Basic mathematical operations, including differentiation and cross-correlation, are performed by directly modulating complex wavefronts in spatial Fourier domain, facilitating edge detection and pattern recognition of various image processing. Our work substantiates an ultracompact and powerful kernel processor, which could find important applications for optical analog computing and image processing.
Fichier principal
Vignette du fichier
s41467-022-29732-4.pdf (5.2 Mo) Télécharger le fichier
Origin : Publication funded by an institution

Dates and versions

hal-04177630 , version 1 (15-01-2024)



Zhuochao Wang, Guangwei Hu, Xinwei Wang, Xumin Ding, Kuang Zhang, et al.. Single-layer spatial analog meta-processor for imaging processing. Nature Communications, 2022, 13 (1), pp.2188. ⟨10.1038/s41467-022-29732-4⟩. ⟨hal-04177630⟩
7 View
4 Download



Gmail Facebook X LinkedIn More