Broadband Achromatic Imaging of a Metalens with Optoelectronic Computing Fusion
Wei Cheng, Yan Wang, Yan Wang, Yuqing Zhang, Huan Chen, Zhechun Lu, Fen Zhao, Yaohua Wang, Yaohua Wang, Jiagui Wu, Junbo Yang
Abstract
The remarkable ultrathin ability of metalenses gives them potential as a next-generation imaging candidate. However, the inherent chromatic aberration of metalenses restricts their widespread application. We present an achromatic metalens with optoelectronic computing fusion (OCF) to mitigate the impact of chromatic aberration and simultaneously avoid the significant challenges of nanodesign, nanofabrication, and mass production of metalenses, a method different from previous methods. Leveraging the nonlinear fitting, we demonstrate that OCF can effectively learn the chromatic aberration mapping of metalens and thus restore the chromatic aberration. In terms of the peak signal-to-noise ratio index, there is a maximum improvement of 12 dB, and ∼8 ms is needed to correct the chromatic aberration. Furthermore, the edge extraction of images and super-resolution reconstruction that effectively enhances resolution by a factor of 4 are also demonstrated with OCF. These results offer the possibility of applications of metalenses in mobile cameras, virtual reality, etc.