Multispectral Scattering Imaging Based on Metasurface Diffuser and Deep Learning. Issue 2 (2nd December 2021)

• Record Type: Journal Article
• Authors: Lei, Yunsong; Guo, Yinghui; Pu, Mingbo; He, Qiong; Gao, Ping; Li, Xiong; Ma, Xiaoliang; Luo, Xiangang
• Is Part Of: Physica status solidi. Volume 16:Issue 2(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-02
• Subjects: computational imaging -- deep learning -- metasurface diffusers -- multispectral imaging; Solid state physics -- Periodicals; 530.4105
• DOI: 10.1002/pssr.202100469
• Languages: English
• ISSNs: 1862-6254

Abstract

Abstract : Multispectral imaging plays an essential role in applications from biomedical imaging to remote sensing since it records rich spectral and spatial information. Nevertheless, conventional multispectral imaging systems generally suffer from complicated optical systems and compromise between spectral, spatial, and temporal resolution. Multispectral scattering imaging has recently drawn considerable attention due to its simple setup and unique methodology to solve the aforementioned bottlenecks. Herein, multispectral scattering imaging based on metasurface diffuser and deep learning is proposed. Prior knowledge of the metasurface diffuser's wavefront will avoid the time‐consuming characterization required in conventional scattering media, and a well‐trained deep learning algorithm can realize real‐time image reconstruction. With these merits, this method may push the development of metasurface applications and multispectral imaging. Abstract : The design and fabrication of multispectral scattering imaging based on a metasurface diffuser and deep learning are presented. This technology is essential for many imaging applications in bioscience, advanced sensing, and virtual reality. Deep learning is also used to achieve real‐time image reconstruction, enabling the balance between the spectral, spatial, and temporal resolutions for the multispectral imaging.