Xuemei Hu 1,2Weizhu Xu 1,2Qingbin Fan 1,2Tao Yue 1,2[ ... ]Ting Xu 1,3,*
Author Affiliations
Abstract
1 Nanjing University, Collaborative Innovation Center of Advanced Microstructures, National Laboratory of Solid-State Microstructures, Nanjing, China
2 Nanjing University, School of Electronic Sciences and Engineering, Nanjing, China
3 Nanjing University, College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing, China
Metasurface-based imaging has attracted considerable attention owing to its compactness, multifunctionality, and subwavelength coding capability. With the integration of computational imaging techniques, researchers have actively explored the extended capabilities of metasurfaces, enabling a wide range of imaging methods. We present an overview of the recent progress in metasurface-based imaging techniques, focusing on the perspective of computational imaging. Specifically, we categorize and review existing metasurface-based imaging into three main groups, including (i) conventional metasurface design employing canonical methods, (ii) computation introduced independently in either the imaging process or postprocessing, and (iii) an end-to-end computation-optimized imaging system based upon metasurfaces. We highlight the advantages and challenges associated with each computational metasurface-based imaging technique and discuss the potential and future prospects of the computational boosted metaimager.
metasurface computational imaging inverse problem algorithm 
Advanced Photonics
2024, 6(1): 014002

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