Metasurface-based computational imaging: a review

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.