Metaoptic Computational Imaging
Charles Roques‐Carmes, Kai Wang, Yuanmu Yang, Arka Majumdar, Zin Lin
Abstract
Metasurfaces, ultrathin structures composed of subwavelength optical elements, have revolutionized light manipulation by enabling precise control over electromagnetic waves’ amplitude, phase, polarization, and spectral properties. Concurrently, computational imaging leverages algorithms to reconstruct images from optically processed signals, overcoming the limitations of traditional imaging systems. This Perspective explores the synergistic integration of metaoptics and computational imaging, “metaoptic computational imaging”, which combines the physical wavefront shaping ability of metasurfaces with advanced computational algorithms to enhance imaging performance beyond conventional limits. We discuss how metaoptic computational imaging addresses the inherent limitations of single-layer metasurfaces in achieving multifunctionality without compromising efficiency. By treating metasurfaces as physical preconditioners and codesigning them with reconstruction algorithms through end-to-end (inverse) design, it is possible to jointly optimize the optical hardware and computational software. Advanced applications and new frontiers in the field enabled by metaoptic computational imaging are highlighted, including phase imaging and quantum state measurement.