The paper "Metasurface-based computational imaging: a review" by Xuemei Hu et al. provides an overview of recent advancements in metasurface-based imaging techniques, focusing on computational imaging. Metasurfaces, composed of subwavelength nanostructures, offer compactness, multifunctionality, and subwavelength coding capabilities, making them suitable for various imaging applications. The authors categorize existing metasurface-based imaging techniques into three main groups: conventional metasurface design, computation introduced independently in the imaging process or post-processing, and end-to-end computation-optimized systems. They highlight the advantages and challenges of each category and discuss the potential and future prospects of computational boosted metaimagers. The paper begins with an introduction to metasurfaces and their potential in imaging, emphasizing the challenges of nonidealities and the need for scalable imaging frameworks. Computational imaging, which integrates computational techniques into the imaging and reconstruction processes, is then discussed, highlighting its ability to enhance imaging capabilities and expand observation dimensions. The review section delves into specific metasurface-based computational imaging methodologies, including spectrum, polarization, depth, and compound modulation. For spectrum modulation, the paper covers achromatic and hyperspectral imaging, detailing methods such as canonical phase mask designs and inverse design approaches. Polarization modulation is explored through polarization multiplexing, routing, and filtering, with examples like polarization multiplexing for extreme depth imaging and polarization routing for full-Stokes imaging. Depth and angle modulation techniques, such as PSF engineering and wide-angle modulation, are discussed, including methods like double-helix phase profiles and synthetic aperture methods. Compound modulation, which involves coordinated manipulation of multiple light field dimensions, is also covered, with examples like angle-spectrum modulation and color routing. The paper concludes by addressing the primary challenges in building metasurface-based computational imaging systems and discussing future research directions, emphasizing the potential of metasurfaces in advancing computational imaging and nanophotonics.The paper "Metasurface-based computational imaging: a review" by Xuemei Hu et al. provides an overview of recent advancements in metasurface-based imaging techniques, focusing on computational imaging. Metasurfaces, composed of subwavelength nanostructures, offer compactness, multifunctionality, and subwavelength coding capabilities, making them suitable for various imaging applications. The authors categorize existing metasurface-based imaging techniques into three main groups: conventional metasurface design, computation introduced independently in the imaging process or post-processing, and end-to-end computation-optimized systems. They highlight the advantages and challenges of each category and discuss the potential and future prospects of computational boosted metaimagers. The paper begins with an introduction to metasurfaces and their potential in imaging, emphasizing the challenges of nonidealities and the need for scalable imaging frameworks. Computational imaging, which integrates computational techniques into the imaging and reconstruction processes, is then discussed, highlighting its ability to enhance imaging capabilities and expand observation dimensions. The review section delves into specific metasurface-based computational imaging methodologies, including spectrum, polarization, depth, and compound modulation. For spectrum modulation, the paper covers achromatic and hyperspectral imaging, detailing methods such as canonical phase mask designs and inverse design approaches. Polarization modulation is explored through polarization multiplexing, routing, and filtering, with examples like polarization multiplexing for extreme depth imaging and polarization routing for full-Stokes imaging. Depth and angle modulation techniques, such as PSF engineering and wide-angle modulation, are discussed, including methods like double-helix phase profiles and synthetic aperture methods. Compound modulation, which involves coordinated manipulation of multiple light field dimensions, is also covered, with examples like angle-spectrum modulation and color routing. The paper concludes by addressing the primary challenges in building metasurface-based computational imaging systems and discussing future research directions, emphasizing the potential of metasurfaces in advancing computational imaging and nanophotonics.