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- W4310588384 abstract "Metasurfaces, composed of two-dimensional arrays of subwavelength optical scatterers, are regarded as powerful substitutes to conventional diffractive and refractive optics. In addition, metasurfaces with powerful wavefront manipulation capabilities can steer the phase, amplitude, and polarization of light, which provides the potential to joint optimization with algorithms by encoding and decoding the light fields. In this paper, we propose an end-to-end computational imaging system which is joint optimized of metaoptics and neural networks based on the designed initial phase. We construct the forward model of the unit cell to the optical response and the inverse mapping of the optical response to the unit cell for the differentiable front-end metaoptics. Based on the appropriate initial phase, the calculation of the framework would converge faster, and the proposed system will promote the further development of metaoptics and computational imaging." @default.
- W4310588384 created "2022-12-12" @default.
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- W4310588384 date "2023-01-04" @default.
- W4310588384 modified "2023-09-25" @default.
- W4310588384 title "Inverse design of metasurfaces for end-to-end computational imaging" @default.
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- W4310588384 doi "https://doi.org/10.1117/12.2643799" @default.
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