Poster + Paper
4 January 2023 Inverse design of metasurfaces for end-to-end computational imaging
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Conference Poster
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.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qiangbo Zhang, Zeqing Yu, Xinyu Liu, Yang Zhang, Zhou Xu, Chang Wang, and Zhengrong Zheng "Inverse design of metasurfaces for end-to-end computational imaging", Proc. SPIE 12317, Optoelectronic Imaging and Multimedia Technology IX, 123170V (4 January 2023); https://doi.org/10.1117/12.2643799
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KEYWORDS
Computational imaging

Imaging systems

Image restoration

Neural networks

Nano optics

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