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In this paper, we propose an advanced method to jointly optimize doublet metalens and deep learning-based postprocessing networks for wide-angle and full-color imaging with high fidelity. The optical image formation module in the spatially-variant system and a reconstruction network module are implemented in a differentiable manner. By premitigating coma aberration with doublet metalens, the proposed model outperforms both cases of singlet structure and analogous electronic implementations in terms of reconstruction accuracy.
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Yeongmyeong Park, Byoungho Lee, Yoonchan Jeong, "End-to-end optimization of meta-lens doublet for high-quality wide-angle imaging," Proc. SPIE 12646, Metamaterials, Metadevices, and Metasystems 2023, 126460D (4 October 2023); https://doi.org/10.1117/12.2677367