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4-K-resolution minimalist optical system design based on deep learning

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Abstract

In order to simplify optical systems, we propose a high-resolution minimalist optical design method based on deep learning. Unlike most imaging system design work, we combine optical design more closely with image processing algorithms. For optical design, we separately study the impact of different aberrations on computational imaging and then innovatively propose an aberration metric and a spatially micro-variant design method that better meet the needs of image recognition. For image processing, we construct a dataset based on the point spread function (PSF) imaging simulation method. In addition, we use a non-blind deblurring computational imaging method to repair spatially variant aberrations. Finally, we achieve clear imaging at 4 K ($5184 \times 3888$) using only two spherical lenses and achieve image quality similar to that of complex lenses on the market.

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Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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