1. 54‐1: Development of UDC Image Restoration Technology Using Space Variant CNN.
- Author
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Kim, Daewook, Cho, Jaebum, Yoo, Jewon, Hwang, Hyunjoo, Park, Sungjae, Baek, Seungin, and Cho, Sungchan
- Subjects
CONVOLUTIONAL neural networks ,IMAGE reconstruction ,IMAGE processing ,DEEP learning ,PHOTOGRAPHIC lenses - Abstract
With the continuous evolution of mobile device technologies, the integration of under‐display cameras has emerged as a groundbreaking innovation in the pursuit of bezel‐less and immersive visual experiences. As this technology becomes increasingly prevalent, it introduces a unique set of challenges, particularly in the realm of photography. In particular, the flare cannot be restored by conventional image processing due to saturated pixels. Therefore, a deep learning network capable of restoring such deterioration is proposed. The network is trained by a synthetic datasets generated by accurate optical simulation. However, the distortion of the camera lens distorts the shape of flare differently depending on its position in the photo, and it degrades restore quality. In this paper, we propose space‐variant CNN for solving distortion problem. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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