Image Restoration for Under-Display Camera
Abstract
The new trend of full-screen devices encourages us to position a camera behind a screen. Removing the bezel and centralizing the camera under the screen brings larger display-to-body ratio and enhances eye contact in video chat, but also causes image degradation. In this paper, we focus on a newly-defined Under-Display Camera (UDC), as a novel real-world single image restoration problem. First, we take a 4k Transparent OLED (T-OLED) and a phone Pentile OLED (P-OLED) and analyze their optical systems to understand the degradation. Second, we design a Monitor-Camera Imaging System (MCIS) for easier real pair data acquisition, and a model-based data synthesizing pipeline to generate Point Spread Function (PSF) and UDC data only from display pattern and camera measurements. Finally, we resolve the complicated degradation using deconvolution-based pipeline and learning-based methods. Our model demonstrates a real-time high-quality restoration. The presented methods and results reveal the promising research values and directions of UDC.
Cite
Text
Zhou et al. "Image Restoration for Under-Display Camera." Conference on Computer Vision and Pattern Recognition, 2021. doi:10.1109/CVPR46437.2021.00906Markdown
[Zhou et al. "Image Restoration for Under-Display Camera." Conference on Computer Vision and Pattern Recognition, 2021.](https://mlanthology.org/cvpr/2021/zhou2021cvpr-image-a/) doi:10.1109/CVPR46437.2021.00906BibTeX
@inproceedings{zhou2021cvpr-image-a,
title = {{Image Restoration for Under-Display Camera}},
author = {Zhou, Yuqian and Ren, David and Emerton, Neil and Lim, Sehoon and Large, Timothy},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2021},
pages = {9179-9188},
doi = {10.1109/CVPR46437.2021.00906},
url = {https://mlanthology.org/cvpr/2021/zhou2021cvpr-image-a/}
}