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/CVPR46437.2021.00906

Markdown

[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/CVPR46437.2021.00906

BibTeX

@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/}
}