TY - GEN
T1 - Removing Image Artifacts From Scratched Lens Protectors
AU - Wang, Yufei
AU - Wan, Renjie
AU - Yang, Wenhan
AU - Wen, Bihan
AU - Chau, Lap-Pui
AU - Kot, Alex
N1 - Funding Information:
This work was carried out at the Rapid-Rich Object Search (ROSE) Lab, Nanyang Technological University (NTU), Singapore. The research is supported in part by the NTU-PKU Joint Research Institute (a collaboration between the NTU and Peking University that is sponsored by a donation from the Ng Teng Fong Charitable Foundation) and in part by the Start- Up Grant and NTU-Imperial Collaboration Fund (INCF-2022-003). Renjie Wan is supported by the Blue Sky Research Fund of HKBU under Grant No. BSRF/21-22/16 and Guangdong Basic and Applied Basic Research Foundation under Grant No. 2022A1515110692.
PY - 2023/5/24
Y1 - 2023/5/24
N2 - A protector is placed in front of the camera lens for mobile devices to avoid damage, while the protector itself can be easily scratched accidentally, especially for plastic ones. The artifacts appear in a wide variety of patterns, making it difficult to see through them clearly. Removing image artifacts from the scratched lens protector is inherently challenging due to the occasional flare artifacts and the co-occurring interference within mixed artifacts. Though different methods have been proposed for some specific distortions, they seldom consider such inherent challenges. In our work, we consider the inherent challenges in a unified framework with two cooperative modules, which facilitate the performance boost of each other. We also collect a new dataset from the real world to facilitate training and evaluation purposes. The experimental results demonstrate that our method outperforms the baselines qualitatively and quantitatively. The code and datasets will be released after acceptance.
AB - A protector is placed in front of the camera lens for mobile devices to avoid damage, while the protector itself can be easily scratched accidentally, especially for plastic ones. The artifacts appear in a wide variety of patterns, making it difficult to see through them clearly. Removing image artifacts from the scratched lens protector is inherently challenging due to the occasional flare artifacts and the co-occurring interference within mixed artifacts. Though different methods have been proposed for some specific distortions, they seldom consider such inherent challenges. In our work, we consider the inherent challenges in a unified framework with two cooperative modules, which facilitate the performance boost of each other. We also collect a new dataset from the real world to facilitate training and evaluation purposes. The experimental results demonstrate that our method outperforms the baselines qualitatively and quantitatively. The code and datasets will be released after acceptance.
UR - https://confcats-event-sessions.s3.amazonaws.com/iscas23/uploads/ISCAS_2023_Program_Final.pdf
U2 - 10.48550/arXiv.2302.05746
DO - 10.48550/arXiv.2302.05746
M3 - Conference contribution
BT - IEEE International Symposium on Circuits and Systems (ISCAS) 2023
ER -