NB-GTR: Narrow-Band Guided Turbulence Removal
Yifei Xia, Chu Zhou, Chengxuan Zhu, Minggui Teng, Chao Xu, Boxin Shi
Abstract
The removal of atmospheric turbulence is crucial for long-distance imaging. Leveraging the stochastic nature of atmospheric turbulence numerous algorithms have been developed that employ multi-frame input to mitigate the turbulence. However when limited to a single frame existing algorithms face substantial performance drops particularly in diverse real-world scenes. In this paper we propose a robust solution to turbulence removal from an RGB image under the guidance of an additional narrow-band image broadening the applicability of turbulence mitigation techniques in real-world imaging scenarios. Our approach exhibits a substantial suppression in the magnitude of turbulence artifacts by using only a pair of images thereby enhancing the clarity and fidelity of the captured scene.
BibTeX
@inproceedings{cvpr2024_nbgtrnarrowbandg,
title = {NB-GTR: Narrow-Band Guided Turbulence Removal},
author = {Yifei Xia and Chu Zhou and Chengxuan Zhu and Minggui Teng and Chao Xu and Boxin Shi},
booktitle = {CVPR 2024},
year = {2024}
}