NB-GTR: Narrow-band guided turbulence removal

Yifei Xia

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.