Atmospheric Turbulence Removal with Video Sequence Deep Visual Priors

arXiv:2402.19041v1 Announce Type: new
Abstract: Atmospheric turbulence poses a challenge for the interpretation and visual perception of visual imagery due to its distortion effects. Model-based approaches have been used to address this, but such methods often suffer from artefacts associated with moving content. Conversely, deep learning based methods are dependent on large and diverse datasets that may not effectively represent any specific content. In this paper, we address these problems with a self-supervised learning method that does not require ground …

abstract arxiv challenge cs.ai cs.cv deep learning eess.iv effects interpretation moving perception turbulence type video visual