Abstract
Video defogging is a process that aims to improve the visibility and quality of video captured in foggy or hazy conditions. It involves several steps, including analyzing the captured video, estimating the amount of fog or haze in each frame, and applying algorithms to remove or reduce the effect of fog or haze. There are various techniques used for video defogging, such as image fusion, dark channel prior, and atmospheric scattering models. Image fusion involves combining multiple images of the same scene to create a clear image, while dark channel prior exploits statistical regularities to estimate the haze layer. Atmospheric scattering models use light scattering properties in the atmosphere to estimate the amount of haze. Video defogging has numerous applications, including surveillance, traffic monitoring, and outdoor video recording. It can improve the visibility of captured video, making it easier to identify objects and events in the scene.
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