Paper Title
Removal of Fog From Video

Abstract
Applications such as autonomous driving and surveillance are restricted by the inability of existing video dehazing techniques to adjust to changing environments. This article proposes a systematic approach for enhancing video clarity in foggy conditions. The method involves selecting a reference frame, adjusting its V channel in the HSV color space, and using it as a bench mark for the next few subsequent frames. Through frame-by-frame processing, a kernel derived from the reference frame is applied to mitigate haze effects across the video sequence. This strategy ensures consistent dehazing, progressively improving visual quality. Whilefurther optimizations are possible, The method shows promise in addressing the challenge of video dehazing and advancing video processing capabilities in adverse weather conditions. Readers interested in efficient, real-time video dehazing techniques may find this approach valuable. Keywords - Video Defogging, Frame, Subsampling, Visual Quality, Dehazing, Fog, Haze