Universal strategy for surveillance video defogging

Abstract

We present a new approach to remove haze from surveillance video sequences. This approach extracts the background image through the frame differential method, uses the dark channel prior to estimate the atmospheric light, and then calculates a universal transmission map on the intensity component of the background image through a process of multiscale retinex, parameter adjustment, bilateral filtering, and total variation denoising filtering. Finally, it renders haze-free video according to the haze image model. The main advantage of the proposed approach is its speed as this approach adopts a "universal strategy" that applies the same atmospheric light and a universal pseudo-transmission map to a series of video frames. Experiments demonstrate that our method produces visually pleasing defogging results and tends to preserve main details better than previous techniques. A comparative study and quantitative evaluation show the efficiency of the proposed method.