Day color transfer based night video enhancement for surveillance system

A dark video captured during night surveillance is insufficient to recognize an action. In order to perform various video analysis operations, a night time video enhancement approach is required. A daytime coloring approach is proposed to improve the visual perception of night video. The day image is down sampled and its color features are applied to the night fusion video. The experimental results are compared with context enhancement fusion methods and objective metrics are used to evaluate the performance of the algorithm. The quality measures show that edge pixel strength and contrast of the surveillance videos are enhanced compared to other methods.