Night video enhancement using improved dark channel prior

Abstract

Videos taken under low lighting condition usually have serious loss of visibility and contrast and are inconvenient for observation and analysis. To solve this problem, this paper presents a real-time night video enhancement approach. As observed that a pixel-wise inversion of a night video has quite similar appearance with the video acquired at foggy days, we use the similar idea of haze removal method to enhance the perceptual quality of the night videos. We present an improved dark channel prior model and integrate it with local smoothing and image Gaussian Pyramid operators. The experimental results demonstrate that the proposed approach can improve the perceptual quality of night videos in real-time in terms of not only enhancing details, but also effectively avoiding excessive enhancement phenomenon.