Nighttime Haze Removal Based on New Imaging Model with Artificial Light Sources

The non-uniform illumination, low brightness, serious color deviation and halo effects around artificial light sources lead to the difficulty in haze removal for night-time image. The existing dehazing methods are mostly designed for daytime image and not applicable to nighttime image. This paper focuses on researching nighttime image dehazing. A new nighttime haze model that accounts for the artificial varying light sources is introduced. Based on this new model, a new dehazing framework is proposed. Firstly, the atmospheric light is estimated based on the low pass filter method. This atmospheric light map can be used to predict the transmission of night scene accurately. Secondly, to solve the problem of halo effects around artificial light sources in existing dehazing methods, a method that estimates the distance between the object of the scene and the artificial light sources based on the image chromaticity is proposed. In this way, the scene objects near to the light source region and objects far away from the light source region can be processed respectively. Finally, as for the color cast, an efficient color correction algorithm based on the histogram matching is presented in this paper. Comparing with existing daytime and nighttime dehazing methods, the experimental results of a number of examples demonstrate the effectiveness of the proposed night-time haze model and the dehazing method.