Real-time enhancement of the image clarity for traffic video monitoring systems in haze

The images of outdoor scenes obtained in haze, fog and other weather days are usually have poor contrast and color fidelity. In this paper, in order to effectively improve the degraded image in haze quality, reduce the effect of the haze to outdoor traffic video monitoring systems, we analyzed the image degradation reason and fuzzy mechanism of image in haze. From the viewpoints of image restoration and image enhancement, an efficient and real-time image haze removal approach in view of the global dark-channel prior theory and image contract extending was proposed. Firstly, we used the global dark-channel prior method to remove the haze and fog, and then adopted the histogram equalization to enhance the contract and the brightness of images. The experimental results showed that the approach directly recovered a clear and quality haze-free image, obtained satisfactory visual effect. For the practical engineering applications, a high performance image acquisition, enhancement, haze removal and transmission platform was designed. It used the FPGA (field programmable gate array) as the core processer, and the algorithm proposed in this paper was implemented on the platform. The simulation result of timing sequence and the actual testing result were verified the reliability and validity of the method. Finally, through the actual test results indicated that the system can real-time, effectively enhance the image contrast and color definition of traffic video monitoring systems, thus it can improve its reliability, stability and the ability to cope with the bad weather such as the fog, haze and so on.