Author:
Dong Tianyang,Zhao Guoqing,Wu Jiamin,Ye Yang,Shen Ying
Abstract
In order to restore traffic videos with different degrees of haziness in a real-time and adaptive manner, this paper presents an efficient traffic video dehazing method using adaptive dark channel prior and spatial-temporal correlations. This method uses a haziness flag to measure the degree of haziness in images based on dark channel prior. Then, it gets the adaptive initial transmission value by establishing the relationship between the image contrast and haziness flag. In addition, this method takes advantage of the spatial and temporal correlations among traffic videos to speed up the dehazing process and optimize the block structure of restored videos. Extensive experimental results show that the proposed method has superior haze removing and color balancing capabilities for the images with different degrees of haze, and it can restore the degraded videos in real time. Our method can restore the video with a resolution of 720 × 592 at about 57 frames per second, nearly four times faster than dark-channel-prior-based method and one time faster than image-contrast-enhanced method.
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
26 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献