Nighttime Image Fog Removal Based on Statistical Properties and Intensity Estimation

被引：1
|
作者：
Yang A. [1 ]
Yang S. [1 ]
Tian X. [1 ]
Zhao M. [1 ]
Wang J. [1 ]
机构：
[1] School of Electrical and Information Engineering, Tianjin University, Tianjin
来源：
Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology | 2018年 / 51卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Defogging; Intensity estimation; Local Grey-world; Statistical characteristics;
D O I：
10.11784/tdxbz201703004
中图分类号：
学科分类号：
摘要：
Due to the existence of artificial light, nighttime fog image has the characteristics of non-uniform illumination, color cast and low intensity. The existing image dehazing algorithms are not applicable. Considering the character of nighttime hazy images, a new imaging model for hazy image based on color cast factor was established, which is suitable for defogging of nighttime hazy image. Then the nighttime image dehazing algorithm was proposed based on the statistical properties of nighttime hazy images and the estimation of image intensity. Because of the similarity between the intensity histogram of nighttime hazy images and low light images, the nighttime hazy image was inverted firstly, and then the atmosphere light with color cast factor was estimated locally based on the proposed model. As a resultt of color cast, the three channel transmissions have significant differences, so three channel transmissions were estimated respectively. At last, the transmission was optimized based on the intensity estimation, and the color cast correction was performed using local Grey-world algorithm. Experimental results show that the proposed algorithm can remove nighttime haze effectively, and at the same time the brightness, contrast and image details are improved remarkably. © 2018, Editorial Board of Journal of Tianjin University(Science and Technology). All right reserved.
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收藏
页码：299 / 307
页数：8
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