Study of visibility enhancement of hazy images based on dark channel prior in polarimetric imaging

被引:18
|
作者
Zhang, Wenfei [1 ,2 ,3 ]
Liang, Jian [1 ,3 ]
Ju, Haijuan [1 ,3 ]
Ren, Liyong [1 ]
Qu, Enshi [1 ]
Wu, Zhaoxin [2 ]
机构
[1] Chinese Acad Sci, Res Dept Informat Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
[2] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Dept Elect Sci & Technol, Xian 710049, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源
OPTIK | 2017年 / 130卷
基金
中国国家自然科学基金;
关键词
Image enhancement; Polarimetric imaging; Scattering; Visibility and imaging;
D O I
10.1016/j.ijleo.2016.11.047
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
During past decades, lots of efforts on image dehazing have been made based on either computer vision or physical models. In this paper, based on the combination of the polarimetric imaging and the dark channel prior techniques, we propose a novel haze-removal method. On the one hand, the former technique ensures this method has the advantage of keeping the detailed information which might be almost vanished in hazy images; on the other hand, the latter technique provides a much easier way to precisely estimate the key parameters, such as the global atmospheric light and the degree of polarization of the airlight. Moreover, in order to realize the automatically dehazing process with our method, a dynamic bias factor is creatively introduced into the dehazing process by use of the evaluation function Entropy, ensuring excellent dehazed image being automatically obtained while not involving any other human-computer interaction. Experimental results indicate that our dehazing method can not only enhance the visibility of the hazy images effectively, but also preserve the details considerably. In addition, it is also found that this method is useful and effective for thin, medium and dense haze conditions, and thus shows a good robustness and universality. (C) 2016 Elsevier GmbH. All rights reserved.
引用
收藏
页码:123 / 130
页数:8
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