[1]刘翠响,张莎,王宝珠,等.航拍图像去雾优化算法研究[J].深圳大学学报理工版,2018,35(5):516-522.[doi:10.3724/SP.J.1249.2018.05516]
 LIU Cuixiang,ZHANG Sha,WANG Baozhu,et al.Optimization algorithm of aerial image dehazing[J].Journal of Shenzhen University Science and Engineering,2018,35(5):516-522.[doi:10.3724/SP.J.1249.2018.05516]
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航拍图像去雾优化算法研究()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第35卷
期数:
2018年第5期
页码:
516-522
栏目:
电子与信息科学
出版日期:
2018-09-25

文章信息/Info

Title:
Optimization algorithm of aerial image dehazing
作者:
刘翠响张莎王宝珠袁香伟
河北工业大学电子信息工程学院,天津 300401
Author(s):
LIU Cuixiang ZHANG Sha WANG Baozhu and YUAN Xiangwei
School of Electronic and Information Engineering, Hebei University of Technology, Tianjin 300401, P.R.China
关键词:
图像处理航拍图像去雾暗通道四叉树快速导向滤波多尺度Retinex直方图去雾
Keywords:
image processing aerial image dehazing dark channel quadtree fast guided filter multiscale Retinex histogram defogging
分类号:
TN 911.7
DOI:
10.3724/SP.J.1249.2018.05516
文献标志码:
A
摘要:
为优化航拍图像的去雾算法,提出基于暗通道规律的快速去雾、四叉树子空间划分层次搜索算法和快速导向滤波整合处理的方式进行去雾优化,发现相比单一原算法,该算法的复杂度被大幅降低,同时提高了图像清晰度.通过研究不同算法的图像处理发现,单独使用某一算法只能优化图像的某一方面,整体效果不明显,而采用这3种优化算法综合处理航拍有雾图像,清晰度至少提高11.57%,峰值信噪比至少增加1.88%,耗时比单一优化算法缩短了至少37.49%,不仅去雾效果好且实时性高.分别对雨天和雪天情况下的雾气图像进行实验分析,结果证明,该综合算法对雨天和雪天的有雾航拍图像同样有效.分别采用多尺度Retinex算法、直方图去雾算法和本研究提出的综合去雾算法对航拍有雾图像进行去雾处理,本算法清晰度高,更适合航拍图像.
Abstract:
In order to study optimization algorithm of aerial image dehazing, we propose a combined defogging method based on three optimization algorithms, including a rapid defog based on dark channel, the use of a hierarchical search method based on quadtree subspace to optimize the acquisition of atmospheric light, and optimizing the transmission based on the fast-directed filtering. We find that our algorithm can greatly reduce the complexity compared to a single original algorithm and improve the image clarity. By studying the image processing of different algorithms, we find that the use of only one of the three algorithms alone can only optimize the characteristics of a certain aspect of image, and the effect is not obvious. But using these three optimization algorithms to simultaneously process aerial foggy images, the resolution is improved by at least 11.57%, the peak signal-to-noise ratio is increased by at least 1.88%, and the time is at least 37.49% shorter than a single optimization algorithm, that is, the defogging effect is good and the real-time performance is high. At the same time, to verify the feasibility and universality of the research algorithm, we analyze the fog images in rainy and snowy days experimentally. We also compare the results of our combined defogging algorithm to those of the multi-scale Retinex algorithm and histogram dehazing algorithm to verify the applicability of the algorithm. The experimental results show that the proposed algorithm has wide applicability.

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更新日期/Last Update: 2018-08-21