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基于最小值通道与对数衰减的图像融合去雾算法

杨燕 张得欣 岳辉

杨燕, 张得欣, 岳辉等 . 基于最小值通道与对数衰减的图像融合去雾算法[J]. 北京航空航天大学学报, 2020, 46(10): 1844-1852. doi: 10.13700/j.bh.1001-5965.2019.0552
引用本文: 杨燕, 张得欣, 岳辉等 . 基于最小值通道与对数衰减的图像融合去雾算法[J]. 北京航空航天大学学报, 2020, 46(10): 1844-1852. doi: 10.13700/j.bh.1001-5965.2019.0552
YANG Yan, ZHANG Dexin, YUE Huiet al. Image fusion dehazing algorithm based on minimum channel and logarithmic attenuation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(10): 1844-1852. doi: 10.13700/j.bh.1001-5965.2019.0552(in Chinese)
Citation: YANG Yan, ZHANG Dexin, YUE Huiet al. Image fusion dehazing algorithm based on minimum channel and logarithmic attenuation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(10): 1844-1852. doi: 10.13700/j.bh.1001-5965.2019.0552(in Chinese)

基于最小值通道与对数衰减的图像融合去雾算法

doi: 10.13700/j.bh.1001-5965.2019.0552
基金项目: 

国家自然科学基金 61561030

甘肃省财政厅基本科研业务费 214138

兰州交通大学教改项目 160012

详细信息
    作者简介:

    杨燕  女,博士,教授,硕士生导师。主要研究方向:数字图像处理、智能信息处理等

    张得欣  女,硕士研究生。主要研究方向:数字图像处理

    岳辉  男,硕士,副教授,硕士生导师。主要研究方向:数字图像处理

    通讯作者:

    杨燕. E-mail:1275022532@qq.com

  • 中图分类号: TP391.4

Image fusion dehazing algorithm based on minimum channel and logarithmic attenuation

Funds: 

National Natural Science Foundation of China 61561030

Research Fund of Department of Finance of Gansu Province 214138

Research Fund of Teaching Reform Project of Lanzhou Jiaotong University 160012

More Information
  • 摘要:

    雾天各类图像采集系统获取的图像颜色退化,细节模糊,严重影响户外成像系统的稳定性和有效性,因此研究图像去雾技术很有必要。针对暗通道一类去雾算法边缘去雾不彻底问题,提出一种基于最小值通道与对数衰减的融合去雾算法。首先,对有雾图像的最小值通道图进行对数衰减作为先验假设条件,再进行交叉双边滤波消除纹理效应,在操作前后分别进行下采样和上采样操作以提高运算速度,求出初始透射率;然后,用Canny算子检测最小值通道图得到的边缘进行对数衰减,得到边缘信息图,将初始透射率与边缘信息图进行加权融合构成优化透射率;最后,结合改进的四叉树搜索法求得的大气光值反解大气散射模型,恢复无雾图像。实验结果表明:所提算法可以有效抑制光晕现象,去除边缘残雾,且实时性好。

     

  • 图 1  文献[9]去雾过程

    Figure 1.  Dehazing process of Ref.[9]

    图 2  暗通道先验对含大片天空区域图像的处理效果

    Figure 2.  Dehazing results of dark channel prior when hazy images have a large amount of bright area

    图 3  本文算法原理框图

    Figure 3.  Schematic block diagram of proposed algorithm

    图 4  暗通道与对数衰减暗通道实验对比

    Figure 4.  Experimental comparison between dark channel and logarithmic attenuated dark channel

    图 5  本文算法与文献[9]算法去雾效果对比

    Figure 5.  Comparison of dehazing result between proposed algorithm and algorithm in Ref.[9]

    图 6  image1去雾效果对比

    Figure 6.  Comparison of image1 dehazing effect

    图 7  image2去雾效果对比

    Figure 7.  Comparison of image2 dehazing effect

    图 8  image3去雾效果对比

    Figure 8.  Comparison of image3 dehazing effect

    图 9  image4去雾效果对比

    Figure 9.  Comparison of image4 dehazing effect

    图 10  image5去雾效果对比

    Figure 10.  Comparison of image5 dehazing effect

    图 11  客观评价实验结果

    Figure 11.  Experimental results with objective evaluation

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出版历程
  • 收稿日期:  2019-10-23
  • 录用日期:  2020-01-27
  • 网络出版日期:  2020-10-20

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