结合最小颜色通道图与传播滤波的单幅图像去雾算法研究

汤红忠; 张小刚; 朱玲; 陈华; 王翔; 李骁

doi:10.11959/j.issn.1000-436x.2017004

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结合最小颜色通道图与传播滤波的单幅图像去雾算法研究

学术论文 | 更新时间：2024-06-05

- 结合最小颜色通道图与传播滤波的单幅图像去雾算法研究
- Study of single image dehazing algorithm based on propagated filtering and minimum color channels
- 通信学报 2017年38卷第1期页码：26-34
- 作者机构：
  
  1. 湖南大学电气与信息工程学院，湖南长沙 410082
  2. 湘潭大学信息工程学院，湖南湘潭 411105
  3. 湘潭大学控制工程研究所，湖南湘潭 411105
  4. 湖南大学信息科学与工程学院，湖南长沙410082
- 作者简介：
  
  [ "汤红忠（1979-），女，湖南衡山人，湘潭大学副教授，湖南大学博士生，主要研究方向为图像处理与模式识别、字典学习及稀疏表示。" ]
  [ "张小刚（1972-），男，河南汝南人，湖南大学教授、博士生导师，主要研究方向为工业过程控制与模式识别。" ]
  [ "朱玲（1990-），女，湖南娄底人，湘潭大学硕士生，主要研究方向为图像处理与模式识别。" ]
  [ "陈华（1974-），女，广东五华人，湖南大学讲师、硕士生导师，主要研究方向为图像处理与模式识别。" ]
  [ "王翔（1991-），男，湖南衡阳人，湘潭大学硕士生，主要研究方向为图像处理与模式识别。" ]
  [ "李骁（1993-），男，湖南临湘人，湘潭大学硕士生，主要研究方向为图像处理与模式识别。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61573299);国家自然科学基金资助项目(61673162);国家自然科学基金资助项目(61672216);国家自然科学基金资助项目(61602397);湖南省教育厅基金资助项目(15C1328)
- DOI：10.11959/j.issn.1000-436x.2017004
  中图分类号： TP391.4
- 网络出版日期：2017-01，
  
  纸质出版日期：2017-01-25
- 稿件说明：
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汤红忠, 张小刚, 朱玲, 等. 结合最小颜色通道图与传播滤波的单幅图像去雾算法研究[J]. 通信学报, 2017,38(1):26-34.

Hong-zhong TANG, Xiao-gang ZHANG, Ling ZHU, et al. Study of single image dehazing algorithm based on propagated filtering and minimum color channels[J]. Journal on communications, 2017, 38(1): 26-34.
汤红忠, 张小刚, 朱玲, 等. 结合最小颜色通道图与传播滤波的单幅图像去雾算法研究[J]. 通信学报, 2017,38(1):26-34. DOI： 10.11959/j.issn.1000-436x.2017004.

Hong-zhong TANG, Xiao-gang ZHANG, Ling ZHU, et al. Study of single image dehazing algorithm based on propagated filtering and minimum color channels[J]. Journal on communications, 2017, 38(1): 26-34. DOI： 10.11959/j.issn.1000-436x.2017004.

摘要

针对单幅图像去雾中边缘区域去雾不彻底及黑斑现象，提出了一种结合最小颜色通道图与传播滤波的图像去雾算法。该方法首先基于双区域滤波实现大气透射率的初始估计，然后引入最小颜色通道图作为参考图像，采用传播滤波优化初始透射率，优化后的透射图因与参考图像具有相似的边缘特性，能有效避免图像景深突变边缘像素点透射率估值出现偏差的问题，同时去除了初始透射图中冗余的纹理信息，最后利用L-BFGS自适应恢复大气光矢量，基于大气散射模型复原无雾图像。实验结果表明，所提算法对图像景深突变边缘具有更为精确的透射率估算值，能有效保持边缘和细节，图像景深均匀区域具有较好的空间平滑特性，复原后的图像具有较高清晰度和丰富色彩度。

Abstract

To solve the challenging problem that the edge regions of image have some remained hazes and blackspots

a novel image dehazing algorithm was proposed based on the minimal color channel and propagated filtering.Firstly

an initial atmospheric transmission map was obtained by double-area filtering

then a minimal channel color was introduced as a reference image

and the propagated filtering was combined to optimize the initial atmospheric transmission map.Optimized transmission have the similar edge characteristics as the referenced image

so the deviation of transmission estimation can be effectively avoided for the edge pixels in the depth mutated regions

and the redundant texture information were removed in the initial transmission map.Finally

L-BFGS was used to restore atmospheric light

and the haze-free image can be recovered based on the atmospheric scattering model.Experimental results show that proposed algorithm has the more accurate transmission estimation for the depth mutated edge regions of image

so the recovered image effectively preserves the edges and details in the depth mutated regions

and has better spatial smoothness in the uniform depth regions.The recovered haze-free image with proposed method has a better sharpness and richer color degree.

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references

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