计算机与现代化

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一种改进的基于暗通道先验的图像去雾算法

  

  1. (1.上海农林职业技术学院农业信息工程系,上海201699;2.海南医学院医学信息系,海南海口571199)
  • 收稿日期:2018-06-26 出版日期:2019-02-25 发布日期:2019-02-26
  • 作者简介:包斌(1973-),男,河南信阳人,讲师,硕士,研究方向:图像处理,数据库及应用,E-mail: baobin_bb@163.com; 李亚岗(1971-),男,河南襄城人,副教授,硕士,研究方向:图像处理,数据库及应用,E-mail: liyagang@163.com。
  • 基金资助:
    上海农林职业技术学院自然科学基金资助项目(KY1-0000-16-03)

An Improved Image Dehazing Algorithm Based on Dark Channel Prior

  1. (1. Department of Agricultural Information Engineering, Shanghai Vocational College of Agriculture and Forestry,
    Shanghai 201699, China; 2. Department of Medical Informatics, Hainan Medical University, Haikou 571199, China)
  • Received:2018-06-26 Online:2019-02-25 Published:2019-02-26

摘要: 针对暗通道先验去雾算法在图像灰白色或天空区域会产生颜色畸变及图像比较暗淡的问题,提出一种基于暗通道先验改进的算法。该算法通过修正导致颜色畸变的透射率计算问题,从而提高图像的视觉效果。同时,通过降低3个颜色通道的高亮度值,并采用均值方法来得到增强的无雾图像。实验结果表明,本文方法在很大程度上消除了去雾图像明亮区域的颜色畸变现象且有更好的颜色恢复度。

关键词: 图像去雾, 暗通道先验, 颜色通道, 图像增强, 大气散射模型

Abstract: Aiming at the problem that the dark channel prior image dehazing algorithm produces color distortion and dim image in offwhite scenery or bright sky, an improved method based on dark channel prior is proposed. By correcting the computing problem of transmission rate which causes color distortion, the visual effect of the image can be improved. In addition, an enhanced free-haze image is obtained by reducing the high brightness value of the three color channels and using the mean value method. The experimental results show that the proposed method largely eliminates color distortion in the bright areas of the dehazed image and has better color degrees.

Key words: image dehazing, dark channel prior, color channels, image enhancement, atmosphere scattering model

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