基于暗通道先验的图像去雾算法改进

王凯; 王延杰; 樊博

doi:10.3788/YJYXS20163108.0840

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基于暗通道先验的图像去雾算法改进

驱动与控制 | 更新时间：2020-07-07

- 基于暗通道先验的图像去雾算法改进
- Improved method for single image dehazing using dark channel prior
- 液晶与显示 2016年31卷第8期页码：840-845
- 作者机构：
  
  1.中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
  2.中国科学院大学, 北京 100049
- 作者简介：
  
  王凯(1991-), 男, 辽宁沈阳人, 硕士研究生, 主要从事数字图像处理方面的研究。E-mail:wangkaicool@foxmail.com
- 基金信息：
  
  国家863高技术研究发展计划资助项目(2015AA703101);National High Technology Research and Development Program of China(2015AA7031010B)
- DOI：10.3788/YJYXS20163108.0840
  中图分类号： TP391
- 收稿日期：2016-04-11，
  
  录用日期：2016-8-19，
  
  纸质出版日期：2016-08
- 稿件说明：
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王凯, 王延杰, 樊博. 基于暗通道先验的图像去雾算法改进[J]. 液晶与显示, 2016,31(8):840-845.

Kai WANG, Yan-jie WANG, Bo FAN. Improved method for single image dehazing using dark channel prior[J]. Chinese journal of liquid crystals and displays, 2016, 31(8): 840-845.
王凯, 王延杰, 樊博. 基于暗通道先验的图像去雾算法改进[J]. 液晶与显示, 2016,31(8):840-845. DOI： 10.3788/YJYXS20163108.0840.

Kai WANG, Yan-jie WANG, Bo FAN. Improved method for single image dehazing using dark channel prior[J]. Chinese journal of liquid crystals and displays, 2016, 31(8): 840-845. DOI： 10.3788/YJYXS20163108.0840.

摘要

为了实现基于物理模型的图像复原去雾算法，文中提出了一种改进的基于暗通道先验的图像去雾算法。介绍了雾天图像退化模型和基于该雾天图像退化模型的几种去雾算法。详细介绍了何恺明提出的基于暗通道先验的去雾算法，该算法在估计光线传播图时使用的基于导向滤波的软抠图非常耗时，经过改进，直接使用景深估计光线传播图，算法运行时间大大减少。最后，使用MATLAB对改进的去雾算法进行仿真，并与原算法的运行时间进行比较。结果显示新方法对光线传播图的估计可靠，运行时间对比改进前大约下降60%，实时性大大提高。带有天空的有雾图像去雾后色斑和光晕大幅减少，取得了很好的效果。改进的去雾算法运行速度快、去雾效果好，新提出的光线传播图估计方法可靠，并且去雾过程中得到的光线传播图可以用于其他应用。

Abstract

To develop an algorithm for haze removal based on the physics model

this paper proposes an improved and fast method for single image haze removal using dark channel prior. First

we introduce the degraded model for describing the formation of a haze image and several algorithms based on this model. Second

we introduce the method of He's single image haze removal using dark channel prior. The image quality of He's method is satisfactory

but it is a time consuming method because of refining the transmission map with guide filter. We propose an optimized method based on estimating transmission by scene depth directly and the runtime of the new algorithm decreases a lot. Finally

we realize the algorithm in MATLAB and compare the runtime with the original algorithm. Results demonstrates that the new method provides a reliable transmission estimation and a better image quality with around 40% computation time of He's method

and the results of haze images with sky are less halos. The optimized method execute fast and the results demonstrate the new method abilities to remove the haze layer as well as provide a high quality transmission estimation as a byproduct of haze removal which can be used for other applications.

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references

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