结合自适应雾气估计的快速单幅图像去雾

杨燕; 刘珑珑; 张得欣; 杨志飞

doi:10.3788/OPE.20192710.2263

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结合自适应雾气估计的快速单幅图像去雾

信息科学 | 更新时间：2020-08-13

- 结合自适应雾气估计的快速单幅图像去雾
- Fast single image dehazing combined with adaptive haze estimation
- 光学精密工程 2019年27卷第10期页码：2263-2271
- 作者机构：
  
  兰州交通大学电子与信息工程学院，甘肃兰州730070
- 作者简介：
  
  [ "杨燕(1972-)，女，河南临颍人，博士，教授，硕士生导师，1995年于兰州铁道学院获得学士学位，2006年于兰州交通大学获得硕士学位，2010年于兰州大学获得博士学位，主要从事数字图像处理、智能信息处理及语音信号处理方面的研究。E-mail：yangyantd@mail.lzjtu.cn" ]
  [ "刘珑珑(1993-)，女，山东菏泽人，硕士研究生，2017年于济南大学获得学士学位，主要从事数字图像处理方面的研究。E-mail：1067173785@qq.com" ]
- 基金信息：
  
  国家自然科学基金资助项目(61561030);机器人学国家重点实验室开放基金资助项目(2015008)
- DOI：10.3788/OPE.20192710.2263
  中图分类号： TP391.41
- 收稿日期：2019-03-20，
  
  录用日期：2019-4-10，
  
  纸质出版日期：2019-10-15
- 稿件说明：
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杨燕, 刘珑珑, 张得欣, 等. 结合自适应雾气估计的快速单幅图像去雾[J]. 光学精密工程, 2019,27(10):2263-2271.

Yan YANG, Long-long LIU, De-xin ZHANG, et al. Fast single image dehazing combined with adaptive haze estimation[J]. Optics and precision engineering, 2019, 27(10): 2263-2271.
杨燕, 刘珑珑, 张得欣, 等. 结合自适应雾气估计的快速单幅图像去雾[J]. 光学精密工程, 2019,27(10):2263-2271. DOI： 10.3788/OPE.20192710.2263.

Yan YANG, Long-long LIU, De-xin ZHANG, et al. Fast single image dehazing combined with adaptive haze estimation[J]. Optics and precision engineering, 2019, 27(10): 2263-2271. DOI： 10.3788/OPE.20192710.2263.

摘要

大气中水分子及微小颗粒对光的散射和吸收，使得在雾天条件下获取的图像严重降质，本文提出一种结合自适应雾气估计的快速单幅图像去雾算法。首先，该算法从大气散射模型出发，通过分析景深与亮度分量之间存在的相关关系，提出线性系数利用亮度分量来近似估计出景深，并通过最小滤波对明亮区域进行修正，得到粗略透射率；其次，观察到散射系数值与雾浓度呈正相关，从而结合雾浓度模型与指数函数提出自适应散射系数概念，估计出较准确的透射率；最后，根据大气散射模型复原出无雾图像。实验结果表明本文算法可以复原出清晰自然的无雾图像，明显提高了图像可见度，且具有较低的时间复杂度。

Abstract

Owing to the scattering and absorption of light by water molecules and other tiny particles in the atmosphere

images captured in hazy conditions are inevitably seriously degraded. To address this problem

a fast single image dehazing algorithm combined with adaptive haze estimation was proposed in this paper. The algorithm begined by considering the atmospheric scattering model and assumed a correlation between scene depth and luminance components. Subsequently

a linear coefficient was proposed to approximate the scene depth using the luminance components

and overly bright regions were corrected via minimum filtering to obtain a coarse transmission. As the value of the scattering coefficient was related to the haze concentration

the concept of an adaptive scattering coefficient was proposed by combining the haze concentration model with the exponential function to estimate the accurate transmission. Finally

a haze-free image was restored via the atmospheric scattering model. Experimental results demonstrated that the proposed algorithm could recover a clear

natural

and haze-free image

which significantly improves image visibility and has lower computational complexity than existing methods.

关键词

Keywords

references

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SUN W, WANG H, SUN C H, et al .. Fast single image haze removal via local atmospheric light veil estimation[J]. Computers & Electrical Engineering, 2015, 46(C): 371-383.

CAI B L, XU X M, JIA K, et al .. DehazeNet: an end-to-end system for single image haze removal[J]. IEEE Transactions on Image Processing , 2016, 25(11): 5187-5198.

王一斌, 伊诗白, 吕卓纹.自适应背景光估计与非局部先验的水下图像复原[J].光学精密工程, 2019, 27(2):499-509.

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