大气光幂雾图像的清晰度复原

吴斌; 付辉; 张红英

doi:10.3788/OPE.20162408.2018

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大气光幂雾图像的清晰度复原

信息科学 | 更新时间：2020-07-07

- 大气光幂雾图像的清晰度复原
- De-hazing of atmosphere veil haze images
- Editorial Office of Optics and Precision Engineeri 2016年24卷第8期页码：2018-2026
- 作者机构：
  
  西南科技大学信息工程学院, 四川绵阳 621000
- 作者简介：
  
  [ "吴斌(1965-)，男，四川大竹人，教授，博士生导师，1985年于中南大学获得学士学位，1993年、1999年于北京科技大学分别获得硕士、博士学位，主要从事经济智能控制、图像处理等方面的研究。E-mail：wubin@swust.edu.cn" ]
  付辉(1991-)，女，山西阳泉人，硕士研究生，主要从事图像处理、DSP的研究。E-mail：1285110730@qq.com E-mail：1285110730@qq.com
- 基金信息：
  
  四川省教育厅重点项目(No.15ZA0118);特殊环境机器人技术四川省重点实验室开放基金资助项目(No.13zxtk0505);西南科技大学博士基金资助项目(No.13zx7112)
- DOI：10.3788/OPE.20162408.2018
  中图分类号： TP391.4
- 收稿日期：2016-03-22，
  
  录用日期：2016-5-23，
  
  纸质出版日期：2016-08-25
- 稿件说明：
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吴斌, 付辉, 张红英. 大气光幂雾图像的清晰度复原[J]. Editorial Office of Optics and Precision Engineeri, 2016,24(8):2018-2026.

Bin WU, Hui FU, Hong-ying ZHANG. De-hazing of atmosphere veil haze images[J]. Optics and precision engineering, 2016, 24(8): 2018-2026.
吴斌, 付辉, 张红英. 大气光幂雾图像的清晰度复原[J]. Editorial Office of Optics and Precision Engineeri, 2016,24(8):2018-2026. DOI： 10.3788/OPE.20162408.2018.

Bin WU, Hui FU, Hong-ying ZHANG. De-hazing of atmosphere veil haze images[J]. Optics and precision engineering, 2016, 24(8): 2018-2026. DOI： 10.3788/OPE.20162408.2018.

摘要

针对现有图像去雾方法处理效率低，天空部分处理效果欠佳以及去雾图像视觉效果不理想等问题，提出了一种快速大气光幂去雾算法。提出的算法是对全球环境光值和大气光幂值求取方法的改进。首先，采用高斯低通滤波求取雾气图像低频区，应用循环四分图算法在低频区得到全球环境光值A；其次，采用暗原色优先算法获取初始大气光幂值，结合自适应各向异性高斯滤波处理大气光幂；最后，采用色调调整增强图像细节，使图像逼近于无雾场景。实验结果表明，本文算法能消减图像景深突变处的晕轮效应，亮度、对比度和细节信息处理效果较好，不仅较完整地保留了边缘细节，而且显著提升了处理效率，同时具有较高的鲁棒性和实时性。

Abstract

A fast atmosphere veil de-hazing method was proposed to overcome the shortcomings of existing de-hazing methods in lower process efficiency

poorer treatment result of sky part and a bad visual effect for images. The method focuses on the improvements for global atmospheric light values and the acquiring method of atmospheric veil values. Firstly

the Gaussian low-pass filter method was used to gain a low frequency area of an image

and the circle quarter figure algorithm was used to obtain the global atmospheric light value of the low frequency area. Then

the dark channel prior algorithm was employed to achieve the initial atmospheric veil value and the atmospheric veil was processed by the adaptive anisotropic Gaussian filter. Finally

image details were enhanced by utilizing tone mapping

by which the image could approximate to the no fog scene image. The experimental results show that the proposed method restricts the halo effect of depth mutation area in the image and well processes lightness

contrast and detail information for the image. It keeps edge details of the image perfectly

improves the image processing efficiency and has good robustness and real-time ability.

关键词

Keywords

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