基于大气散射模型的单幅图像去雾

孙伟; 李大健; 刘宏娟; 贾伟

doi:10.3788/OPE.20132104.1040

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基于大气散射模型的单幅图像去雾

信息科学 | 更新时间：2020-08-12

- 基于大气散射模型的单幅图像去雾
- Fast Single Image Fog Removal based on Atmospheric Scattering Model
- 光学精密工程 2013年21卷第4期页码：1040-1046
- 作者机构：
  
  西安电子科技大学机电工程学院2. 西北工业大学第365研究所
- 作者简介：
- 基金信息：
  
  视觉原理指导下的动目标检测与跟踪新方法研究()
- DOI：10.3788/OPE.20132104.1040
  中图分类号： TP752.1
- 收稿日期：2012-09-19，
  
  修回日期：2012-11-05，
  
  网络出版日期：2013-04-20，
  
  纸质出版日期：2013-04-15
- 稿件说明：
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孙伟李大健刘宏娟贾伟. 基于大气散射模型的单幅图像去雾[J]. 光学精密工程, 2013,21(4): 1040-1046

SUN Wei LI Da-jian LIU Hong-juan JIA Wei. Fast Single Image Fog Removal based on Atmospheric Scattering Model[J]. Editorial Office of Optics and Precision Engineering, 2013,21(4): 1040-1046
孙伟李大健刘宏娟贾伟. 基于大气散射模型的单幅图像去雾[J]. 光学精密工程, 2013,21(4): 1040-1046 DOI： 10.3788/OPE.20132104.1040.

SUN Wei LI Da-jian LIU Hong-juan JIA Wei. Fast Single Image Fog Removal based on Atmospheric Scattering Model[J]. Editorial Office of Optics and Precision Engineering, 2013,21(4): 1040-1046 DOI： 10.3788/OPE.20132104.1040.

摘要

根据大气散射物理模型及光学反射成像模型，总结并分析了影响单幅图像去雾效果的3大因素，以实现对雾霾图像的快速去雾。基于光学原理，解释了暗影通道现象，从新的角度推导出了大气散射模型中各参数的求法。利用灰度开运算去除白色目标的干扰获得精确的环境光亮度，基于快速联合双边带滤波精确计算了大气散射函数，最后由光学反射模型计算了场景目标的反射率并有效截断至[0

1]区间。本方法可以消除天空及环境光线的影响，能真实复原场景的色彩和清晰度。仿真结果表明，对分辨率为576768的图像处理时间仅为0.517 s，且视觉效果和客观指标比现有算法均有不同程度的提高。与现有图像去雾算法相比

本文提出的参数计算方法提高了运算速度、场景适应能力和复原效果。

Abstract

Based on the physical model of atmospheric scattering and an optical reflectance imaging model

three major factors influencing the fog removal for a single image were discussed in detail. The dark channel phenomenon was explained by the optical model

and the method to solve the parameters of atmospheric scattering model was rigorously derived from a new view. The gray-scale opening operation was used to eliminate the interference from a while object to obtain the global atmospheric light and the fast joint bilateral filtering technique was proposed to greatly improve the speed and accuracy of atmospheric scattering function solving. Finally

the scene albedo was recovered by inverting this model. Experiments show that the method can remove effectively the effect of lights from sky and environments and can recover the color and definition of original scenes. The simulation results indicate that the processing time for an image of 576768 spends only by 1.7 s. As compared with the existing algorithm

obtained results on a variety of outdoor foggy images demonstrate that the proposed method achieves good restoration for contrast and color deity

and improves image visibility greatly.

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references

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