沈 琛,曹风云,杨雪洁.夜间图像去雾研究综述与展望[J].电子测量与仪器学报,2020,34(11):101-114
夜间图像去雾研究综述与展望
Review and prospect of nighttime haze removal
  
DOI:
中文关键词:  夜间去雾  大气散射模型  深度学习  图像质量评测
英文关键词:nighttime haze removal  atmospheric scattering model  deep learning  image quality assessment
基金项目:安徽省自然科学基金青年基金(1708085QF157)、安徽省高校优秀青年人才项目( gxyq2019068,gxyq2017050)、电子信息系统仿真设计安徽省重点实验室开放基金项目(2019ZDSYSZY06)资助
作者单位
沈 琛 1. 合肥师范学院 计算机学院,2. 安徽大学 电子信息工程学院 
曹风云 1. 合肥师范学院 计算机学院,3. 合肥师范学院 电子信息系统仿真设计安徽省重点实验室 
杨雪洁 1. 合肥师范学院 计算机学院 
AuthorInstitution
Shen Chen 1. School of Computer, Hefei Normal University,2. School of Electronics and Information,Anhui University 
Cao Fengyun 1. School of Computer, Hefei Normal University,3. Anhui Province Key Laboratory of Simulation and Design for Electronic Information System,Hefei Normal University 
Yang Xuejie 1. School of Computer, Hefei Normal University 
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中文摘要:
      夜间图像去雾技术是图像处理和计算机视觉领域的研究热点,对航空航天、自动驾驶、交通监控等领域具有十分重要的 意义。 综合了近年来夜间图像去雾技术的国内外研究工作,分别从基于物理模型的传统方法和基于深度学习的方法两方面对 近年来提出的典型方法进行归纳和总结,详细阐述了现有方法的优势和不足,并对一些典型的夜间去雾方法分别从主观评价和 客观评价两方面进行了比较和分析。 最后,展望了夜间图像去雾技术的未来研究方向,并给出了一些建议
英文摘要:
      Removing nighttime haze technique is a research hotspot in both digital image processing and computer vision, which is of great significance in the fields of aerospace, autonomous driving and traffic monitoring. Surveyed the domestic and foreign research on nighttime image defogging in recent years, summarized from the viewpoint of the traditional methods based on physical models and the method based on deep learning. After that, illustrated those algorithms in detail and then characterized their strengths and limitations, followed by comparison and analysis from subjective and objective evaluation respectively. Finally, future research directions were prospected and some suggestions were given.
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