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图像去雾的最新研究进展

吴迪 朱青松

吴迪, 朱青松. 图像去雾的最新研究进展. 自动化学报, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137
引用本文: 吴迪, 朱青松. 图像去雾的最新研究进展. 自动化学报, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137
WU Di, ZHU Qing-Song. The Latest Research Progress of Image Dehazing. ACTA AUTOMATICA SINICA, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137
Citation: WU Di, ZHU Qing-Song. The Latest Research Progress of Image Dehazing. ACTA AUTOMATICA SINICA, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137

图像去雾的最新研究进展


DOI: 10.16383/j.aas.2015.c131137
详细信息
    作者简介:

    吴迪 上海交通大学软件学院硕士研究生. 中国科学院深圳先进技术研究院客座学生. 主要研究方向为计算机视觉与机器学习.E-mail: gandwudi@hotmail.com

    通讯作者: 朱青松 中国科学院深圳先进技术研究院医疗机器人与微创手术器械研究中心副研究员. 2010 年获中国科学技术大学硕士学位. 主要研究方向为机器人视觉技术基础研究, 核与支持向量机, 统计模式识别, 机器学习, 图灵测试与图灵自动机以及图像引导微创手术机器人. 本文通信作者. E-mail: qs.zhu@siat.ac.cn
  • 基金项目:

    国家重点基础研究发展计划(973计划)(2010CB732606),国家自然科学基金(61303166)资助

The Latest Research Progress of Image Dehazing

More Information
  • Fund Project:

    Supported by National Basic Research Program of China (973 Program) (2010CB732606), and National Natural Science Foundation of China (61303166)

  • 摘要: 随着计算机视觉系统的发展及其在军事、交通以及安全监控等领域的发展, 图像去雾已成为计算机视觉的重要研究方向. 在雾、霾之类的恶劣天气下采集的图像会由于大气散射的作用而被严重降质, 使图像颜色偏灰白色, 对比度降低, 物体特征难以辨认, 不仅使视觉效果变差, 图像观赏性降低, 还会影响图像后期的处理, 更会影响各类依赖于光学成像仪器的系统工作, 如卫星遥感系统、航拍系统、室外监控和目标识别系统等. 因此, 需要图像去雾技术来增强或修复, 以改善视觉效果和方便后期处理. 本文归纳总结了两大类图像去雾方法:基于图像增强和基于物理模型的方法, 深入探讨了其中的典型算法和研究成果, 并对这些算法的测试结果进行了定性和定量的分析比较, 最后总结了图像去雾技术目前的研究状况和未来的发展方向.
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出版历程
  • 收稿日期:  2013-12-16
  • 修回日期:  2014-06-10
  • 刊出日期:  2015-02-20

图像去雾的最新研究进展

doi: 10.16383/j.aas.2015.c131137
    基金项目:

    国家重点基础研究发展计划(973计划)(2010CB732606),国家自然科学基金(61303166)资助

    作者简介:

    吴迪 上海交通大学软件学院硕士研究生. 中国科学院深圳先进技术研究院客座学生. 主要研究方向为计算机视觉与机器学习.E-mail: gandwudi@hotmail.com

    通讯作者: 朱青松 中国科学院深圳先进技术研究院医疗机器人与微创手术器械研究中心副研究员. 2010 年获中国科学技术大学硕士学位. 主要研究方向为机器人视觉技术基础研究, 核与支持向量机, 统计模式识别, 机器学习, 图灵测试与图灵自动机以及图像引导微创手术机器人. 本文通信作者. E-mail: qs.zhu@siat.ac.cn

摘要: 随着计算机视觉系统的发展及其在军事、交通以及安全监控等领域的发展, 图像去雾已成为计算机视觉的重要研究方向. 在雾、霾之类的恶劣天气下采集的图像会由于大气散射的作用而被严重降质, 使图像颜色偏灰白色, 对比度降低, 物体特征难以辨认, 不仅使视觉效果变差, 图像观赏性降低, 还会影响图像后期的处理, 更会影响各类依赖于光学成像仪器的系统工作, 如卫星遥感系统、航拍系统、室外监控和目标识别系统等. 因此, 需要图像去雾技术来增强或修复, 以改善视觉效果和方便后期处理. 本文归纳总结了两大类图像去雾方法:基于图像增强和基于物理模型的方法, 深入探讨了其中的典型算法和研究成果, 并对这些算法的测试结果进行了定性和定量的分析比较, 最后总结了图像去雾技术目前的研究状况和未来的发展方向.

English Abstract

吴迪, 朱青松. 图像去雾的最新研究进展. 自动化学报, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137
引用本文: 吴迪, 朱青松. 图像去雾的最新研究进展. 自动化学报, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137
WU Di, ZHU Qing-Song. The Latest Research Progress of Image Dehazing. ACTA AUTOMATICA SINICA, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137
Citation: WU Di, ZHU Qing-Song. The Latest Research Progress of Image Dehazing. ACTA AUTOMATICA SINICA, 2015, 41(2): 221-239. doi: 10.16383/j.aas.2015.c131137
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