计算机应用 ›› 2011, Vol. 31 ›› Issue (05): 1227-1229.DOI: 10.3724/SP.J.1087.2011.01227

• 图形图像技术 • 上一篇    下一篇

单幅遥感图像去除薄云算法的改进

阎庆1,2,3,梁栋1,2,张晶晶3   

  1. 1.安徽大学 计算智能与信号处理教育部重点实验室,合肥230039
    2.安徽大学 电子信息工程学院,合肥230039
    3.安徽大学 电气工程与自动化学院,合肥230039
  • 收稿日期:2010-10-20 修回日期:2010-12-08 发布日期:2011-05-01 出版日期:2011-05-01
  • 通讯作者: 阎庆
  • 作者简介:阎庆(1978-),女,安徽六安人,讲师,博士研究生,主要研究方向:数字图像处理、模式识别;梁栋(1963-),男,安徽合肥人,教授,博士,主要研究方向:计算视觉、计算信号处理、电能质量检测与控制;张晶晶(1974-),女,浙江宁波人,讲师,博士,主要研究方向:遥感图像处理。
  • 基金资助:

    国家自然科学基金资助项目(60772121);安徽省教育厅重点科研计划项目(KJ2010A021)。

Improved algorithm for removing thin cloud in single remote sensing image

YAN Qing1,2,3, LIANG Dong1,2, ZHANG Jing-jing3   

  1. 1. Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, Hefei Anhui 230039, China
    2. School of Electronics and Information Engineering, Anhui University, Hefei Anhui 230039, China
    3. College of Electrical Engineering and Automation, Anhui University, Hefei Anhui 230039, China
  • Received:2010-10-20 Revised:2010-12-08 Online:2011-05-01 Published:2011-05-01

摘要: 针对基于小波阈值理论提出的云区阈值法存在的容易产生边界效应的问题,提出了一种改进的单幅图像去除薄云的新算法。对有云图像做多层小波分解,找到合适的分界层数,将小波系数分成高、低细节系数和近似系数3个部分。去云处理中仅对高层小波细节系数作同态滤波,而对低层小波细节系数和近似系数作简单的加权处理,最后将三部分系数重构得到去云的结果图像。将该方法与同态滤波法和云区阈值法进行了对比实验研究。实验结果表明,该方法不仅可以有效减少薄云雾的影响,而且可以更好地保留图像细节信息,同时防止了边缘效应的产生。

关键词: 遥感图像处理, 薄云去除, 小波变换, 同态滤波, 权重因子

Abstract: Because the algorithm of cloud threshold often generates boundary effect, this paper proposed an improved algorithm based on wavelet transform and homomorphic filter. The image with cloud was decomposed by wavelet transform to find the proper number of demarcation levels. Cloud could be removed by making homomorphic filtering to the higher level coefficients, while giving the lower level detailed coefficients and the approximation coefficients some weight factors respectively. The three parts of coefficients were reconstructed and fused to get processed result. The experimental results indicate that the proposed algorithm can remove the thin cloud cover effectively, maintain the details better and prevent producing the boundaries.

Key words: remote image processing, thin cloud removal, wavelet transform, homomorphic filting, weight factor