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基于最大后验和非局域约束的非下采样轮廓波变换域SAR图像去噪方法

岳春宇1,江万寿2   

  1. 1. 武汉大学
    2. 武汉大学测绘遥感信息工程国家重点实验室
  • 收稿日期:2011-04-11 修回日期:2011-05-23 出版日期:2012-02-25 发布日期:2012-02-25
  • 通讯作者: 岳春宇

An Algorithm of SAR Image Denoising in Nonsubsampled Contourlet Transform(NSCT)Domain Based on Maximum A Posteriori(MAP) and Non-Local(NL) Restriction

  • Received:2011-04-11 Revised:2011-05-23 Online:2012-02-25 Published:2012-02-25

摘要: 本文提出了一种基于最大后验和非局域约束的非下采样轮廓波变换域SAR图像去噪方法。根据SAR图像数据的特征,引入了非对数加性模型,并在该模型下对SAR图像NSCT域中的噪声分布统计建模,应用最大后验(MAP)准则和Non-Local(NL)约束相结合的方法解求SAR图像真实信号的NSCT系数。实验结果表明,本方法具有良好的去噪能力并在性能上优于当前主流方法。

Abstract: An algorithm of SAR image denoising in Nonsubsampled Contourlet Transform(NSCT) domain based on Maximum A Posteriori(MAP) and Non-Local(NL) restriction is proposed in this paper. Nonlogarithmic additive model is applied to SAR image, and then the statistical distribution of the noise within nonlogarithmic additive model is modeled in the NSCT domain. MAP and NL restriction are used to get the NSCT coefficients of the real signal. Experiments show that the algorithm proposed in this paper is effective in SAR image denoising, and also possess high performance over many traditional algorithms.