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基于局部平移瑞利分布模型的SAR图像相干斑抑制

凤宏晓 焦李成 侯彪

凤宏晓, 焦李成, 侯彪. 基于局部平移瑞利分布模型的SAR图像相干斑抑制[J]. 电子与信息学报, 2010, 32(4): 925-931. doi: 10.3724/SP.J.1146.2009.00512
引用本文: 凤宏晓, 焦李成, 侯彪. 基于局部平移瑞利分布模型的SAR图像相干斑抑制[J]. 电子与信息学报, 2010, 32(4): 925-931. doi: 10.3724/SP.J.1146.2009.00512
Feng Hong-xiao, Jiao Li-cheng, Hou Biao. SAR Image Despeckling Based on Local Translation-Rayleigh Distribution Model[J]. Journal of Electronics & Information Technology, 2010, 32(4): 925-931. doi: 10.3724/SP.J.1146.2009.00512
Citation: Feng Hong-xiao, Jiao Li-cheng, Hou Biao. SAR Image Despeckling Based on Local Translation-Rayleigh Distribution Model[J]. Journal of Electronics & Information Technology, 2010, 32(4): 925-931. doi: 10.3724/SP.J.1146.2009.00512

基于局部平移瑞利分布模型的SAR图像相干斑抑制

doi: 10.3724/SP.J.1146.2009.00512

SAR Image Despeckling Based on Local Translation-Rayleigh Distribution Model

  • 摘要: 该文提出了一种基于平稳小波域统计模型的SAR图像抑斑算法。首先对SAR图像应用非对数加性模型,接着针对该模型中的噪声在空域提出一种统计分布模型局部平移瑞利分布模型。最后基于该分布,在平稳小波域应用最大后验(MAP)方法获得真实信号平稳小波系数的解。实验表明,该文提出的局部平移瑞利分布模型是有效的,同时也表明该文给出的一种基于此分布模型的抑斑算法有很强的鲁棒性,抑斑性能优于许多现存的算法。
  • Oliver C and Quegan S. Understanding Synthetic ApertureRadar Images. Boston MA: Artech House, 1998: 158-187.[2]Lee J S. Digital image enhancement and noise filtering by useof local statistics[J].IEEE Transactions on Pattern Analysisand Machine Intelligence.1980, PAMI-2(2):165-168[3]Lopes A, Touzi R, and Nezry E. Adaptive speckle filters andscene heterogeneity[J].IEEE Transactions Geoscience andRemote Sensing.1990, 28(6):992-1000[4]Lopes A.[J].Nezry E, and Touzi R, et al.. Maximum a posteriorifiltering and first order texture models in SAR images. Proc.IGARSS90, Washington, D.C., May 20-2.1990,:-[5]Bhuiyanr M I H, Ahmad M O, and Swamy M N S. Spatiallyadaptive wavelet- based method using the cauchy prior fordenoising the SAR images. IEEE Transactions on Geoscienceand Remote Sensing, 2007, 17(4): 500-507.[6]卢晓光, 韩萍, 吴仁彪等. 基于二维小波变换和独立分量分析的SAR 图像去噪方法[J].电子与信息学报.2008, 30(5):1052-1055浏览[7]Bianchi T, Argenti F, and Alparone L. Segmentation-basedMAP despeckling of SAR images in the undecimated Waveletdomain[J].IEEE Transactions on Geoscience and RemoteSensing.2008, 46(9):2728-2742[8]Stian S and Torbj.rn E. A stationary wavelet-domain wienerfilter for correlated speckle. IEEE Transactions onGeoscience and Remote Sensing, 2008, 46(4): 1219-1230.[9]郭旭静, 王祖林. SAR 图像的非下采样Contourlet 噪声抑制算法. 北京航空航天大学学报, 2007, 33(8): 894-897.Guo X J and Wang Z L. Nonsubsampled Contourlet specklereduction algorithm for SAR images. Journal of BeijingUniversity of Aeronautics and Astronautics, 2007, 33(8):894-897.[10]Xie H, Pierce L E, and Ulaby F T. Statistical properties oflogarithmically transformed speckle[J].IEEE Transactions onGeoscience and Remote Sensing.2002, 40(3):721-727[11]Nason G P and Silverman B W. The stationary wavelettransform and some statistical applications in wavelet andstatistics. Lecture notes in statistics, Berlin: Spinger Verlag,1995: 281-299.[12]Xie H, Pierce L E, and Ulaby F T. SAR speckle reductionusing wavelet denoising and Markov random field modeling[J].IEEE Transactions on Geoscience and Remote Sensing.2002,40(10):2196-2212
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出版历程
  • 收稿日期:  2009-04-10
  • 修回日期:  2009-09-28
  • 刊出日期:  2010-04-19

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