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基于复contourlet域隐马尔科夫树模型的海面溢油合成孔径雷达图像相干斑抑制

DOI: 10.3969/j.issn.02534193.2013.02.018, PP. 168-177

Keywords: 海面溢油检测,合成孔径雷达图像,相干斑抑制,复contourlet变换,隐马尔科夫树模型,贝叶斯估计

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Abstract:

海面溢油SAR图像中的相干斑噪声严重影响了后续的图像分割、特征提取和分类。为了更有效地抑制海面溢油SAR图像相干斑,文中提出了一种基于复contourlet域隐马尔科夫树模型的海面溢油SAR图像相干斑抑制方法。首先对观测图像取对数并进行复contourlet变换;然后在复contourlet域中用隐马尔科夫树模型对相邻尺度间的带通方向子带系数进行建模,并依据贝叶斯最小均方误差准则估计无噪系数;最后进行逆复contourlet变换和指数变换,得到相干斑抑制后的图像。大量实验结果表明,与Lee、Kuan、Frost及GammaMap等4种经典滤波方法以及小波域和contourlet域隐马尔科夫树模型方法相比,文中方法从主观视觉和客观定量评价两方面来看综合性能更为优越,是一种行之有效的SAR遥感图像海面溢油检测的预处理方法。

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