冗余轮廓波变换的构造及其在SAR图像降斑中的应用

The Construction of Redundant Contourlet Transform and Its Application to SAR Image Despeckling

构造了由非抽样塔式分解和方向滤波器组实现的冗余轮廓波变换。文中利用McClellan变换设计非抽样塔式分解中满足精确重构条件的圆对称滤波器组。利用冗余轮廓波变换系数的自适应局部统计模型及最大后验概率法对SAR图像进行降斑处理,并与基于平稳小波和轮廓波变换的降斑算法进行比较。结果表明,提出的算法能有效地去除散斑噪声,并且具有更强的边缘保持能力。

The redundant contourlet transform implemented by undecimated pyramidal decomposition and directional filter bank is proposed. The circular symmetric filter bank satisfying perfect reconstruction conditions in the undecimated pyramidal decomposition is designed by McClellan transform. The adaptive local statistical model in the redundant contourlet domain and MAP estimator are employed to reduce speckle noise in SAR images. Compared with the despeckling methods based on stationary wavelet and contourlet transform, the proposed algorithm can reduce speckle noise more effectively while preserving the edges of the SAR images.