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中文摘要：
提出了一种结合边缘信息的双树复小波变换（dual tree complex wavelet transform,DT-CWT）干涉图滤波算法。该方法是在DT-CWT几何多尺度变换域上,通过分析层间系数的传递性及层内系数的相关性确定边缘系数,并利用贝叶斯双变量收缩函数分别对复数小波域的边缘及非边缘系数采用不同的阈值进行收缩处理。实验结果表明,本算法对干涉图噪声有较强的抑制能力,较大程度地保留了干涉图的边缘及细节信息,处理结果优于传统小波域软阈值去噪方法。
英文摘要：
A new algorithm considering edge information in dual tree complex wavelet transform （DT-CWT） domain was proposed in this paper. In the multiscale geometry transforming domain of DT-CWT, the edge coefficients were determined by analyzing both the transitivity of interscale coefficients and the correlation of intrascale coefficients. The edge and non-edge coefficients in DT-CWT domain were shrunk with different thresholds by using the Bayes bivariate shrinkage function. The experimental results show that the algorithm proposed in this paper obviously restrains the interferogram noise and also greatly maintain the edges and details information comparing with the traditional way of soft-threshold denoising in wavelet domain.
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