基于贝叶斯门限的静态小波域干涉相位图滤波

干涉相位图中的噪声会妨碍后续的相位解缠，并降低最终的DEM精度。本文提出一种静态小波域的干涉相位图滤波方法。该方法能够自适应地计算贝叶斯门限分类静态小波系数，并可根据干涉相位图特性自适应地选取小波变换的最优尺度值。文中用仿真数据和SIR-C/X SAR在意大利Etna火山的干涉数据进行实验，并将该文算法处理结果与均值滤波、中值滤波和Goldstein滤波的结果相比较。用该算法处理，处理仿真数据所得结果的最小均方误差和相关性均优于其余方法。该算法处理Etna火山的干涉数据时，残余点从30430点降至113点，远少于其余算法的处理结果。实验结果表明：该文算法能够较好地保持干涉条纹细节，有效减少干涉相位图中的残余点，与Goldstein滤波相比也具有一定优势。

INSAR Interferogram Filtering Based on Bayesian Threshold in Stationary Wavelet Domain

Noise in the interferogram hinders the processing of two-dimensional phase unwrapping,and decreases the accuracy of the final DEM products. In this paper a interferometric phase noise reduction algorithm,in the stationary wavelet domain,is proposed. The algorithm chooses threshold of wavelet coefficients adaptively by using Bayesian method,and adaptively selects the best scale of two dimensional stationary wavelet transform for filtering. By using both simulated and SIR-C/X SAR generated interferograms,the performance of the algorithm is demonstrated and compared with the mean filter,the median filter and the Goldstein filter. By processing the simulated data,it is proved that the algorithm can get a result with better RMS and coherence. By using the algorithm,the residue number of real data reduced from 30430 to 113,far below the other methods. The result shows that the algorithm can preserve the fringes better,and filter the phase noise more effectively by reducing the number of residues. And the algorithm has some advantages over the Goldstein filter.