INSAR Interferogram Filtering Based on Bayesian Threshold in Stationary Wavelet Domain
Wang Pei①②; Wang Yan-fei①; Zhang Bing-chen①; Tang Yu①②; Ma Li-xiang①②
①Institute of Electronics, Chinese Academy of Sciences, Beijing 100080, China;②Graduate School of the Chinese Academy of Sciences, Beijing 100039, China
Abstract: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.