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This paper extends the application of Block-matching(BM) and 3D transform-domain collaborative filtering(BM3D) to the noise reduction in Interferometric synthetic aperture radar(In SAR) phase imagery,and proposes a denoising algorithm which can effectively remove noise and preserve fringes. Since the noise level estimated by a median estimator is not always optimal for proposed algorithm in wavelet domain, a method of calculating optimal noise standard deviation is also developed.The proposed algorithm is efficient and robust. Experimental results show that the visual quality and evaluation indexes of proposed algorithm outperform other filters for both simulated and real In SAR images.
This paper extends the application of Block-matching (BM) and 3D transform-domain collaborative filtering (BM3D) to the noise reduction in Interferometric synthetic aperture radar (In SAR) phase imagery, and proposes a denoising algorithm which can effectively remove noise and preserve fringes. Since the noise level estimated by a median estimator is not always optimal optimal for proposed algorithm in wavelet domain, a method of calculating optimal noise standard deviation is also developed. The proposed algorithm is efficient and robust. Experimental results show that the visual quality and evaluation indexes of proposed algorithm outperform other filters for both simulated and real In SAR images.