SAR image denoising based on wavelet fuzzy clustering algorithm
Xu Wei, Zhanzhuang He · Journal of Changchun Post and Telecommunication Institute · 2004
An efficient method based on algorithm of wavelet fuzzy clustering to suppress the speckle noise in synthetic aperture radar SAR (Synthetic Aperture Radar) images is presented. It regards the segmentation of signal and noise' wavelet coefficients as two types of pattern classification. The noise coefficient from wavelet coefficient amplitude and edge information in high frequency subimage which is considered as feature clustering is separated. The proposed technique produces a refined separation of wavelet coefficient, and filters speckle noise as well. The method has preferable data self-organized capability without threshold selecting and foregoing noise information. The simulative experimental results show that it has obvious merits in the image effect and PSNR(Peak Signal-to-Noise Ratio)of the two-dimension clustering denoising is increased by 8% approximately.