Speckle Reduction for SAR Images Based on Adaptive Gaussian Mixture Models
Yanqiu Cui, Tao Zhang, Shuang Xu, Houjie Li · 2010
A new algorithm for suppressing speckle in synthetic aperture radar (SAR) images was proposed based on the local statistical property of wavelet coefficients. This method modeled the distribution of wavelet coefficients as an adaptive Gaussian mixture model. This model took into account geometrical structures of the coefficients within one scale and it was adaptive to the wavelet subbands corresponding to three orientations in the image. Based on this model in a Bayesian framework, a spatially adaptive Bayesian shrinkage function was obtained and each modified coefficient was decided separately. Experimental results demonstrate the proposed method improves the performance of speckle reduction and preserves the details of the image.