(Symmetric alpha-Stable)模型是小波域一种精确的图像模型 ，但是其计算复杂性高,本文在分析 模型的基础上，提出了高斯-柯西模型，将此模型作为图像的小波域先验模型信息，并用Bayesian估计器，算法复杂性上有显著的降低。另外，图像对数变换后的统计特性发生变化 ，需要在变换过程中加入均值调整的过程。实验结果表明，本文的算法模型在较好的保持了SAR图像结构的基础上，能较好的保留图像边缘信息和纹理特征，并能有效的抑制图像的斑点噪声，取得了良好的效果。

(Symmetric alpha-Stable) model is an accurate image model in Wavelet-domain. But this method needs lots of computation. In this paper, a new model, Gaussian-Cauchy model, was proposed on the base of model. Using this model characterizing the real-world images prior model can reduce computations obviously. In addition, the logarithm transform changes its statistical characteristic, so we must adjust the mean in the process. Experimental results show that there is almost nothing differences between this model and model in edges、 SNR (signal to noise ratio) and subjective visual effect.