基于平稳小波域GSM模型的SAR图像去噪

为解决SAR图像处理中传统方法存在的图像边缘模糊、失真等问题,将平稳小波变换和高斯混合尺度模型（GSM）相结合,建立了基于平稳小波分解系数的邻域模型,并利用Bayes最小均方估计进行局部去噪,最后对各个方法的滤波结果用评估参数进行客观评价。实验结果表明,该方法具有比空域滤波及标准小波方法更优的去噪性能。

SAR image despeckling based on Gaussian scale mixtures model in stationary wavelet domain

Aimed at overcoming blurring edge and distortion revealed by traditional methods used in image processing,this paper proposes the combination of stationary wavelet transform with Gaussian scale mixtures model to develop the neighborhood model based on stationary wavelet transform coefficients and the reduction of the speckle noise by using Bayes least square estimation.The paper ends with the objective assessment of filtering results of the various methods by using evaluation parameters.Experimental results show that this method exhibits the speckle noise-reducing performance better than the spatial filters and standard wavelet transform.