方向小波域的选择性阈值SAR图像去噪

SAR图像去噪一直是SAR图像处理中一个具有特殊意义的研究课题。噪声抑制的关键是解决图像平滑与保持纹理之间的矛盾。提出了一种基于方向小波的选择性阈值SAR图像去噪算法。该算法利用方向小波的多方向框架对图像作12个方向的分解和变换。针对方向小波分解图像所产生的系数序列长度不同的特点，利用白噪声的置信区间，将不同长度的系数分成3组，对中间长度的系数序列采用统一阈值，对其他长度序列采用白噪声置信区间阈值处理。为了更好地保持图像细节信息，将每一尺度高频系数的方差中值作为噪声方差估计值。利用真实的SAR图像进行去噪试验，与几种经典的空域滤波和小波软阈值算法进行比较结果表明，该算法在平滑图像的同时更好地保持了图像本身的纹理信息，图像的视觉效果优于其他算法，等效视数和边缘保持指数分别提高了97和0.15。

SAR Speckle Filtering Using Selective Threshold in Directionalet Domain

SAR speckle filtering is an important research subject. An ideal algorithm should smooth the Speckle without blurring texture and fine detail. A new speckle filtering method, using selective threshold in directionalet domain, is proposed. Image was decomposed and transformed in 12 directions by using multi-directional frames of directionalet. According to the characteristics of different length pixel sequences, the pixel sequences are divided into three groups and dealt with different threshold method respectively by Gaussian noise statistical distribution interval. To retain many fine details in the image, the median of high frequency coefficients variance is used as noise variance estimate value in every scale. A real SAR image is used in the experimentation. The result shows that the proposed method outperforms several classical speckle reduction algorithms in visual quality. ENL and ESI are enhanced by 97 and 0.15.