基于多尺度自适应小波阈值的SAR图像降噪

为了抑制合成孔径雷达(synthetic aperture radar,SAR)成像系统所固有的相干斑噪声,提出一种小波域的多尺度自适应阈值滤波算法.本算法基于BayesShrink阈值,利用多尺度小波系数的局部统计量估计参数和阈值,并结合空域增强Lee算法的思想,平滑均匀区域,保留斑点发育不完全区域.实验结果表明,相对于传统的空域滤波算法、小波软阈值去噪算法和BayesShrink软阈值算法,本算法等效视数(equivalent number of looks,ENL)和边缘保持指数最高,能有效抑制斑点噪声,并且很好地保存了边缘细节。

SAR Image Despeckling Based on Multi-scales Adaptive Wavelet Thresholding

An improved algorithm based on wavelet thresholding is proposed for suppressing speckle noise of synthetic aperture radar image.The method uses the local statistics of multiscale wavelet coefficients to obtain estimated parameters and thresholds based on BayesShrink threshold.Moreover,it employs the method of enhanced Lee filter to smooth the homogeneous areas and preserve the point-target areas.Results demonstrate that compared with the results of enhanced Lee filter,traditional soft-thresholding of discrete wavelet transform(DWT) and BayesShrink soft-thresholding,the improved algorithm provides the largest equivalent number of looks(ENL) and edge sustain index(ESI),which indicates it can not only reduce the speckle but also preserve edges and details.