非下采样小波域的四阶偏微分SAR图像去噪

SAR Image Denoising Using Fourth-order PDE Based on NSWT

针对合成孔径雷达(Synthetic Aperture Radar,SAR)图像受相干斑噪声的干扰会严重影响后续图像处理与分析的问题,提出了一种非下采样小波变换(NonSubsampled Wavelet Transform,NSWT)与四阶偏微分方程相结合的SAR图像去噪算法。首先利用NSWT将SAR图像分解为不同尺度、不同分辨率的高低频分量,然后利用四阶偏微分方程变换消除高频噪声,利用小波软阈值消除低频噪声,在去噪的同时能有效保留图像的边缘与细节,最后再利用NSWT逆变换进行重构。实验表明,该算法可以有效消除SAR图像的斑点噪声。

Speckle noise in synthetic aperture radar（SAR） images seriously affects the subsequent processing of SAR image. In order to solve this problem,a denoising method is presented for SAR image which combines fourth-order partial differential equation （PDE） and nonsubsampled wavelet transform （NSWT）. Firstly, the original SAR image is decomposed by NSWT to get the low-frequency subband and high-frequency subband image. The high-frequency noise in high-frequency subbandis removed by using fourth-order PDE and low-frequency noisein low frequency subband is removed by using soft-thresholding filtering. This operation could not only smooth speckle in the SAR image, but also retain the characteristics well. The effectiveness of the method is verified by the experiments with real SAR image.