基于形态Haar小波的SAR图像斑点噪声抑制方法

针对现有相干斑抑制算法不能在去除斑点噪声和保持图像边缘、细节信息之间做到很好的折中,提出了一种新的基于形态Haar小波变换的合成孔径雷达(SAR)图像斑点噪声抑制方法。该方法首先对SAR图像进行二维形态Haar小波分解,图像的边缘、细节和纹理信息在低频子带中得到了更好的保留,噪声主要分布在高频子带;然后,根据各高频子带噪声的特点,分别对高频子带进行均值和中值滤波达到去除斑点噪声的目的;最后,再对低频子带和处理后的高频子带进行形态Haar小波精确重构得到去斑图像。实验证明:该算法不仅大大改善了原始SAR图像的画面质量,同时很好地保持了原始SAR图像的纹理特性和细节信息;该算法去斑性能指标总体优于传统的Lee滤波、Frost滤波、Kuan滤波和小波软阈值法。

Speckle reduction of SAR image based on morphological Haar wavelet

The existing speckle reduction algorithms of Synthetic Aperture Radar(SAR) image can efficiently reduce the speckle effects but unfortunately smear edges and details.A new method,based on morphological Haar wavelet,was proposed.In this method,the SAR image was firstly decomposed by 2-D morphological Haar wavelet.Thus,the edges,details and textures were well preserved in low-frequency sub-band.The speckle noise was mainly distributed in high-frequency sub-bands.Then,the average filtering and median filtering were run on the corresponding high frequency sub-bands according to the noise features.Finally,2-D morphological Haar wavelet inverse transform was carried on to low-frequency sub-band coefficients and filtered high-frequency sub-bands coefficients to reconstruct SAR image accurately.The experimental results show that the proposed method can not only filter the speckle noise efficiently,but well preserve the image textures and details of SAR image.The proposed method is better than the traditional Lee filtering,Frost filtering,Kuan filtering and wavelet soft-threshold overall.