摘要
提出一种SAR图像相干斑噪声抑制新的滤波方法。该方法利用小波变换结合主分量分析(PCA)对SAR图像进行去噪。小波变换可以很好地保持边缘细节信息,主分量分析(PCA)能从混合信号中提取出主分量即信号的主要特征,将小波变换结合PCA用于图像处理,能在有效消除噪声的同时保持边缘信息。与Kirsch模板加权平滑滤波和结合小波变换的Kirsch模板加权平滑滤波去噪方法进行比较,实验结果表明,该方法具有良好的抑制相干斑噪声效果和较强的边缘保持能力。
This paper puts forward a new method of speckle suppression in SAR image.The method gets rid of noises using of wavelet transform joining into Principal Components Analysis（PCA） processing for SAR image. Wavelet transform may keep the edges＇ information of image better, and PCA can draw out of PCs which are the primary characteristics of signals from the mixed signals. Togethering wavelet transform with the PCA can eliminate noises efficiently in image processing. Simultaneously, it can keep edge. Compared with Kirsch template weighted smoothing filtering and Kirsch template weighted smoothing filtering of adding into wavelet transform, the result shows this method has the better advantage in speckle suppression and stronger edge keeping.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第20期235-237,共3页
Computer Engineering
关键词
SAR图像
主分量分析
相干斑抑制
小波变换
SAR image
Principal Components Analysis（PCA）
speckle suppression
wavelet transform
