期刊论文

Guo, J.(jmguo@sgg.whu.edu.cn)

中文

测绘学报

1001-1595

2013

42

5

707-714

中央高校基本科研业务费专项资金（2012214020209） 湖南省教育厅科研基金（12C0566）

本校为其他机构

基于信号和噪声经过经验模态分解后在不同的IMF上有不同的特征,提出一种基于EMD-自适应滤波干涉图去噪方法。该方法先对信号进行经验模态分解,然后对各个高频IMF信号分别选用不同的滤波梯度参数进行自适应滤波处理,从初始干涉图上减去与噪声所对应尺度信息,从而达到抑制噪声的目的。最后通过试验对比研究该算法与Goldstein滤波、圆周期中值滤波、EMD分解方法、梯度-自适应滤波和Baran滤波去噪的降噪效果。试验表明,该方法在有效地抑制InSAR干涉图噪声的同时,能很好地保持相位的细节和条纹的边缘信息。

In view of different characteristics in different intrinsic mode function (IMFS) after signal and noise were decomposed by empirical mode decomposition (EMD), a new adaptive filter method based on empirical mode decomposition for reducing interferometric phase noises was proposed. At first the signals were decomposed by empirical mode decomposition, and different high-frequency IMF signals were separately processed by adaptive filter with different filter gradient parameter, and then the scale information corresponding to the noises was subtracted from the original interferogram so as to achie...