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小波支持向量机在SAR图像降噪中的应用
引用本文:张绍明,陈鹰,林怡.小波支持向量机在SAR图像降噪中的应用[J].计算机工程与应用,2008,44(3):214-216.
作者姓名:张绍明  陈鹰  林怡
作者单位:同济大学,遥感与空间信息技术研究中心,上海,200092
摘    要:基于支持向量回归理论和小波支持向量核函数,提出了一种新的SAR滤波方法。首先对支持向量回归方法做了分析,通过对复杂信号进行逼近实验,验证了其应用于图像滤波的可行性和合理性。之后将SAR图像看成是一个二维连续信号,将对复杂信号具有更好逼近能力的小波支持向量核函数用于SAR图像滤波,小波核函数由Morlet小波构建。实验结果表明本文提出的方法能很好的降低SAR图像噪声,而且能比传统方法更好的保持边缘。

关 键 词:合成孔径雷达  支持向量机  核函数  小波分析  函数逼近
文章编号:1002-8331(2008)03-0214-03
修稿时间:2007年7月1日

Application of wavelet support vector machine on SAR image denoising
ZHANG Shao-ming,CHEN Ying,LIN Yi.Application of wavelet support vector machine on SAR image denoising[J].Computer Engineering and Applications,2008,44(3):214-216.
Authors:ZHANG Shao-ming  CHEN Ying  LIN Yi
Affiliation:Research Center of Remote Sensing and Spatial Technology,Tongji University,Shanghai 200092,China
Abstract:A new filtering method for Synthetic Aperture Radar image is presented based on support vector regression and wavelet kernel function.The feasibility of SAR image fitting based on support vector machine is proved based on the analysis for support vector regression and the experiment of signal filtering.Then the SAR image is regarded as 2-dimension continuous signal and filtered by support vector regression with wavelet kernel function.The wavelet kernel is constructed by Morlet mother wavelet function.The results of experiment show that the method proposed in this paper could reduce the noise effective and keep the edge better than traditional ones.
Keywords:Synthetic Aperture Radar(SAR)  support vector machine  kernel function  wavelet analysis  function approximation
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