SAR图像斑点噪声整体变分偏微分方程滤波算法研究

李  贺; 秦志远; 周丽雅

doi:10.11834/jig.20100609

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SAR图像斑点噪声整体变分偏微分方程滤波算法研究
Study on SAR Image Speckle Noise Smoothing Algorithm with TV-PDE
2010年15卷第6期页码：910
纸质出版：2010
DOI： 10.11834/jig.20100609
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李贺, 秦志远, 周丽雅. SAR图像斑点噪声整体变分偏微分方程滤波算法研究[J]. 中国图象图形学报, 2010,15(6):910. DOI： 10.11834/jig.20100609.

LI He, QIN Zhiyuan, ZHOU Liya. Study on SAR Image Speckle Noise Smoothing Algorithm with TV-PDE[J]. Journal of Image and Graphics, 2010, 15(6): 910. DOI： 10.11834/jig.20100609.

摘要

SAR图像固有的斑点噪声严重影响了图像的判读和后续处理，因此抑制SAR图像斑点噪声显得尤其重要。一个良好的斑点噪声抑制算法应该在降低斑点噪声的同时，能很好地保持图像的细节特征，但现有的去噪算法没有一种能够完美地解决这个问题的。本文基于SAR图像斑点噪声滤波的重要性以及存在的问题，将整体变分偏微分方程用于去除斑点噪声。根据整体偏微分方程建立了去噪模型，并分析了模型的性能和参数选择的重要性。通过实验验证了该算法的有效性，并以峰值信噪比（PSNR）为评价准则，利用多项式拟合方法选择了最优参数。引入边缘保持指数(EPI)，与其他滤波算法比较，本算法在去除噪声的同时较好地保持了边缘。

Abstract

The inherent speckle noise of SAR image affects the interpretation and the further processing，so it is important to suppress speckle noise of SAR images. A nice speckle filter would be preserving details while suppressing the noise. But now none of the existent filters can solve this problem ideally. TV-PDE(Total Variation Partial Differential Equation) was introduced to denoise speckle noise because is important to reduce the speckles for SAR image. The mathematical model for denoise was built and then the capability of this model was analyzed and also the importance of selecting preference. Experiments proved the validity of the model. Taking Peak Signal-to-Noise Ratio(PSNR) as criterion the best preference was found by using polynomial fitting. The model preserved the edge when denoise the speckle better comparing with other algorithms according to EPI(Edge Preserved Index).