基于Gauss滤波和Euler修复模型的SAR图像去噪
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Speckle Removement of SAR Image Based on Euler′s Elastica Model and Gauss Filtering
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    摘要:

    针对二阶偏微分模型(Total variation,TV) 在合成孔径雷达(Synthetic aperture radar,SAR)图像去噪时会产生阶梯效应的问题, 结合Euler修复正则项的优点,提出一种基于Euler修复正则项的高阶变分模型应用到图像去 噪。为有效求解模型,采用加性算子分裂(Additive operating splitting,AOS)方法进 行数值离散。迭代方式为半隐式 ,克服了显示格式对步长的限制。试验结果表明,仿真实验取得了很好的效果,而对真实的 SAR图像,去噪图像会有明显的孤立大颗粒噪声存在,使视觉效果不好。针对此问题,本文 又 提出一种将Gauss滤波和Euler修复模型相结合的复合模型,数值实验表明,该方法有效地 消除了大颗粒噪声,阶梯效应也被有效抑制。

    Abstract:

    To tackle the staircase effect pro blem of classical total variational models(TV) in SAR image d enoising, a high order variational model based on Euler′s elasti c a model is proposed, taking advantage of Euler′s elastica and impainting regula rized term. A numerical additive operating splitting (AOS) scheme is us ed to discre tize the image, which overcomes the time step size restriction for explicit sche m e. Experimental results show that the proposed model performs well in simulation, while leaving isolated particles on SA R imag e. To solve the problem, the proposed method is complemented through Gauss filtering in conjunction with the proposed model. Results verify that the pr oposed method can eliminate the large particles effectively and suppress the staircase effect with a high equivalent numbe r of looks (ENL).

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王田芳;李浩;温四林;崔成玲.基于Gauss滤波和Euler修复模型的SAR图像去噪[J].数据采集与处理,2016,31(3):562-569

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  • 在线发布日期: 2016-06-24