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A Non Local Approach to De-noise SAR Images Using Compressive Sensing Method

机译:使用压缩感测方法将非局部致噪声SAR图像的方法

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De noising of Synthetic Aperture Radar (SAR) images has gained a lot of attention lately. Many researchers have proposed different techniques to de noise SAR images among which non local approaches provided better results. Other techniques like graph cut method and compressive sensing method provided significant improvement in parameters used for enhancement of a SAR image. Compressive sensing requires the image to be sparse that is added through the speckle noise in the original image, the image should be compressed before sensing i.e. it is under sampling the image below some threshold value. Further we are applying BM3D filter to de-noise the corrupted image. This paper summarizes the compressive sensing method with a BM3D chosen as Non Local mean. The results are tabulated in comparison to SAR BM3D with different amounts of speckle content.
机译:最近的合成孔径雷达(SAR)图像的通知最近越来越大。许多研究人员提出了不同的技术来解除噪声SAR图像,其中非本地方法提供更好的结果。图形切割方法和压缩检测方法等其他技术提供了用于增强SAR图像的参数的显着改进。压缩检测要求图像通过原始图像中的散斑噪声添加稀疏,在感测之前应该压缩图像。它在将图像上采样以下阈值。此外,我们正在应用BM3D过滤器来解除损坏的图像。本文总结了作为非本地均值选择的BM3D的压缩感测方法。与SAR BM3D具有不同量的散斑含量的SAR BM3D表示结果。

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