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A non local approach to de-noise SAR images using compressive sensing method

机译:使用压缩感测方法对SAR图像进行去噪的非局部方法

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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:合成孔径雷达(SAR)图像的去噪最近引起了很多关注。许多研究人员提出了不同的技术来对SAR图像进行去噪,其中非局部方法提供了更好的结果。其他技术(例如图形切割方法和压缩感测方法)在用于增强SAR图像的参数方面提供了显着改善。压缩感测要求图像是稀疏的,该图像是通过原始图像中的斑点噪声添加的,因此图像应在感测之前进行压缩,即,它在对图像进行采样时低于某个阈值。此外,我们将应用BM3D滤波器对损坏的图像进行消噪。本文总结了以BM3D作为非局部均值的压缩感知方法。与具有不同斑点含量的SAR BM3D相比,结果列于表中。

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