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Comparison of wavelet-based and statistical speckle filters

机译:基于小波和统计散斑滤波器的比较

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The wavelet transform has become a very popular tool in signal and image processing. Over the last few years, several authors have proposed wavelet-based filters for speckle reduction in SAR*images, and the results are generally reported to be superior to those obtained with traditional statistical speckle filters. In this paper we give a thorough experimental comparison of representative filters from both categories. We show that spatially adaptive statistical filters yield better noise reduction and preservation of structures than wavelet- based methods, but that the latter have certain advantages compared to statistical filters which are not spatially adaptive.
机译:小波变换已成为信号和图像处理中非常流行的工具。在过去几年中,一些作者提出了基于小波的过滤器,用于SAR *图像的散斑减少,并且通常报道结果优于传统统计斑块过滤器的结果。在本文中,我们提供了两种类别的代表过滤器进行了彻底的实验比较。我们表明空间自适应统计过滤器产生的噪音减少和保护结构的保存比基于小波的方法,但与在空间透明的统计过滤器相比,后者具有某些优点。

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