Speckle Denoising With NL Filter and Stochastic Distances Under the Haar Wavelet Domain

Pedro A. A. Penna, N. Mascarenhas
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引用次数: 1

Abstract

Synthetic aperture radar SAR imaging systems have a coherent processing that causes the appearance of the multiplicative speckle noise. This noise gives a granular appearance to the terrestrial surface scene impairing its interpretation. The similarity between patches approach is applied by the current state-of-the-art filters in remote sensing area. The goal of this manuscript is to present a method to transform the non-local means (NLM) algorithm capable to mitigate the noise. Singlelook speckle and the NLM under the Haar wavelet domain are considered in our research with intensity SAR images. To achieve our goal, we used the Exponential-Polynomial (EP) and Gamma distributions to describe the Haar coefficients. Also, stochastic distances based on these two mentioned distributions were formulated and embedded in the original NLM technique. Finally, we present analyses and comparisons of real scenarios to demonstrate the competitive performance of the proposed method with some recent filters of the literature.
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Haar小波域下基于NL滤波和随机距离的散斑去噪
合成孔径雷达SAR成像系统的相干处理导致了乘性散斑噪声的出现。这种噪声使地表景象呈现颗粒状,影响了其解释。在遥感领域,目前最先进的滤波器采用了斑块相似性方法。本文的目的是提出一种能够减轻噪声的非局部均值(NLM)算法的变换方法。本文研究了高强度SAR图像的单面散斑和Haar小波域下的NLM。为了实现我们的目标,我们使用指数多项式(EP)和Gamma分布来描述Haar系数。此外,基于这两种分布的随机距离被制定并嵌入到原始的NLM技术中。最后,我们提出了真实场景的分析和比较,以证明所提出的方法与一些最近的文献过滤器的竞争性能。
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