A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage
A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage
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DOI：
10.1109/tgrs.2011.2161586
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发表时间：
2012-02-01
影响因子：
8.2
通讯作者：
Verdoliva, Luisa
中科院分区：
文献类型：
--
作者：
Parrilli, Sara;Poderico, Mariana;Verdoliva, Luisa
提出了一种基于非局部滤波和小波域收缩概念的合成孔径雷达（SAR）图像相干斑抑制算法。它遵循的块匹配的3-D算法，最近提出的加性白色高斯噪声去噪的结构，但修改其主要的处理步骤，以考虑到SAR图像的特点。一个概率相似性度量用于块匹配步骤，而小波收缩开发使用加性信号相关的噪声模型，并寻找最佳的局部线性最小均方误差估计在小波域。所提出的技术相比有利w.r.t.几个国家的最先进的参考技术，具有更好的结果，无论是在信号噪声比（在模拟斑点图像）和感知图像质量。
We propose a novel despeckling algorithm for synthetic aperture radar (SAR) images based on the concepts of nonlocal filtering and wavelet-domain shrinkage. It follows the structure of the block-matching 3-D algorithm, recently proposed for additive white Gaussian noise denoising, but modifies its major processing steps in order to take into account the peculiarities of SAR images. A probabilistic similarity measure is used for the block-matching step, while the wavelet shrinkage is developed using an additive signal-dependent noise model and looking for the optimum local linear minimum-mean-square-error estimator in the wavelet domain. The proposed technique compares favorably w.r.t. several state-of-the-art reference techniques, with better results both in terms of signal-to-noise ratio (on simulated speckled images) and of perceived image quality.