Multiplicative Noise Removal with Spatially Varying Regularization Parameters
Multiplicative Noise Removal with Spatially Varying Regularization Parameters
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DOI：
10.1137/090748421
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发表时间：
2010-01-01
影响因子：
2.1
通讯作者：
Shen, Chaomin
中科院分区：
文献类型：
--
作者：
Li, Fang;Ng, Michael K.;Shen, Chaomin
Aubert-Aujol（AA）模型是一种用于去除乘性噪声的变分方法。本文研究了AA模型中正则化参数的一些基本性质。提出了一种在乘性噪声去除过程中自动选择正则化参数的方法。特别是，我们采用空间变化的正则化参数的AA模型，以恢复更多的纹理细节的去噪图像。实验结果表明，空间变化的正则化参数的方法可以得到更好的去噪图像比其他测试的乘性噪声去除方法。
The Aubert-Aujol (AA) model is a variational method for multiplicative noise removal. In this paper, we study some basic properties of the regularization parameter in the AA model. We develop a method for automatically choosing the regularization parameter in the multiplicative noise removal process. In particular, we employ spatially varying regularization parameters in the AA model in order to restore more texture details of the denoised image. Experimental results are presented to demonstrate that the spatially varying regularization parameters method can obtain better denoised images than the other tested multiplicative noise removal methods.