Multiplicative noise removal using primal-dual and reweighted alternating minimization.
Multiplicative noise removal using primal-dual and reweighted alternating minimization.
复制标题
使用原始对偶和重新加权交替最小化来消除乘性噪声
DOI：
10.1186/s40064-016-1807-3
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Huo L
中科院分区：
文献类型：
--
作者：
Wang X;Bi Y;Feng X;Huo L
乘性噪声去除是图像处理领域的一个重要研究课题。在我们的初步工作中，提出了一种利用重加权交替最小化来去除这类噪声的算法。在获得良好结果的同时，需要一个较小的参数来避免分母消失。结果表明，参数对数值结果有重要影响，必须慎重选择。本文设计了一种不需要人工参数的原始对偶算法。数值实验表明，该算法在保持高信噪比的同时，能获得较好的视觉质量，克服阶梯效应，保留边缘。
Multiplicative noise removal is an important research topic in image processing field. An algorithm using reweighted alternating minimization to remove this kind of noise is proposed in our preliminary work. While achieving good results, a small parameter is needed to avoid the denominator vanishing. We find that the parameter has important influence on numerical results and has to be chosen carefully. In this paper a primal–dual algorithm is designed without the artificial parameter. Numerical experiments show that the new algorithm can get a good visual quality, overcome staircase effects and preserve the edges, while maintaining high signal-to-noise ratio.