一种改进的非凸正则项模型的噪声去除方法

›› 2013, Vol. 26 ›› Issue (11): 71-.

一种改进的非凸正则项模型的噪声去除方法

余婷,张振山

(西安电子科技大学理学院,陕西西安 710071)

出版日期:2013-11-15 发布日期:2013-11-19
作者简介:余婷(1990—),女,硕士研究生。研究方向:多尺度分析理论及其在图像处理中的应用。E-mail:18789401759@163.com。张振山(1986—),男,硕士研究生。研究方向:多尺度分析理论及其在图像处理中的应用。

An Improved Method for Multiplicative Noise Removal Based on the Nonconvex Regularization Model

YU Ting,ZHANG Zhenshan

(School of Science,Xidian University,Xi'an 710071,China)

Online:2013-11-15 Published:2013-11-19

摘要/Abstract

摘要：

针对非凸正则项模型,在去除乘性噪声时边缘信息对噪声敏感且强度较大的噪声抑制能力弱的缺陷,提出了一种改进的图像去噪新模型。在新模型中通过取对数将乘性噪声转变成加性噪声,然后在模型的正则项和忠诚项中均引入高斯卷积,既对图像进行平滑预处理,又获得丰富的边缘信息,从而对边缘作出精确定位,使新模型具有良好的鲁棒性并根据图像的特征进行平滑,因而更好地保护了图像的边缘。数值实验表明,新方法的去噪结果在定量指标上有大幅提高,视觉效果上也有较大改善,尤其是对强度较大的噪声,新方法的优势更突出。

关键词: 图像去噪, 非凸正则项, 高斯卷积, 交替极小化

Abstract:

In view of the fact that non-convex regularization model is sensitive to noise in removing multiplicative noise and the suppression capability is weak for greater intensity noise,an improved image denoising model is proposed.In the new model,multiplicative noise is first transformed into additive noise by Logarithmic transformation,and Gaussian convolution is then introduced into the regularization term and the fidelity term for smooth image preprocessing and more details of edge so that the edge is located accurately.The new model is robust and can smooth according to the characteristics of the image,and therefore the edges are better preserved.Numerical experiments show that the new method of denoising results has a greatly increase on quantitative indicators and a remarkable improvement on the visual effect.The new method has distinct advantages especially for large noise.

Key words: image denoising;nonconvex regularization term;gaussian convolution;alternating minimization

中图分类号:

TN911.73

余婷,张振山. 一种改进的非凸正则项模型的噪声去除方法[J]. , 2013, 26(11): 71-.

YU Ting,ZHANG Zhenshan. An Improved Method for Multiplicative Noise Removal Based on the Nonconvex Regularization Model[J]. , 2013, 26(11): 71-.

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