基于最小线性均方估计的小波去噪算法  

Wavelet De-noising Algorithm Based on LMS Estimation

作　　者：朱文涛[1] 付炜[1] 

机构地区：[1]燕山大学信息科学与工程学院,河北秦皇岛066004

出　　处：《现代电子技术》2010年第12期121-124,共4页Modern Electronics Technique

基　　金：河北省教育厅自然科学基金项目(2003114)

摘　　要：提出一种新的基于最小线性估计正交小波图像去噪算法。该算法把降噪过程直接看作是一个小波系数的加权和,而不是为小波系数假设一个统计模型。在此,基于最小线性均方估计构造去噪函数,然后最小化均方误差,得到一组估计参数,从而得到线性去噪函数,实现对非线性去噪算法的改进,其最大的好处就是不用先验知识;最后通过使用该去噪算法对一定噪声级数的标准图像进行处理,并与目前去噪效果最好的BLS-GSM方法进行了比较。结果表明了该方法的有效性。A new orthogonal wavelet image de noising algorithm based on the least linear estimation is proposed. Instead of postulating a statistical model for the wavelet coefficients, the de-noising process was regarded as a sum of wavelet coefficients with unknown weights. Constructing de-noising function based on the least linear mean square estimation, then minimizing the mean square error, a group of estimation parameters can be acquired to construct the linear de-nosing function completing the improvement of no-linear de-nosing function. The most important advantage is that the priori knowledge is needless. Comparing with the result acquired by BLS-GSM over a suitable range of noise levels for a standard image, the result acquired by using this proposed approach.

关 键 词：均方误差 小波系数 去噪 线性估计 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]