基于高斯混合模型图像局部自适应去噪算法  

Image denoising based on local-adaptive Gaussian scale mixture model

作　　者：刘卫华[1] 何明一[1] 

机构地区：[1]西北工业大学电子信息学院信息获取与处理陕西省重点实验室,陕西西安710129

出　　处：《系统工程与电子技术》2009年第12期2806-2808,共3页Systems Engineering and Electronics

基　　金：国家自然科学基金(60736007)资助课题

摘　　要：针对传统阈值小波去噪方法未考虑小波域尺度内和尺度间系数相关性的问题,采用基于小波域统计模型的新型去噪方法,图像小波域的先验统计模型采用高斯混合尺度模型。在计算信号的协方差矩阵时,对图像分块并用椭圆窗滑动求局部协方差矩阵,以达到局部自适应的去噪目的。实验表明,该方法与在子带内求协方差矩阵的方法相比,去噪效果有所提高。The traditional wavelet-denoising is based on a selection of the threshold,but a new method based on statistical model in wavelet domain is presented,in which the prior statistical model is Gaussian scale mixture model.When the signal covariance is calculated,the image is cut into several blocks and the elliptic window is used,so the local covariance is achieved.Experiments results show that the performance of the proposed method is higher than the method which calculates the covariance in subband.

关 键 词：高斯混合尺度模型 小波变换 局部自适应 椭圆窗 

分 类 号：TN911[电子电信—通信与信息系统]