A Note on Mixture Bivariate Model

摘要：

L. Sendur and I. W. Selesnick suggest four jointly non-Gaussian bivariate models to characterize the dependency between a coefficient and its parent, and respectively derive the corresponding MAP estimators based on noisy wavelet coefficients in detail in |6|. Among the four models, the second is a mixture model and it is quite complicated to evaluate parameters, so L. Sendur and I.W. Selesnick didnt give a concrete method. In this letter, a concrete mixture bivariate model will be described by drawing inspiration from Model 2. Expectation maximization (EM) algorithm is employed to find the parameters of new model. The simulation results show that the values of PSNR have a bit improvement compared with Model 1. The results can be viewed as a supplementary

关键词： Imagedenoising Mixturebivariatemodel Bayesian estimator Expectation maximization algorithm

作者: Hanwen Cao Wei Tian Chengzhi Deng

作者单位: Department of Science Nanchang Institute of Technology Nanchang, China School of Information Engineering Nanchang Institute of Technology Nanchang, China

会议类型: 国际会议

会议名称: 2010 International Conference on Signal and Information Processing(2010年IEEE信号与信息处理国际会议 ICSIP2010)

会议地点: 长沙

会议语种:英文

页码: 62-65

在线出版日期: 2010-12-14（万方平台首次上网日期，不代表论文的发表时间）