摘要
贝叶斯估计理论在图像处理领域有广泛的应用.结合图像去噪问题,讨论了贝叶斯最大后验概率估计技术,并推导了信号的最小均方误差估计;在此基础上,提出了一种利用后验均值准则推导维纳滤波表达式的方法.
Bayesian estimation theory has been widely used in the field of image processing. In this paper, the estimation technique by Bayesian Maximum A Posteriori (MAP) is investigated with respect to the issue of image denoising, and the formula of the Minimum Mean Squared Error (MMSE)-like estimation is derived. Based on the discussion, a method is proposed which can deduce Wiener filtering formula by using Posterior Mean criteria.
出处
《西南民族大学学报（自然科学版）》
CAS
2006年第3期591-594,共4页
Journal of Southwest Minzu University(Natural Science Edition)
基金
中南民族大学教学研究项目.
关键词
贝叶斯估计
最大后验估计
后验均值准则
维纳滤波
最小均方误差估计
Bayesian estimation
Maximum A Posteriori estimation
Posterior Mean criteria
Wiener filtering
Minimum Mean Squared Error estimation
