J4 ›› 2013, Vol. 51 ›› Issue (02): 289-293.

• 计算机科学 • 上一篇    下一篇

一种基于最大后验概率与图像局部统计量的磁共振图像去噪模型

王洋1,2, 左平3   

  1. 1. 吉林大学 公共计算机教学与研究中心, 长春 130012|2. 吉林大学 计算机科学与技术学院, 长春 130012;3. 空军航空大学 基础部, 长春 130022
  • 收稿日期:2012-09-12 出版日期:2013-03-26 发布日期:2013-03-27
  • 通讯作者: 左平 E-mail:nancy98.good@163.com

A Variational Model Based on Maximum Posterior Probability forRestoration of MR Images Corrupted by Rician Noise

WANG Yang1,2, ZUO Ping3   

  1. 1. Center for Computer Fundamental Education, Jilin University, Changchun 130012, China;2. College of Computer Science and Technology, Jilin University, Changchun 130012, China;3. Department of Foundation, Aviation University of Air Force, Changchun 130022, China
  • Received:2012-09-12 Online:2013-03-26 Published:2013-03-27
  • Contact: ZUO Ping E-mail:nancy98.good@163.com

摘要:

提出一种基于最大后验概率与图像局部统计量的磁共振图像去噪模型. 该模型针对射频场所引起的磁共振图像灰度值不均匀问题, 将在Rician噪声模型下的最大后验估计与全变差正则化模型相结合, 在模型中引入了瞬时变化系数. 根据Euler-Lagrange方程, 给出了模型的解及方程解的离散形式. 数值实验验证了所提算法的有效性.

关键词: 磁共振图像, 图像去噪, 全变差模型, 最大后验估计

Abstract:

We proposed a variational model to restore images degraded by Rician noise. This model was established by considering  total variation regularization with a fidelity term involving the Rician probability distribution and instaneous variation coefficient. The quantitative and the qualitative measures used as the quality metrics demonstrate the ability of the proposed method for noise suppression.

Key words: magnetic resonance imaging, image denoising, total variation model, maximum posterior probability estimation

中图分类号: 

  • TP391