基于隐式马尔科夫参数模型的图像消噪研究  

Image's denoising research based on hidden Markov parameter model

作　　者：李宏升[1] 徐洪章[1] 

机构地区：[1]黄淮学院,河南驻马店463000

出　　处：《激光与红外》2013年第10期1184-1187,共4页Laser & Infrared

摘　　要：针对隐式马尔科夫模型在图像消噪中的不足,采用参数求解方法。首先对参数模型三元组确定其限制条件,通过递归计算状态概率,通过最大似然估计来使期望最大化,期望最大化过程包括期望过程和最大化过程;在图像消噪中提取观察信号过程利用Kullback-Leibler距离设置其阈值,最终给出了参数解。实验仿真表明本文算法能够保持图像有用信息,执行速度快。Aiming at Hidden Markov model＇ s disadvantages in image denoising, parameter solving method is used. Firstly for the parametric model of ternary group its restrictions are determined, state probability is computed with recursive function, expectation maximization is made by using maximum likelihood estimation. The process includes expectation and maximization. In image denoising,its threshold is set through Kullback-Leibler distance. Finally the parameter solution is given. Simulation results show that the proposed algorithm can keep the useful information of the image, and computation speed is fast.

关 键 词：隐式马尔科夫 参数 消噪 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]