Image registration algorithm based on generalized mutual information

ZHANG Zhen1; CAO Yun-feng2; DING Meng1; FENG Cheng-tao1

doi:10.13873/j.1000-97872008.04.016

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Image registration algorithm based on generalized mutual information

更新时间：2025-09-11

- Image registration algorithm based on generalized mutual information
- Issue 4, Pages: 108-110(2008)
- 作者机构：
  
  1. 南京航空航天大学自动化学院
  2. 南京航空航天大学高新技术研究院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872008.04.016
  CLC： TP391.41
- Published：2008
- 稿件说明：
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[1]张珍,曹云峰,丁萌,冯成涛.一种基于广义互信息的图像配准算法[J].传感器与微系统,2008(04):108-110.

ZHANG Zhen1, CAO Yun-feng2, DING Meng1, et al. Image registration algorithm based on generalized mutual information[J]. 2008, (4): 108-110.
[1]张珍,曹云峰,丁萌,冯成涛.一种基于广义互信息的图像配准算法[J].传感器与微系统,2008(04):108-110. DOI： 10.13873/j.1000-97872008.04.016.

ZHANG Zhen1, CAO Yun-feng2, DING Meng1, et al. Image registration algorithm based on generalized mutual information[J]. 2008, (4): 108-110. DOI： 10.13873/j.1000-97872008.04.016.

摘要

互信息作为图像配准中的相关度矩阵有着广泛的应用

通常采用的是基于Shannon熵的互信息。采用一个广义的信息熵——Renyi熵

提出了一种基于广义互信息的图像配准方法。在全局搜索阶段

采用q取较小值的Renyi熵

此时

Renyi熵可以消除局部极值

再通过局部优化方法对当前的局部最优解进行局部寻优

以找到全局最优解;在局部优化阶段

使用基于q→1时的Renyi熵的归一化互信息测度作为目标函数。实验结果表明:相对于归一化互信息图像配准算法

基于Renyi熵的互信息配准算法有良好的配准效果

且提高了配准速度。

Abstract

Mutual information is widely used as a similarity metric for image registration.Usually similarity metric is based on Shannon definition of entropy.One generalized entropy named as Renyi entropy is used and a new image registration algorithm is proposed based on generalized mutual information.Firstly Renyi entropy with smaller q is used for global searches

here Renyi entropy can remove some unwanted local optimum;secondly

the local one is used to locate the global optimal solution by searching the current local optimal ones.The normalized mutual information measure based on Renyi entropy with q→1 is taken as the objective function.The experiment results show that the mutual information image registration algorithm based on Renyi entropy is better than the normalized mutual informatron image registration algorithm

and the speed of registration is improved.

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Keywords

references

基于混合互信息的医学图像配准 [J]. 张红颖,张加万,孙济洲. 计算机应用 . 2006(10)

基于边界距离场互信息的图像配准方法 [J]. 张见威,韩国强,沃焱. 通信学报 . 2006(07)

MATLAB 6.x图像处理[M]. 清华大学出版社 , 孙兆林编著, 2002

Image registration methods: a survey [J] . Barbara Zitová,Jan Flusser. Image and Vision Computing . 2003 (11)

An overlap invariant entropy measure of 3D medical image alignment [J] . C. Studholme,D.L.G. Hill,D.J. Hawkes. Pattern Recognition . 1999 (1)

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