IMAGE REGISTRATION BY AUTOMATIC SUBIMAGE SELECTION AND MAXIMIZATION OF COMBINED MUTUAL INFORMATION AND SPATIAL INFORMATION

被引：1
|
作者：
Amankwah, Anthony [1 ]
机构：
[1] Univ Witwatersrand, Sch Comp Sci, Johannesburg 2050, South Africa
来源：
2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年
关键词：
Enhance mutual information; subimage; image registration;
D O I：
10.1109/IGARSS.2013.6723805
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Image registration is one of the most important steps in the analysis of remotely sensed data. Mutual information is a robust similarity metric in image registration. Unfortunately mutual information neglects spatial information. In this work, we propose a new similarity metric for image registration called enhanced mutual information (EMI), which combines mutual information with a weighting function based on the absolute difference of corresponding pixel values. We also use subimages with high entropy as a search data strategy Experimental results show that our proposed method was more robust to noise and accurate than the standard methods used.
引用
收藏
页码：4379 / 4382
页数：4
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