Mutual Information Optimization Based Dynamic Log-Polar Image Registration

doi:10.1007/s12204-015-1589-8

上海交通大学学报（英文版） ›› 2015, Vol. 20 ›› Issue (1): 61-67.doi: 10.1007/s12204-015-1589-8

Mutual Information Optimization Based Dynamic Log-Polar Image Registration

ZHANG Kui* (张葵), ZHANG Xiao-long (张晓龙), XU Xin (徐新), FU Xiao-wei (付晓薇)

(Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430081, China)

出版日期:2015-02-28 发布日期:2015-03-10
通讯作者: ZHANG Kui (张葵) E-mail:zhangkui@wust.edu.cn

Mutual Information Optimization Based Dynamic Log-Polar Image Registration

ZHANG Kui* (张葵), ZHANG Xiao-long (张晓龙), XU Xin (徐新), FU Xiao-wei (付晓薇)

(Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430081, China)

Online:2015-02-28 Published:2015-03-10
Contact: ZHANG Kui (张葵) E-mail:zhangkui@wust.edu.cn

摘要/Abstract

摘要： Log-polar transformation (LPT) is widely used in image registration due to its scale and rotation invariant properties. Through LPT, rotation and scale transformation can be made into translation displacement in log-polar coordinates, and phase correlation technique can be used to get the displacement. In LPT based image registration, constant samples in digitalization processing produce less precise and effective results. Thus, dynamic log-polar transformation (DLPT) is used in this paper. DLPT is a method that generates several sample sets in axes to produce several results and only the effective results are used to get the final results by using statistical approach. Therefore, DLPT can get more precise and effective transformation results than the conventional LPT. Mutual information (MI) is a similarity measure to align two images and has been used in image registration for a long time. An optimal transform for image registration can be obtained by maximizing MI between the two images. Image registration based on MI is robust in noisy, occlusion and illumination changing circumstance. In this paper, we study image registration using MI and DLPT. Experiments with digitalizing images and with real image datasets are performed, and the experimental results show that the combination of MI with DLPT is an effective and precise method for image registration.

关键词: image registration, mutual information (MI), log-polar transformation (LPT), phase correlation technique

Abstract: Log-polar transformation (LPT) is widely used in image registration due to its scale and rotation invariant properties. Through LPT, rotation and scale transformation can be made into translation displacement in log-polar coordinates, and phase correlation technique can be used to get the displacement. In LPT based image registration, constant samples in digitalization processing produce less precise and effective results. Thus, dynamic log-polar transformation (DLPT) is used in this paper. DLPT is a method that generates several sample sets in axes to produce several results and only the effective results are used to get the final results by using statistical approach. Therefore, DLPT can get more precise and effective transformation results than the conventional LPT. Mutual information (MI) is a similarity measure to align two images and has been used in image registration for a long time. An optimal transform for image registration can be obtained by maximizing MI between the two images. Image registration based on MI is robust in noisy, occlusion and illumination changing circumstance. In this paper, we study image registration using MI and DLPT. Experiments with digitalizing images and with real image datasets are performed, and the experimental results show that the combination of MI with DLPT is an effective and precise method for image registration.

Key words: image registration, mutual information (MI), log-polar transformation (LPT), phase correlation technique

中图分类号:

TP 391.4

ZHANG Kui* (张葵), ZHANG Xiao-long (张晓龙), XU Xin (徐新), FU Xiao-wei (付晓薇). Mutual Information Optimization Based Dynamic Log-Polar Image Registration[J]. 上海交通大学学报（英文版）, 2015, 20(1): 61-67.

ZHANG Kui* (张葵), ZHANG Xiao-long (张晓龙), XU Xin (徐新), FU Xiao-wei (付晓薇). Mutual Information Optimization Based Dynamic Log-Polar Image Registration[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(1): 61-67.

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Mutual Information Optimization Based Dynamic Log-Polar Image Registration

Mutual Information Optimization Based Dynamic Log-Polar Image Registration

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