Image fusion using Evolutionary algorithms: a Survey

被引:0
作者
Haritha, K. C. [1 ]
Jeyakumar, G. [1 ]
Thangavelu, S. [1 ]
机构
[1] Amrita Univ, Amrita Vishwa Vidyapeetham, Amrita Sch Engn Coimbatore, Dept Comp Sci & Engn, Coimbatore, Tamil Nadu, India
来源
2017 4TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATION SYSTEMS (ICACCS) | 2017年
关键词
Image fusion; Differential Evolution algorithm; Genetic Algorithm; Particle Swarm Optimization; Evolutionary algorithms; OPTIMIZATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper is mainly intended to compare image fusion method using different evolutionary algorithms and a comparison between these methods. The survey focuses on region-based fusion techniques, which is a major area of research. The paper compares image fusion processes using various evolutionary algorithms and illustrates the advantages and disadvantages of these algorithms. This survey illustrates that a method of image fusion can also be included in the DE optimization stage with the block size optimization. Finally, it is concluded that spatial frequency can be used as the sharpness criterion and Evolutionary algorithms perform better in block size optimization.
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收藏
页数:7
相关论文
共 35 条
[1]  
Anish A, 2012, INT J ADV RES COMPUT, V1, P2012
[2]  
Aslantas Veysel, 2014, Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics ICINCO 2014, P312
[3]   Fusion of multi-focus images using differential evolution algorithm [J].
Aslantas, V. ;
Kurban, R. .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (12) :8861-8870
[4]  
Aslantas Veysel, 2014, INF CONTR AUT ROB IC, V1
[5]  
Bedi S.S., 2013, INT J SOFT COMPUT EN, V3, P2231
[6]  
Erkanli S., 2012, FUSION VISUAL THERMA
[7]  
Feng Y., 2011, J INFORM COMPUTATION, V8, P2637
[8]  
Feng Y, 2014, APPL MATH INFORM SCI, V8, P2395
[9]  
Geetha G, 2012, J COMPUT SCI INF TEC, V10, P103
[10]  
Gupta R, 2014, 2014 5TH INTERNATIONAL CONFERENCE CONFLUENCE THE NEXT GENERATION INFORMATION TECHNOLOGY SUMMIT (CONFLUENCE), P280, DOI 10.1109/CONFLUENCE.2014.6949273