A novel approach to image fusion based on multi-objective optimization

被引：0

作者：

Niu, Yifeng ^{[1
]}

Shen, Lincheng ^{[1
]}

机构：

[1] Natl Univ Def Technol, Sch Mechatron & Automat, Changsha 410073, Peoples R China

来源：

WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年

关键词：

multi-objective image fusion; adaptive multi-objective particle swarm optimization (AMOPSO);

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Most approaches to image fusion determine the building of image fusion model based on experience, and the parameter configuration of the fusion model is somewhat arbitrary. In this paper, a novel approach to image fusion based on multi-objective optimization was presented, which could achieve the optimal fusion indices through optimizing the fusion parameters. First the uniform model of image fusion in DWT (Discrete Wavelet Transform) domain was established; then the proper evaluation indices of image fusion were given; and finally the adaptive multi-objective particle swarm optimization (AMOPSO) was introduced to search the optimal fusion parameters. Experiment results show that AMOPSO has a higher convergence speed and better exploratory capabilities that MOPSO, and that the approach to image fusion based on AMOPSO realizes the Pareto optimal image fusion.

引用

页码：558 / 558

页数：1

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