A Novel Approach to Image Fusion Based on Multi-Objective Optimization

Author

Niu, Yifeng ; Shen, Lincheng

Author_Institution

Sch. of Mechatronics & Autom., Nat. Univ. of Defense Technol., Changsha

Volume

2

fYear

0

fDate

0-0 0

Firstpage

9911

Lastpage

9915

Abstract

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 than MOPSO, and that the approach to image fusion based on AMOPSO realizes the Pareto optimal image fusion

Keywords

discrete wavelet transforms; image processing; particle swarm optimisation; sensor fusion; adaptive multiobjective particle swarm optimization; discrete wavelet transform; image fusion; multiobjective optimization; Automation; Convergence; Discrete wavelet transforms; Evolutionary computation; Image fusion; Mechatronics; Particle swarm optimization; Sorting; Spatial resolution; Wavelet domain; adaptive multi-objective particle swarm optimization (AMOPSO); multi-objective image fusion;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713934

Filename

1713934