Title :
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
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;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713934
