• Multi-resolution image fusion...

Result: Multi-resolution image fusion using AMOPSO-II

Title:
Multi-resolution image fusion using AMOPSO-II
Authors:
YIFENG NIU, LINCHENG SHEN
Source:
Intelligent computing in signal processing and pattern recognition (International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006)0ICIC 2006. :343-352
Publisher Information:
Berlin: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 18 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Documentation, Computer science, Informatique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Analyse multirésolution, Multiresolution analysis, Análisis multiresolución, Conception optimale, Optimal design, Concepción optimal, Image multiple, Multiple image, Imagen múltiple, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Modélisation, Modeling, Modelización, Méthode adaptative, Adaptive method, Método adaptativo, Ondelette discrète, Discrete wavelet, Ondita discreta, Optimisation PSO, Particle swarm optimization, Optimización PSO, Optimisation essaim particule, Swarm intelligence, Optimización enjambre partícula, Optimum Pareto, Pareto optimum, Optimo Pareto, Programmation multiobjectif, Multiobjective programming, Programación multiobjetivo, Résolution image, Image resolution, Resolución imagen, Temps discret, Discrete time, Tiempo discreto, Traitement image, Image processing, Procesamiento imagen, Transformation discrète, Discrete transformation, Transformación discreta
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Mechatronics and Automation National University of Defense Technology, 410073, Changsha, China
ISSN:
0170-8643
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=18315851
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.18315851
Database:
PASCAL Archive

Further Information

Most approaches to multi-resolution image fusion are based on experience, and the fusion results are not the optimal. In this paper, a new approach to multi-resolution image fusion based on AMOPSO-II (Adaptive Multi-Objective Particle Swarm Optimization) is presented, which can achieve the optimal fusion results through optimizing the fusion parameters. First the uniform model of multi-resolution image fusion in DWT (Discrete Wavelet Transform) domain is established; then the proper evaluation indices of multi-resolution image fusion are given; and finally AMOPSO-II is proposed and used to search the fusion parameters. AMOPSO-II not only uses an adaptive mutation operator and an adaptive inertia weight to raise the search capacity, but also uses a new crowding operator to improve the distribution of nondominated solutions along the Pareto front, and uses the uniform design to obtain the optimal combination of the parameters of AMOPSO-II. Results show that AMOPSO-II has better exploratory capabilities than AMOPSO-I, and that the approach to multi-resolution image fusion based on AMOPSO-II realizes the Pareto optimal multi-resolution image fusion.