Title
Maximum local energy: An effective approach for multisensor image fusion in beyond wavelet transform domain
Abstract
The benefits of multisensor fusion have motivated research in this area in recent years. Redundant fusion methods are used to enhance fusion system capability and reliability. The benefits of beyond wavelets have also prompted scholars to conduct research in this field. In this paper, we propose the maximum local energy method to calculate the low-frequency coefficients of images and compare the results with those of different beyond wavelets. An image fusion step was performed as follows: first, we obtained the coefficients of two different types of images through beyond wavelet transform. Second, we selected the low-frequency coefficients by maximum local energy and obtaining the high-frequency coefficients using the sum modified Laplacian method. Finally, the fused image was obtained by performing an inverse beyond wavelet transform. In addition to human vision analysis, the images were also compared through quantitative analysis. Three types of images (multifocus, multimodal medical, and remote sensing images) were used in the experiments to compare the results among the beyond wavelets. The numerical experiments reveal that maximum local energy is a new strategy for attaining image fusion with satisfactory performance.
Year
DOI
Venue
2012
10.1016/j.camwa.2012.03.017
Computers & Mathematics with Applications
Keywords
Field
DocType
fusion system capability,attaining image fusion,effective approach,image fusion step,low-frequency coefficient,maximum local energy method,multisensor fusion,maximum local energy,fused image,redundant fusion method,multisensor image fusion,laplacian method,image fusion
Inverse,Pattern recognition,Image fusion,Fusion,Artificial intelligence,Energy method,Mathematics,Fusion system,Wavelet transform,Wavelet,Laplace operator
Journal
Volume
Issue
ISSN
64
5
0898-1221
Citations 
PageRank 
References 
27
1.36
15
Authors
3
Name
Order
Citations
PageRank
Huimin Lu178073.60
Lifeng Zhang2355.27
Seiichi Serikawa354038.54