Title
A Novel Multiscale Transform Decomposition Based Multi-Focus Image Fusion Framework
Abstract
In this work, we propose a novel multiscale transform decomposition model for multi-focus image fusion to get a better fused performance. The motivation of the proposed fusion framework is to make full use of the decomposition characteristics of multiscale transform. The nonsubsampled contourlet transform (NSCT) is firstly used to decompose the source multi-focus images into low-frequency (LF) and several high-frequency (HF) bands to separate out the two basic characteristics of source images, i.e., principal information and edge details. The common "average" and "max-absolute" fusion rules are performed on low- and high-frequency components, respectively, and a basic fusion image is generated. Then the difference images between the basic fused image and the source images are calculated, and the energy of the gradient (EOG) of difference images are utilized to refine the basic fused image by integrating average filter and median filter. Visual and quantitative using fusion metrics like VIFF, Q(S), MI, Q(AB/F), SD, Q(PC) and running time comparisons to state-of-the-art algorithms demonstrate the out-performance of the proposed fusion technique.
Year
DOI
Venue
2021
10.1007/s11042-020-10462-y
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Multiscale transform, Multi-focus image fusion, NSCT, Difference image, Energy of the gradient
Journal
80
Issue
ISSN
Citations 
8
1380-7501
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Liangliang Li154.17
Ma Hongbing2378.17
Zhenhong Jia331.05
Yujuan Si4134.64