Technique for image fusion based on non-subsampled contourlet transform domain improved NMF

To overcome the problem of multi-sensor image fusion, a technique for image fusion based on non-subsampled contourlet transform （NSCT） domain improved nonnegative matrix factorization （NMF） is presented. Firstly, by using NSCT, multi-scale and multi-direction sparse decompositions of source images a...

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Bibliographic Details
Published in:Science China. Information sciences 2010-12, Vol.53 (12), p.2429-2440
Main Authors: Kong, WeiWei, Lei, YingJie, Lei, Yang, Zhang, Jie
Format: Article
Language:English
Subjects:
Computer Science
Computer simulation
Computer vision
Contourlet变换
Factorization
Information Systems and Communication Service
Inverse
Multisensor fusion
Neural networks
NMF
Randomization
Research Papers
Shape
Transforms
下采样
多传感器图像融合
脉冲耦合神经网络
融合技术
非负矩阵分解
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Summary:To overcome the problem of multi-sensor image fusion, a technique for image fusion based on non-subsampled contourlet transform （NSCT） domain improved nonnegative matrix factorization （NMF） is presented. Firstly, by using NSCT, multi-scale and multi-direction sparse decompositions of source images are performed. Then, an improved NMF technique is utilized to complete the fusion of low-frequency sub-images. The low-frequency fused image can be produced fast by the process which does not involve the randomization of the vectors W and H at all, in addition, the fusion course of high-frequency sub-images can be dealt with by use of the model of adaptive unit-fast-linking pulse coupled neural network （AUFLPCNN）. Finally, the ultimate fused image can be obtained by synthesizing all sub-images with inverse NSCT. The simulated experiments show that the technique is effective.
ISSN:1674-733X
1869-1919
DOI:10.1007/s11432-010-4118-2