scholarly journals An Effective Image Fusion Method Based on Nonsubsampled Contourlet Transform and Pulse Coupled Neural Network

2012 ◽  
Author(s):  
Lijuan Ma ◽  
Chunhui Zhao
Keyword(s):  
Neural Network ◽  
Image Fusion ◽  
Contourlet Transform ◽  
Fusion Method ◽  
Nonsubsampled Contourlet Transform ◽  
Pulse Coupled Neural Network ◽  
Image Fusion Method

scholarly journals Infrared and Visible Image Fusion Method Based on ResNet in a Nonsubsampled Contourlet Transform Domain

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Ce Gao ◽  
Donghao Qi ◽  
Yanchao Zhang ◽  
Congcong Song ◽  
Yi Yu
Keyword(s):  
Image Fusion ◽  
Contourlet Transform ◽  
Transform Domain ◽  
Fusion Method ◽  
Nonsubsampled Contourlet Transform ◽  
Visible Image ◽  
Image Fusion Method

A Nonsubsampled Contourlet Transform Based Medical Image Fusion Method

2013 ◽  
Vol 12 (4) ◽  
pp. 749-755 ◽  
Author(s):  
Shen Yu ◽  
Ren Enen ◽  
Dang Jian-Wu ◽  
Wang Guo-Hua ◽  
Feng Xin
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Contourlet Transform ◽  
Fusion Method ◽  
Nonsubsampled Contourlet Transform ◽  
Medical Image Fusion ◽  
Image Fusion Method

A novel multi-focus image fusion method using PCNN in nonsubsampled contourlet transform domain

Optik ◽  
2015 ◽  
Vol 126 (20) ◽  
pp. 2508-2511 ◽  
Author(s):  
Jingjing Wang ◽  
Qian Li ◽  
Zhenhong Jia ◽  
Nikola Kasabov ◽  
Jie Yang
Keyword(s):  
Image Fusion ◽  
Contourlet Transform ◽  
Transform Domain ◽  
Fusion Method ◽  
Nonsubsampled Contourlet Transform ◽  
Focus Image ◽  
Image Fusion Method

Optimal image-fusion method based on nonsubsampled contourlet transform

2012 ◽  
Vol 51 (10) ◽  
pp. 107006 ◽  
Author(s):  
Jianfang Dou ◽  
Jianxun Li
Keyword(s):  
Image Fusion ◽  
Contourlet Transform ◽  
Fusion Method ◽  
Nonsubsampled Contourlet Transform ◽  
Image Fusion Method

An Effective Image Fusion Method Based on Nonsubsampled Contourlet Transform and Pulse Coupled Neural Network

2013 ◽  
Vol 756-759 ◽  
pp. 3542-3548 ◽  
Author(s):  
Li Juan Ma ◽  
Chun Hui Zhao
Keyword(s):  
Image Fusion ◽  
Infrared Image ◽  
Low Frequency ◽  
Contourlet Transform ◽  
Fusion Method ◽  
Nonsubsampled Contourlet Transform ◽  
Wavelet Method ◽  
Weighted Sum Method ◽  
Ihs Transform ◽  
Image Fusion Method

In order to solve the problem of spectral distortion and the fuzzy texture in visible and infrared image fusion technology, a novel visible and infrared image fusion method based on the Nonsubsampled Contourlet Transform (NSCT) and Pulse Coupled Neural Networks (PCNN) is proposed in this paper. First, we gain three components of visible image, luminance I, chrominance H and saturation S, using the IHS transform. Then, we gain three coefficients, low frequency sub-band, passband sub-band and high frequency coefficient by decomposing the component I and infrared image with the help of the NSCT. Next, we use weighted-sum method to fuse the low frequency sub-band and PCNN method to fuse the other sub-band coefficient respectively. At last, we gain the fusion image by using the inverse IHS transform on the fusion component I gained by the inverse NSCT transform. Experiments show that our method have better fusion quality and can be more better to keep the visible spectral and detail information than some traditional methods such as, Laplace method, Wavelet method and Lifting Wavelet method.

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