A new method of medical image fusion based on nonsubsampled contourlet transform

2008 ◽  
Author(s):  
Xuebin Xu ◽  
Xinman Zhang ◽  
Deyun Zhang
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
New Method ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Medical Image Fusion

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

scholarly journals The Nonsubsampled Contourlet Transform Based Statistical Medical Image Fusion Using Generalized Gaussian Density

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Guocheng Yang ◽  
Meiling Li ◽  
Leiting Chen ◽  
Jie Yu
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Low Frequency ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Medical Image Fusion ◽  
Gaussian Density ◽  
Generalized Gaussian Density ◽  
Fusion Scheme ◽  
Jensen Shannon Divergence

We propose a novel medical image fusion scheme based on the statistical dependencies between coefficients in the nonsubsampled contourlet transform (NSCT) domain, in which the probability density function of the NSCT coefficients is concisely fitted using generalized Gaussian density (GGD), as well as the similarity measurement of two subbands is accurately computed by Jensen-Shannon divergence of two GGDs. To preserve more useful information from source images, the new fusion rules are developed to combine the subbands with the varied frequencies. That is, the low frequency subbands are fused by utilizing two activity measures based on the regional standard deviation and Shannon entropy and the high frequency subbands are merged together via weight maps which are determined by the saliency values of pixels. The experimental results demonstrate that the proposed method significantly outperforms the conventional NSCT based medical image fusion approaches in both visual perception and evaluation indices.

Medical Image Fusion Based on the Nonsubsampled Contourlet Transform

2013 ◽  
Vol 50 (11) ◽  
pp. 111002
Author(s):  
李翠 Li Cui ◽  
纪峰 Ji Feng ◽  
常霞 Chang Xia ◽  
吴仰玉 Wu Yangyu
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Medical Image Fusion
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