Medical image fusion using non subsampled contourlet transform and iterative joint filter

2021 ◽  
Author(s):  
M Munawwar Iqbal Ch ◽  
Abdul Ghafoor ◽  
Asim Dilawar Bakhshi ◽  
Nuwayrah Jawaid Saghir
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
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 Multimodal Medical Image Fusion in Non-Subsampled Contourlet Transform Domain

2016 ◽  
Vol 07 (08) ◽  
pp. 1598-1610 ◽  
Author(s):  
Periyavattam Shanmugam Gomathi ◽  
Bhuvanesh Kalaavathi
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Contourlet Transform ◽  
Transform Domain ◽  
Medical Image Fusion

scholarly journals Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Hui Huang ◽  
Xi’an Feng ◽  
Jionghui Jiang
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Sparse Matrix ◽  
Nonlinear Approximation ◽  
Low Frequency ◽  
Contourlet Transform ◽  
Fusion Algorithm ◽  
Medical Image Fusion ◽  
Regional Features ◽  
Pros And Cons

According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

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