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⛄ 内容介绍
At this paper we reviewed the application of the Multi-Wavelet Transform (Haar wavelet) in the fusion of different modality medical images such as Computed Tomography (CT) and Magnetic Resonance (MR) are fused forming a new image with highly improved information content for diagnosis. In our Proposed Method, an algorithm for image fusion based on the MWT was implemented, analyzed and compared with existed Wavelet-based fusion algorithm. And further results were evaluated and provided with better efficiency measures of performance in - the ENTROPY (H), ROOT MEAN SQUARE ERROR (RMSE), PEAK SIGNAL TO NOISE RATIO (PSNR) AND CORRELATION COEFFICIENT (CC). The quantitative performance measure parameters have shown that the MWT based image fusion algorithm provides a slightly better fused image than the Wavelet algorithm.
⛄ 部分代码
% Please cite this article as: Bavirisetti DP, Kollu V, Gang X, Dhuli R. Fusion of MRI and CT images using guided image filter and image statistics.
% Int. J. Imaging Syst. Technol. 2017;27:227�37. https://doi.org/10.1002/ima.22228
close all;
clear all;
clc;
% Parameters
r=25;
eps=2.1;
cov_wsize=5;
% source image 1
% I1=double(imread('med256A.jpg'));
I1=double(imread('source18A.tif'));
if size(I1,3)==3
I1=rgb2gray(I1);
end
% source image 2
% I2=double(imread('med256B.jpg'));
I2=double(imread('source18B.tif'));
if size(I2,3)==3
I2=rgb2gray(I2);
end
I(:,:,1)=I1;
I(:,:,2)=I2;
tic
% Base and detail layers seperation
A1= guidedfilter(double(I1), double(I2), r, eps);
B1=uint8(A1);
D1=double(I1)-A1;
C1=uint8(D1);
A2=guidedfilter(double(I2), double(I1), r, eps);
B2=uint8(A2);
D2=double(I2)-A2;
C2=uint8(D2);
D(:,:,1)=D1;
D(:,:,2)=D2;
% Fusion rule
xfused=GFS_fusion_rule(I,D,cov_wsize);
toc
FF=uint8(xfused);
% Display of images
figure, imshow(I1,[]);
figure, imshow(I2,[]);
figure, imshow(FF,[]);
⛄ 运行结果
⛄ 参考文献
[1] Kumar D R , Nelson S . Fusion of MRI and CT Images using Multi-Wavelet Based Image Fusion.
[2]张瑶, 刘生辉. 基于MATLAB的图像融合技术[J]. 中国科技信息, 2016(1):2.
