基于小波变换的图像融合

 clc;
 clear all;
 close all;                        % 清理工作空间
 clear
 [imA,map1] = imread('A.tif');
 M1 = double(imA) / 256;
 [imB,map2] = imread('B.tif');
 M2 = double(imB) / 256;


 zt= 4;
 wtype = 'haar';
 %    M1 - input image A
 %    M2 - input image B
 %    wtype使用的小波类型
 %    Y  - fused image
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %%
 %%  小波变换图像融合
 %%
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %%   小波变换的绝对值大的小波系数，对应着显著的亮度变化，也就是图像中的显著特征。所以，选择绝对值大
 %%   的小波系数作为我们需要的小波系数。【注意，前面取的是绝对值大小，而不是实际数值大小】
 %%
 %%   低频部分系数采用二者求平均的方法
 %%
 %%
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

 [c0,s0] = wavedec2(M1, zt, wtype);%多尺度二维小波分解

 [c1,s1] = wavedec2(M2, zt, wtype);%多尺度二维小波分解

 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %%  后面就可以进行取大进行处理。然后进行重构，得到一个图像
 %%  的小波系数，然后重构出总的图像效果。
 %%  取绝对值大的小波系数，作为融合后的小波系数
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 KK = size(c1);
 Coef_Fusion = zeros(1,KK(2));
 Temp = zeros(1,2);
 Coef_Fusion(1:s1(1,1)) = (c0(1:s1(1,1))+c1(1:s1(1,1)))/2;  %低频系数的处理
                      %这儿，连高频系数一起处理了，但是后面处理高频系数的时候，会将结果覆盖，所以没有关系

    %处理高频系数
     MM1 = c0(s1(1,1)+1:KK(2));
     MM2 = c1(s1(1,1)+1:KK(2));
     mm = (abs(MM1)) > (abs(MM2));
     Y  = (mm.*MM1) + ((~mm).*MM2);
     Coef_Fusion(s1(1,1)+1:KK(2)) = Y;
     %处理高频系数end

  %重构
  Y = waverec2(Coef_Fusion,s0,wtype);

 %显示图像
 subplot(2,2,1);imshow(M1);
 colormap(gray);
 title('input2');
 axis square

 subplot(2,2,2);imshow(M2);
 colormap(gray);
 title('input2');
 axis square

 subplot(223);imshow(Y,[]);
 colormap(gray);
 title('融合图像');
 axis square;
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

效果图：