matlab小波融合程序

1、基于低频融合策略的小波租激图像融合程序（Imfus.rar）；

2、嵌入式零树小波（EZW）算法的图像压缩编解码程序（EZW.rar）；

3、多级树集合分裂（SPIHT）算法斗前的图像压缩编解码空型清程序（SPIHT.rar）；

4、一种SPIHT改进算法（Mod-SPIHT.rar）。

其中都包含了基本的小波图像分解与重构程序，使用的是基本的Haar小波，根据Mallat算法编写。

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

%%

%%

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[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袭羡。

%% 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闭禅银数的时候，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('融轿宴合图像')

axis square

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