e3_matlab_RGB三通道_图像处理_图像融合_

%% p1=imread('F:\img1.jpg'); p2=imread('F:\img2.jpg'); p1=rgb2gray(p1); p2=rgb2gray(p2); %平均 [m,n]=size(p1); I1=zeros(m,n); w1=0.5;w2=0.5; w=w1+w2; for i=1:m for j=1:n I1(i,j)=(w1*p1(i,j)+w2*p2(i,j))/w; end end %加权平均 I2=zeros(m,n); w1=0.25;w2=0.75; w=w1+w2; for i=1:m for j=1:n I2(i,j)=(w1*p1(i,j)+w2*p2(i,j))/w; end end %灰度值选大法 I3=zeros(m,n); for i=1:m for j=1:n I3(i,j)=max(p1(i,j),p2(i,j)); end end %灰度值取小法 I4=zeros(m,n); for i=1:m for j=1:n I4(i,j)=min(p1(i,j),p2(i,j)); end end figure subplot(2,2,1) imshow(I1,[]);title('两幅图像像素灰度值平均后的图像'); subplot(2,2,2) imshow(I2,[]);title('两幅图像像素灰度值加权平均后的图像'); subplot(2,2,3) imshow(I3,[]);title('像素选大法'); subplot(2,2,4) imshow(I4,[]);title('像素取小法'); %% %彩色图像的分解与合成 img=imread('F:\s1v.jpg'); R=img(:,:,1); %获取红色分量 G=img(:,:,2); %获取绿色分量 B=img(:,:,3); %获取蓝色分量 figure subplot(2,2,1) imshow(img);title('原始图像'); subplot(2,2,2) imshow(R,[]);title('红色分量'); subplot(2,2,3) imshow(G,[]);title('绿色分量'); subplot(2,2,4) imshow(B,[]);title('蓝色分量'); %蓝色加高斯 Bp=imnoise(B,'gaussian',0,0.01); %绿色对数变换 Gp=mat2gray(log(1+double(G))); %红色图像反转 Rp=256-1-R; %合成 Ip=cat(3,Rp,255.*Gp,Bp); figure subplot(2,2,1) imshow(Ip,[]);title('合成图像'); subplot(2,2,2) imshow(Rp,[]);title('红色图像反转'); subplot(2,2,3) imshow(Gp,[]);title('绿色对数变换'); subplot(2,2,4) imshow(Bp,[]);title('蓝色加高斯'); %% %突出感兴趣目标 f=imread('F:\sqv.jpg'); f=im2double(f); r=f(:,:,1);%红 g=f(:,:,2);%绿 b=f(:,:,3);%蓝 %二值子图像提取 [m,n]=size(r); D=ones(m,n); xmin=59;ymin=317; xmax=159;ymax=417; figure subplot(2,2,1) imshow(f,[]);title('原始图像'); for i=ymin:ymax for j=xmin:xmax D(i,j)=0; end end subplot(2,2,2) imshow(D);title('提取窗口'); for i=ymin:ymax for j=xmin:xmax D(i,j)=5; end end Ir=r.*double(D); P=cat(3,Ir,g,b); subplot(2,2,3) imshow(P,[]);title('子图像提取'); %% %差异图像 p1=imread('F:\img1.jpg'); p2=imread('F:\img2.jpg'); p1=rgb2gray(p1); p2=rgb2gray(p2); %均值差异 n=3;%3*3的窗口 [w,h]=size(p1); v1=double(p1); v2=double(p2); c1=zeros(w,h); u1=zeros(w,h); u2=zeros(w,h); for i=2:w-1 for j=2:h-1 a=v1(i-1:i+1,j-1:j+1); b=v2(i-1:i+1,j-1:j+1); u1(i,j)=sum(sum(a))/(n*n); u2(i,j)=sum(sum(b))/(n*n); end end for i=1:w for j=1:h C1=u1(i,j)/(u2(i,j)+0.00001); C2=u2(i,j)/(u1(i,j)+0.00001); c1(i,j)=1-min(C1,C2); end end figure subplot(1,2,1) imshow(c1,[]);title('均值差异'); %对数差异 c2=zeros(w,h); for i=1:w for j=1:h c2(i,j)=abs(log(u2(i,j)+0.00001)-log(u1(i,j)+0.00001)); end end subplot(1,2,2) imshow(c2);title('对数差异'); %图像融合 F1=fftshift(fft2(double(c1))); F2=fftshift(fft2(double(c2))); [m,n]=size(F1); FF=zeros(m,n); m_mid=m/2; n_mid=n/2; H=zeros(m,n); D0=60; for i=1:n for j=1:m D=sqrt((i-m_mid).^2+(j-n_mid).^2); if D<D0 FF(i,j)=0.5*(F1(i,j)+F2(i,j)); else FF(i,j)=max(F1(i,j),F2(i,j)); end end end g1=fftshift(FF); g=ifft2(g1); figure subplot(1,2,1) imshow(abs(g),[]);title('图像融合后（高频成分取大）'); FF=zeros(m,n); for i=1:n for j=1:m D=sqrt((i-m_mid).^2+(j-n_mid).^2); if D<D0 FF(i,j)=0.5*(F1(i,j)+F2(i,j)); else FF(i,j)=min(F1(i,j),F2(i,j)); end end end g1=fftshift(FF); g=ifft2(g1); subplot(1,2,2) imshow(abs(g),[]);title('图像融合后（高频成分取小）');