MATLAB Curvelet-4PCNN图像融合算法核心源码

%% by Vincent  path(path,'PCNN_toolbox/') path(path,'FusionEvaluation/') path(path,'fusetool/') %% %Low_Coeffs_Rule='PCNN'; %'ave','PCNN','SF-PCNN' %High_Coeffs_Rule='PCNN'; %'max','PCNN','SF-PCNN' % %% Parameters for Curvelet im1=double(imread('lena_1.png'));  im2=double(imread('lena_2.png'));  im3=double(imread('lena_3.png'));  im4=double(imread('lena_4.png'));  im1=im1(:,:,1);  im2=im2(:,:,1);  Im3=im3(:,:,1);  Im4=im4(:,:,1);  %% Parameters for PCNN Para.iterTimes=200; Para.link_arrange=3; Para.alpha_L=0.06931;% 0.06931 Or 1 Para.alpha_Theta=0.2; Para.beta=3;% 0.2 or 3 Para.vL=1.0; Para.vTheta=20; %% disp('Decompose the image via curvelet ...') yA = fdct_wrapping(im1,1,2);  yB = fdct_wrapping(im2,1,2); yC = fdct_wrapping(im1,1,2);  yD = fdct_wrapping(im2,1,2);  n = length(yA);  %% Initialized the coefficients of fused image Fused=yA;  for l = 1:n  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%     for d = 1:length(yA{l})         %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%         Ahigh = yA{l}{d};         Bhigh = yB{l}{d};         Chigh = yC{l}{d};         Dhigh = yD{l}{d};        [Abeta,Bbeta] = weighting(yA{l}{d},yB{l}{d});        [Cbeta,Dbeta] = weighting(yC{l}{d},yD{l}{d});        Fused{l}{d} = Four_PCNN(Ahigh, Bhigh,Chigh,Dhigh,Abeta,Bbeta,Cbeta,Dbeta);               %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%     end end %============================================= f_im = real(ifdct_wrapping(Fused,1));  disp('Reconstruct is ended...') %% Fusion=Fusion*255; Fusion(Fusion<0)=0; %disp('F>255') Fusion(Fusion>255)=255; Fusion=round(Fusion); %% Eval=Evaluation(double(ori_A),double(ori_B),Fusion,256); disp(Eval) %%