基于matlab的图像增强算法对比仿真,包括SSR,MSR,MSRCR以及MSRCP+代码仿真操作视频

function res123 = Code(arg) close all; clc; I=imread(arg); Ir=I(:,:,1); Ig=I(:,:,2); Ib=I(:,:,3); %%%%%%%%%%Set the required parameters%%%%%% G = 192; b = -30; alpha = 125; beta = 46; Ir_double=double(Ir); Ig_double=double(Ig); Ib_double=double(Ib); %%%%%%%%%%Set the Gaussian parameter%%%%%% sigma_1=15; %Three Gaussian Kernels sigma_2=80; sigma_3=250; [x, y]=meshgrid((-(size(Ir,2)-1)/2):(size(Ir,2)/2),(-(size(Ir,1)-1)/2):(size(Ir,1)/2)); gauss_1=exp(-(x.^2+y.^2)/(2*sigma_1*sigma_1)); %Calculate the Gaussian function Gauss_1=gauss_1/sum(gauss_1(:)); %Normalization gauss_2=exp(-(x.^2+y.^2)/(2*sigma_2*sigma_2)); Gauss_2=gauss_2/sum(gauss_2(:)); gauss_3=exp(-(x.^2+y.^2)/(2*sigma_3*sigma_3)); Gauss_3=gauss_3/sum(gauss_3(:)); %%%%%%%%%%Operates on R component%%%%%%% % MSR Section Ir_log=log(Ir_double+1); %Converts an image to a logarithm field f_Ir=fft2(Ir_double); %The image is Fourier transformed and converted to the frequency domain %sigma = 15 processing results fgauss=fft2(Gauss_1,size(Ir,1),size(Ir,2)); fgauss=fftshift(fgauss); %Move the center of the frequency domain to zero Rr=ifft2(fgauss.*f_Ir); %After convoluting, transform back into the airspace min1=min(min(Rr)); Rr_log= log(Rr - min1+1); Rr1=Ir_log-Rr_log; %sigma=80 fgauss=fft2(Gauss_2,size(Ir,1),size(Ir,2)); fgauss=fftshift(fgauss); Rr= ifft2(fgauss.*f_Ir); min1=min(min(Rr)); Rr_log= log(Rr - min1+1); Rr2=Ir_log-Rr_log; %sigma=250 fgauss=fft2(Gauss_3,size(Ir,1),size(Ir,2)); fgauss=fftshift(fgauss); Rr= ifft2(fgauss.*f_Ir); min1=min(min(Rr)); Rr_log= log(Rr - min1+1); Rr3=Ir_log-Rr_log; Rr=0.33*Rr1+0.34*Rr2+0.33*Rr3; %Weighted summation MSR1 = Rr; SSR1 = Rr2; %Calculate CR CRr = beta*(log(alpha*Ir_double+1)-log(Ir_double+Ig_double+Ib_double+1)); %SSR min1 = min(min(SSR1)); max1 = max(max(SSR1)); SSR1 = uint8(255*(SSR1-min1)/(max1-min1)); %MSR min1 = min(min(MSR1)); max1 = max(max(MSR1)); MSR1 = uint8(255*(MSR1-min1)/(max1-min1)); %MSRCR Rr = G*(CRr.*Rr+b); min1 = min(min(Rr)); max1 = max(max(Rr)); Rr_final = uint8(255*(Rr-min1)/(max1-min1)); %%%%%%%%%%On g component operation%%%%%%% %Ig_double=double(Ig); Ig_log=log(Ig_double+1); %Converts an image to a logarithm field f_Ig=fft2(Ig_double); %The image is Fourier transformed and converted to the frequency domain fgauss=fft2(Gauss_1,size(Ig,1),size(Ig,2)); fgauss=fftshift(fgauss); %Move the center of the frequency domain to zero Rg= ifft2(fgauss.*f_Ig); %After convoluting, transform back into the airspace min2=min(min(Rg)); Rg_log= log(Rg-min2+1); Rg1=Ig_log-Rg_log; %sigma = 15 processing results fgauss=fft2(Gauss_2,size(Ig,1),size(Ig,2)); fgauss=fftshift(fgauss); Rg= ifft2(fgauss.*f_Ig); min2=min(min(Rg)); Rg_log= log(Rg-min2+1); Rg2=Ig_log-Rg_log; %sigma=80 fgauss=fft2(Gauss_3,size(Ig,1),size(Ig,2)); fgauss=fftshift(fgauss); Rg= ifft2(fgauss.*f_Ig); min2=min(min(Rg)); Rg_log= log(Rg-min2+1); Rg3=Ig_log-Rg_log; %sigma=250 Rg=0.33*Rg1+0.34*Rg2+0.33*Rg3; %Weighted summation SSR2 = Rg2; MSR2 = Rg; %Calculate CR CRg = beta*(log(alpha*Ig_double+1)-log(Ir_double+Ig_double+Ib_double+1)); %SSR: min2 = min(min(SSR2)); max2 = max(max(SSR2)); SSR2 = uint8(255*(SSR2-min2)/(max2-min2)); %MSR min2 = min(min(MSR2)); max2 = max(max(MSR2)); MSR2 = uint8(255*(MSR2-min2)/(max2-min2)); %MSRCR Rg = G*(CRg.*Rg+b); min2 = min(min(Rg)); max2 = max(max(Rg)); Rg_final = uint8(255*(Rg-min2)/(max2-min2)); %%%%%%%%%%The B component is manipulated with the R component%%%%%%% %Ib_double=double(Ib); Ib_log=log(Ib_double+1); f_Ib=fft2(Ib_double); fgauss=fft2(Gauss_1,size(Ib,1),size(Ib,2)); fgauss=fftshift(fgauss); Rb= ifft2(fgauss.*f_Ib); min3=min(min(Rb)); Rb_log= log(Rb-min3+1); Rb1=Ib_log-Rb_log; fgauss=fft2(Gauss_2,size(Ib,1),size(Ib,2)); fgauss=fftshift(fgauss); Rb= ifft2(fgauss.*f_Ib); min3=min(min(Rb)); Rb_log= log(Rb-min3+1); Rb2=Ib_log-Rb_log; fgauss=fft2(Gauss_3,size(Ib,1),size(Ib,2)); fgauss=fftshift(fgauss); Rb= ifft2(fgauss.*f_Ib); min3=min(min(Rb)); Rb_log= log(Rb-min3+1); Rb3=Ib_log-Rb_log; Rb=0.33*Rb1+0.34*Rb2+0.33*Rb3; %计算CR CRb = beta*(log(alpha*Ib_double+1)-log(Ir_double+Ig_double+Ib_double+1)); SSR3 = Rb2; MSR3 = Rb; %SSR: min3 = min(min(SSR3)); max3 = max(max(SSR3)); SSR3 = uint8(255*(SSR3-min3)/(max3-min3)); %MSR min3 = min(min(MSR3)); max3 = max(max(MSR3)); MSR3 = uint8(255*(MSR3-min3)/(max3-min3)); %MSRCR Rb = G*(CRb.*Rb+b); min3 = min(min(Rb)); max3 = max(max(Rb)); Rb_final = uint8(255*(Rb-min3)/(max3-min3)); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %MSRCP Int = (Ir_double + Ig_double + Ib_double) / 3.0; Int_log = log(Int+1); %Converts an image to a logarithm field f_Int=fft2(Int_log); %The image is Fourier transformed and converted to the frequency domain %sigma = 15 processing results fgauss=fft2(Gauss_1,size(Int,1),size(Int,2)); fgauss=fftshift(fgauss); %Move the center of the frequency domain to zero RInt=ifft2(fgauss.*f_Int); %After convoluting, transform back into the airspace min1=min(min(RInt)); RInt_log= RInt - min1+1; RInt1=Int_log-RInt_log; %sigma=80 fgauss=fft2(Gauss_2,size(Int,1),size(Int,2)); fgauss=fftshift(fgauss); RInt= ifft2(fgauss.*f_Int); min1=min(min(RInt)); RInt_log= RInt - min1+1; RInt2=Int_log-RInt_log; %sigma=250 fgauss=fft2(Gauss_3,size(Int,1),size(Int,2)); fgauss=fftshift(fgauss); RInt= ifft2(fgauss.*f_Int); min1=min(min(RInt)); RInt_log= RInt - min1+1; RInt3=Int_log-RInt_log; RInt=0.33*RInt1+0.34*RInt2+0.33*RInt3; %Weighted summation minInt = min(min(RInt)); maxInt = max(max(RInt)); Int1 = uint8(255*(RInt-minInt)/(maxInt-minInt)); MSRCPr = zeros(size(I, 1), size(I, 2)); MSRCPg = zeros(size(I, 1), size(I, 2)); MSRCPb = zeros(size(I, 1), size(I, 2)); for ii = 1 : size(I, 1) for jj = 1 : size(I, 2) C = max(Ig_double(ii, jj), Ib_double(ii, jj)); B = max(Ir_double(ii, jj), C); A = min(255.0 / B, Int1(ii, jj) / Int(ii, jj)); MSRCPr(ii, jj) = A * Ir_double(ii, jj); MSRCPg(ii, jj) = A * Ig_double(ii, jj); MSRCPb(ii, jj) = A * Ib_double(ii, jj); end end minInt = min(min(MSRCPr)); maxInt = max(max(MSRCPr)); MSRCPr = uint8(255*(MSRCPr-minInt)/(maxInt-minInt)); minInt = min(min(MSRCPg)); maxInt = max(max(MSRCPg)); MSRCPg = uint8(255*(MSRCPg-minInt)/(maxInt-minInt)); minInt = min(min(MSRCPb)); maxInt = max(max(MSRCPb)); MSRCPb = uint8(255*(MSRCPb-minInt)/(maxInt-minInt)); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ssr = cat(3,SSR1,SSR2,SSR3); msr = cat(3,MSR1,MSR2,MSR3); msrcr=cat(3,Rr_final,Rg_final,Rb_final); %Combine the three-channel image MSRCP = cat(3, MSRCPr, MSRCPg, MSRCPb); subplot(3,2,1);imshow(I);title('Original') %Show the original image subplot(3,2,2);imshow(ssr);title('SSR') subplot(3,2,3);imshow(msr);title('MSR') subplot(3,2,4);imshow(msrcr);title('MSRCR') %Displays the processed image subplot(3,2,5);imshow(MSRCP);title('MSRCP')