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')
基于matlab的图像增强算法对比程序(包括SSR,MSR,MSRCR以及MSRCP)
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