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main.asv
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% This is the main function of the Region Based adaptive dehazing, details
% enhancement and pre-processing using auto-color transfer method
%
% The pre-proessing of hazy image (auto-color transfer) is performed using
% the function: 'CT'
%
% The image categorization of hazy image (less affected by haze, moderately
% affected by haze and more affected by haze regions) is performed using
% the function 'Image_Classification')
%
% Input arguments:
% ----------------
% - Oimg : input haze image, type "unsigned integer"
% - GT : Ground-Truth image
% - count : Counter for hazy images
% - validation : If hazy image has a corresponding ground-truth image,
% its one, else its zero.
% - imagename: Name of the hazy image from the DB
Oimg=imread('hazy/01_indoor_hazyc.png');
output_folder = 'Dehazing_Results';
Oimg=imresize(Oimg,[360 480]);
%GT=imresize(GT,[360 480]);
img = im2double(Oimg);
imgg = im2double(Oimg);
%outputFileName = fullfile(output_folder, [imagename, '.png']);
img_gray=rgb2gray(img);
[m,n]=size(img_gray);
% Function 'CT' for auto-color transfer function, to enhance the
% low-intensity regions of a hazy image.
%
% Input arguments:
% ----------------
% - S: Source Image
% - Tg: Target Image
%
% Output arguments:
% ----------------
% - r: Enhanced Image
% - comp_time0 : Computation time of this function.
% img1diff=img1max-img1;
%img1diff(img1diff<=0)=
% if numel(img(img<T))>10
% img1max=im2uint8(img1max);
% % filename='img1max.xlsx';
% % img1max1=img1max(:,:,1);
% % img1max2=img1max(:,:,2);
% % img1max3=img1max(:,:,3);
%
%
%
% % imwrite(img1,'img1.png');
% % imwrite(img1max,'img1max.png');
% % source='img1max.png';
% % target='img1.png';
% % S=imread(source);
% % Tg=imread(target);
% S=img;
% Tg=img^0.4;
% [r, comp_time0]=CT(double(S)/255,double(Tg)/255);
% % disp("Inside dark enhancement");
% img(img1f<T)=r(img1f<T);
% %figure;imshow([img1f r]);title('img1f vs Dark enhanced');
% %figure;imshow([imgg img]);title('org vs org Dark enhanced');
% end
%difference=zeros(size(img));
B=mean(mean(img_gray));count75=0;
for i=1:m
for j=1:n
if img_gray(i,j)<0.3
count75=count75+1;
end
end
end
if count75>1000
img_gt=img.^0.7;
% img_gt=img.^0.4;
Tg=im2uint8(img);
S=im2uint8(img_gt);
imwrite(Tg,'Tg.png');
imwrite(S,'S.png');
S=imread('S.png');
Tg=imread('Tg.png');
%figure;
%imshow([S Tg]);
[r, comp_time0]=CT(double(S)/255,double(Tg)/255);
%imwrite(im2uint8(r),outputFileName);
%return
img=r;
end
% figure;
% imshow([img im2double(S) r]);
% if numel(img(img<T))>100
% rg=rgb2gray(r);img1maxg=rgb2gray(img1max);
%
% figure(1);imshow(S);title('Source Image');
% colormap jet
% figure(2);imshow(Tg);title('Target Image');
% colormap jet
% figure(3);imshow([rgb2gray(img1) rg]);title('Dark regions in hazy image vs enhanced dark regions');
% figure(4);imshow([rg]);title('enhanced dark regions');
% %colormap jet
% % imwrite([rgb2gray(img1)],[imagename, '.png'])
% % colormap jet
% % pause(3);
%
%
%
% difference(:,:,1)=im2uint8(r(:,:,1))-S(:,:,1);
% difference(:,:,2)=im2uint8(r(:,:,2))-S(:,:,2);
% difference(:,:,3)=im2uint8(r(:,:,3))-S(:,:,3);
% Num=numel(difference>10)
% disp('Maximum difference:');disp(max(max(difference)));
% rnew=zeros(size(r));
% %
% % rnew(:,:,1)=img1(:,:,1)+rgb2gray(difference);
% % rnew(:,:,2)=img1(:,:,2)+rgb2gray(difference);
% % rnew(:,:,3)=img1(:,:,3)+rgb2gray(difference);
% %img(img1f<T)=rnew(img1f<T);
% img_med=medfilt3(img);
% img_med_99=medfilt3(img,[9 9 3]);
%
%
% %figure(3);imshow([img img_med img_med_99]);title('Normalised enhancement vs Its median');
%
% % filename = 'difference.xlsx';
% % A = {'difference1','difference2','difference3'; difference(:,:,1),difference(:,:,2),difference(:,:,3)};
% % xlswrite(filename,difference(:,:,1),'difference1');
% % xlswrite(filename,difference(:,:,2),'difference2');
% % xlswrite(filename,difference(:,:,3),'difference3');
% end
% imwrite(im2uint8(r),[imagename, '.png']);
%dmax=max(max(difference));
% if numel(img(img<T))<10
% comp_time0=0;
% disp('No dark regions');
% end
img1=zeros(size(img));%img1f=zeros(size(img));
%img1=im2double(img1);
% Function 'Image_Classification' for auto-color transfer function, to enhance the
% low-intensity regions of a hazy image.
%
% Input arguments:
% ----------------
% - img: Pre-processed Hazy Image
%
% Output arguments:
% ----------------
% - img_map: Image map with region classification i.e., Red colour for
% less-affected by haze regions, Green colour for moderately affected by
% haze regions and blue colour for more-affected by haze regions.
img_map=Image_Classification(img);
% imwrite(img_map,[imagename, '.png']);
%figure(2); imshow([Oimg img_map]);
% T=0.45;
% img2=zeros(size(img));
% img3=zeros(size(img));
% for i=1:m
% for j=1:n
% %disp('n:');disp(n);
% if (img(i,j,1)<=T) || (img(i,j,2)<=T) || (img(i,j,3)<=T)
% img1(i,j,:)=img(i,j,:);
%
% elseif (img(i,j,1)>=U) && (img(i,j,2)>=U) && (img(i,j,3)>=U)
% img3(i,j,:)=img(i,j,:);
%
% else
% img2(i,j,:)=img(i,j,:);
% end
% end
% end
%disp('m:');disp(m);
%Oimg2=im2uint8(img);
%Oimggray=rgb2gray(Oimg);
%imggray=im2double(Oimggray);
%Oimgrgb=grs2rgb(Oimggray,MAP);
%figure(7);imshow([Oimggray Oimgrgb]);title('Gray vs RGB');
%figure(4);imshow([img img1 img3]);title('Input RGB Image vs img1 vs img3');
%img1=medfilt3(img1,[5 5 3]);
%img3=medfilt3(img3,[5 5 3]);
%img=medfilt3(img,[3 3 3]);
%figure(5);imshow([img img1 img3]);title('Input RGB Image vs filtered img1 vs filtered img3');
%img2=img-img1-img3;
%img2=medfilt3(img2,[3 3 3]);
% img11=img1;
% img21=img2;img31=img3;
% %figure;imshow([img11 img21 img31]);title('img11 vs img21 vs img31');
%
%
% img1mean=[T/2,T/2,T/2];%img11=img1;img22=img2;img33=img3;
% imgmean=mean(mean(img));img1min=[0.01,0.01,0.01];
% img3mean=[1-T/2,1-T/2,1-T/2];img3max=[0.99,0.99,0.99];
% for i=1:m
% for j=1:n
% if (img1(i,j,1)<0.01) && (img1(i,j,2)<0.01) && (img1(i,j,3)<0.01)
% img1(i,j,:)=img3max;
% img1(i,j,:)=img3max;
% end
% if (img2(i,j,1)<0.05) || (img2(i,j,2)<0.05) || (img2(i,j,3)<0.05)
% img2(i,j,:)=img3max;
% end
% if (img3(i,j,1)<0.01) && (img3(i,j,2)<0.01) && (img3(i,j,3)<0.01)
% img3(i,j,:)=img3mean;
% end
% end
% end
%img1max=zeros(size(img1));
%for i=1:m
% for j=1:n
% img1max(m,n,:)=img1maxi;
% end
% end
%img1max(img1<T)=max(img1(img1<T));
%img1max(img1>T)=max(img1(img1>T));
%figure(7);imshow([img1 img1max]);title('Dark vs img1max');
%img1(img1>T)=mean(img(img1<T));
%img2(img3>U)=mean(img(img3>U));
%img3(img3<U)=max(img3(img3<U));
%figure(7);imshow([img1 img2 img3]);title('img1 vs img2 vs img3');
%img1(img<T)=img(img<T);img3(img>U)=img(img>U);
%img1(img>T)=White(img>T);img3(img<U)=Black(img<U);
%[m,n,p] = size(img1);
%img1f = medfilt3(img1,[5 5 3]);img3f=medfilt3(img3,[51 51 3]);img3f=medfilt3(img3f,[15 15 3]);
%img1f2 = medfilt3(img1f,[5 5 3]);
%figure(1);imshow([img1 img1f]);title('Dark overview vs dark filtered');
%img1(img1f<T)=img(img1f<T);img3(img3f>U)=img(img3f>U);
%img1(img1f>T)=Black(img1f>T);
%img2=img-img1-img3f;
%img2(img3f>U)=mean(img3f(img3f>U));
%img2(img1f<T)=mean(img1f(img1f<T));
%img2f=medfilt3(img2,[51 51 3]);
%img2=medfilt3(img2,[5 5 3]);
%figure(6);imshow([img2]);title('bright overview');
%img1(img1f>T)=mean(img1f(img1f<T));img3(img3f<U)=mean(img3f(img3f>U));
%figure(4);imshow([img3 img3f]);title('Brightest overview vs brightest filtered');
%img1(img>T)=Black(img>T);
%img3(img<0.85)=Black(img<0.85);
%img3(img>0.85)=img(img>0.85);
%figure(2);imshow(img3);title('Brightest overview-1');
%img2=img-(img1+img3);
%img1(img>T)=mean(img(img<T));
%figure(2);imshow([img1 img1f]);title('Img1 vs Img1f');
%img1=img1f;
%img2((img<T)||(img>0.85))=mean(img);
%img2(img<T)=mean2(img);
%img2(img>0.85)=mean2(img);
%figure(5);imshow(img2);title('Bright overview');
%img3(img<0.85)=mean(img(img>0.85));
%figure(6);imshow(img3);title('Brightest overview-2');
%figure(4);imshow(img3);title('Brightest overview');
%figure(1);imshow(img1);title('Dark overview');
%img1max=max(max(img1));
%figure(3);imshow([img1 img1max]);title('Img1 vs Img1max');
%[m,n,p] = size(img1);
%img1 = medfilt3(img1,[m/10 n/10 p]);
%figure(3);imshow([img img1]);title('RGBImage versus Dark-filtered');
%img2(img>T)=img(img>T);
%img2(img<T)=Black(img<T);
%Oimg2=im2uint8(img);
%figure(5);imshow([Oimg Oimg2]);title('Original image versus Original-filtered');
%img2 = medfilt3(img2,[m/10 n/10 p]);
%disp('Number of dark pixels:');disp(numel(img(img<T)));
%disp('Number of RGB Image pixels:');disp(numel(img));
%figure(2);imshow([img img2]);title('RGBImage versus Non-Dark');
%img1(img1f>T)=mean(img1f(img1f<T));
%figure(7);imshow([img1 img2 img3]);title('Image parts overview img1 img2 img3');
% img=imgg;
HS=new_indicator_v5_opt(img);
Atm_light=Alight(im2double(img));
%Atm_light_h=Alight(im2double(GT));
% HS=Image_Classification_HS(img,mean(Atm_light));
% if HDE>0.5
% imwrite(img,[imagename, '.png']);
% end
[dehazed_img1, comp_time1, trans_map1] = fcn_multi(img,HS,1);
%imwrite(Odehazed_img,outputFileName);
[dehazed_img2, comp_time2, trans_map2] = fcn_multi(img,HS,2);
[dehazed_img3, comp_time3, trans_map3] = fcn_multi(img,HS,3);
% Odehazed_img3=im2uint8(dehazed_img3);
%figure(3);imshow([dehazed_img1 dehazed_img2 dehazed_img3]);title('Different dehazed outcomes from three different blocks');
%[dehazed_img4, comp_time4, trans_map4] = fcn_multi(img,4);
%figure(8);imshow([dehazed_img2 dehazed_img3]);title('Dehazed Image parts');
%figure(12);imshow([img1 dehazed_img1 ]);title('img1 vs dehazed');
%figure(13);imshow([img2 dehazed_img2]);title('img2 vs dehazed');
%figure;imshow([dehazed_img1 dehazed_img2 dehazed_img3]);title('dehazed img1 dehazed img2 dehazed img3');
dehazed_img=zeros(size(img));k=0;
% for i=1:m
% for j=1:n
% if (img1(i,j,:)==img3max)
% dehazed_img(i,j,:)=dehazed_img(i,j,:);
% else
% dehazed_img(i,j,:)=dehazed_img1(i,j,:);
% k=k+1;
% end
% end
% end
% %disp('k:'); disp(k);
% %figure(10);imshow(dehazed_img);title('Dehazed Image after img1');
% for i=1:m
% for j=1:n
% if (img2(i,j,:)==img3max)
% dehazed_img(i,j,:)=dehazed_img(i,j,:);
% else
% dehazed_img(i,j,:)=dehazed_img2(i,j,:);
% end
% end
% end
% %figure(11);imshow(dehazed_img);title('Dehazed Image after img2');
% for i=1:m
% for j=1:n
% if (img3(i,j,:)==img3mean)
% dehazed_img(i,j,:)=dehazed_img(i,j,:);
% else
% dehazed_img(i,j,:)=dehazed_img3(i,j,:);
% end
% end
% end
% Mapping of dehazing results with their respective regions
img1=zeros(size(img));
img2=zeros(size(img));
img3=zeros(size(img));
img_map_R=img_map(:,:,1);img_map_G=img_map(:,:,2); img_map_B=img_map(:,:,3);
I_cond= img_map_R~=0;
I_cond31=I_cond(:,:,[1 1 1]);
dehazed_img(I_cond31)=dehazed_img1(I_cond31);
img1(I_cond31)=dehazed_img1(I_cond31);
I_cond= img_map_G~=0;
I_cond32=I_cond(:,:,[1 1 1]);
dehazed_img(I_cond32)=dehazed_img2(I_cond32);
img2(I_cond32)=dehazed_img2(I_cond32);
I_cond= img_map_B~=0;
I_cond33=I_cond(:,:,[1 1 1]);
dehazed_img(I_cond33)=dehazed_img3(I_cond33);
img3(I_cond33)=dehazed_img3(I_cond33);
%figure(4);imshow([img_map img1 img2 img3]);title('Dehazed outputs from three different blocks are merged according to the image categorization');
% for i=1:m
% for j=1:n
% %disp('n:');disp(n);
% if (img(i,j,1)<=T) && (img(i,j,2)<=T) && (img(i,j,3)<=T)
% img1(i,j,:)=dehazed_img(i,j,:);
%
% elseif (img(i,j,1)>=U) && (img(i,j,2)>=U) && (img(i,j,3)>=U)
% img3(i,j,:)=dehazed_img(i,j,:);
%
% else
% img2(i,j,:)=dehazed_img(i,j,:);
% end
% end
% end
%dehazed_img=medfilt3(dehazed_img,[3 3 1]);
%figure(8);imshow([dehazed_img1 dehazed_img2 dehazed_img3]);title('Dehazed-1 vs Dehazed-2 vs Dehazed-3');
%dehazed_img=0.5*dehazed_img1+0.5*dehazed_img2;
%img1=im2uint8(img1);
%img1(img>T)=White(img>T);img3(img<U)=Black(img<U);
%dehazed_img(img1<T)=dehazed_img1(img1<T);
%dehazed_img(img1>T)=dehazed_img2(img1>T);
%dehazed_img(img3f>U)=dehazed_img3(img3f>U);
%dehazed_img(img>0.85)=dehazed_img1(img>0.85);
%figure(15);imshow([dehazed_img1 dehazed_img2]);title('Dark dehazed vs Bright dehazed');
%figure(13);imshow([img1 dehazed_img1]);title('Dark vs Dark Dehazed');
%figure(15);imshow([img2 dehazed_img2]);title('Bright vs Bright Dehazed');
%comp_final=comp_time0+comp_time1+comp_time2+comp_time3;
%imwrite(dehazed_img, ['results/' save_name '.png']);
%f=ones(3,3)/9;
%radius = 1;
%J1 = fspecial('disk', radius);
%r=medfilt2(dehazed_img(:,:,1));
%g=medfilt2(dehazed_img(:,:,2));
%b=medfilt2(dehazed_img(:,:,3));
%dehazed_img_smoothing = imfilter(dehazed_img,J1,'replicate',3);
%dehazed_img_smoothing=cat(3,r,g,b);
%figure;imshow([img dehazed_img]);title('Enhancement result');
Odehazed_img=im2uint8(dehazed_img);
%Odehazed_img2=im2uint8(dehazed_img4);
% img_brt=mean2(img);
% dehazed_img_brt=mean2(dehazed_img);
% img_crt = mean(img(img>0.5)) - mean(img(img<0.5));
% dehazed_img_crt = mean(dehazed_img(dehazed_img>0.5)) - mean(dehazed_img(dehazed_img<0.5));
%disp('Image brightness:'); disp(img_brt);
%disp('Dehazed Image brightness:'); disp(dehazed_img_brt);
%disp('Image contrast:'); disp(img_crt);
%disp('Dehazed Image contrast:'); disp(dehazed_img_crt);
Oimg=im2uint8(img);
%imhistmatch()
%Odehazed_img_pp=imhistmatch(Odehazed_img,dehazed_img1);
%Odehazed_img_pp=imadjust(Odehazed_img,[0 1],[0.15 0.85],1);
imwrite(Odehazed_img,outputFileName);
% figure;imshow([Oimg Odehazed_img]);title('hazy dehazed');
% drawnow;
% Exec_time=toc;
%
% if strlength(imagename) > 31
% imagename=imagename(strlength(imagename)-30:strlength(imagename));
% end
%
% filename = 'proposed3_AACT-gt-0.7_all_HDEth-0.6_new.xlsx';
% A = {'Execution Time'; Exec_time};
% xlswrite(filename,A,imagename)
% disp('Execution Time:');disp(Exec_time);
% for i=1:m
% for j=1:n
% %disp('n:');disp(n);
% if (img(i,j,1)<=T) && (img(i,j,2)<=T) && (img(i,j,3)<=T)
% img1(i,j,:)=img(i,j,:);
%
% elseif (img(i,j,1)>=U) && (img(i,j,2)>=U) && (img(i,j,3)>=U)
% img3(i,j,:)=img(i,j,:);
%
% else
% img2(i,j,:)=img(i,j,:);
% end
% end
% end
close all;
figure;
imshow([Oimg Odehazed_img]);title('GT hazy dehazed');
% figure;
% imshow(Oimg);title('Hazy');
% drawnow;
% imshow([img1 img2 img3]);title('Less-Affected vs Moderately-Affected vs More-Affected');
% drawnow;
%figure(5);
%imagesc(dehazed_img_smoothing);
%title('dehazed img smoothing');