image = imread('C:\Users\Administrator\Desktop\1212.png');
%image = rgb2gray(image);
edgeThreshold = 0.2;
amount = 0.5;
data = localcontrast(image, edgeThreshold, amount);
PSNR1 = psnr(data, image);
fprintf('\n The Peak-SNR value of LCM is %0.4f', PSNR1);
t=1; % start index of the window (row)
limit=8; % window size of the contextual area
endt=limit; % end index of the window (row)
eqdata=zeros(size(data,1),size(data,2));
for x=1:size(data,1)
q=1; % start index of the window (column)
endq=limit; % end index of the window (column)
%% TO move Window to right and bottom, after exceeding the limit
for y=1:size(data,2)
eqdata(x,y)=0;
if (x>t+limit-1) %to move rows of window right
t=t+limit;
endt=limit+t-1;
end
if (y>q+limit-1) %to move cols of window right
q=q+limit;
endq=limit+q-1;
end
if (endt>size(data,1)) %to shift the rows of window to the next line
% t=t-64;
endt=size(data,1);
end
if (endq>size(data,2)) %to shift the cols of window to the next line
% q=q-64;
endq=size(data,2);
end
%% Counting the number of pixels in each contextual area
for i=t:endt
for j=q:endq
if data(x,y)==data(i,j)
eqdata(x,y)=eqdata(x,y)+1; %storing count of pixels values in matrix eqdata
end
end
end
end
end
%% Second Pass: Calculate partial rank, redistributed area and output values.
output=zeros(size(data,1),size(data,2));
cliplimit=0.3; % Cliplimit can vary between 0 to 1.
t=1;
endt=limit;
for x=1:size(data,1)
q=1;
endq=limit;
%% TO move Window to right and bottom, after exceeding the limit
for y=1:size(data,2)
cliptotal=0;
partialrank=0;
if (x>t+limit-1)
t=t+limit;
endt=limit+t-1;
end
if (y>q+limit-1)
q=q+limit;
endq=limit+q-1;
end
if (endt>size(data,1))
% t=t-64;
endt=size(data,1);
end
if (endq>size(data,2))
% q=q-64;
endq=size(data,2);
end
%% For each pixel (x,y), compare with cliplimit and accordingly do the clipping. Calculate partialrank.
for i=t:endt
for j=q:endq
if eqdata(i,j)>cliplimit
incr=cliplimit/eqdata(i,j);
else
incr=1;
end
cliptotal=cliptotal+(1-incr);
if data(x,y)>data(i,j)
partialrank=partialrank+incr;
end
end
end
%% New distributed pixel values can be found from redistr and will be incremented by partial rank.
redistr=(cliptotal/(limit*limit)).*data(x,y);
output(x,y)=partialrank+redistr;
end
end
figure('name','LCM-CLAHE','NumberTitle','off')
%da=adapthisteq(data);
imshow([image uint8(output)]); % Concatenate original and CLAHE image
figure('name','Histogram of input image','NumberTitle','off'); imhist(image); %Show the histogram of original image, LCM output and CLAHE output
figure('name','Histogram of LCM output','NumberTitle','off');imhist(data);
figure('name','Histogram of CLAHE output','NumberTitle','off');imhist(uint8(output));
PSNR = psnr(uint8(output), image);
fprintf('\n The Peak-SNR value of LCM-CLAHE is %0.4f', PSNR);
normal = adapthisteq(image,'clipLimit',0.02,'Distribution','rayleigh');
%imshow([image normal]);
PSNR0 = psnr(normal,image);
fprintf('\n The Peak-SNR value of CLAHE is %0.4f', PSNR0);
he = histeq(image);
PSNR2 = psnr(he,image);
fprintf('\n The Peak-SNR value of HE is %0.4f', PSNR2);
