├── README.md
└── fn_CLAHE.m


/README.md:
--------------------------------------------------------------------------------
 1 | # CLAHE
 2 | Contrast Limited Adaptive Histogram Equalization
 3 | Change your cliplimit for better outputs.
 4 | 
 5 | The simple histogram method suffers from intensity saturation which results
 6 | in information loss, which is not acceptable in the case of medical images. Thus,
 7 | whenever we want to retain the details of the image while improving the quality
 8 | of the image, CLAHE is one of the best option to go for. In medical images,
 9 | where intensity of the images are very dark, CLAHE provides a better image.
10 | 
11 | Steps to run the code:
12 | 1. Open MATLAB and go to the path where fn_CLAHE.m is stored.
13 | 2. Give the image name in Run as 'example.jpg'
14 | 3. Run the program and see your result
15 | 


--------------------------------------------------------------------------------
/fn_CLAHE.m:
--------------------------------------------------------------------------------
  1 | % This program is used to perform Contrast Limited Adaptive Histogram
  2 | % Equalization to the given image.
  3 | % Author : Ashwini Singh-HW 2 Computer Vision
  4 | % Input  : london.jpg(RGB image)
  5 | 
  6 | function []=fn_CLAHE(filename)
  7 | %% First pass: Count equal pixels
  8 | data=imread(filename);                 % filename : 'london.jpg'
  9 | data=rgb2gray(data);
 10 | t=1;                                   % start index of the window (row)
 11 | limit=8;                               % window size of the contextual area
 12 | endt=limit;                            % end index of the window (row)
 13 | eqdata=zeros(size(data,1),size(data,2));
 14 | for x=1:size(data,1)
 15 |     q=1;                                % start index of the window (column)
 16 |     endq=limit;                         % end index of the window (column)
 17 |     %% TO move Window to right and bottom, after exceeding the limit 
 18 |         for y=1:size(data,2)
 19 |         eqdata(x,y)=0;
 20 |         if (x>t+limit-1)
 21 |             t=t+limit;
 22 |             endt=limit+t-1;
 23 |         end
 24 |         if (y>q+limit-1)
 25 |             q=q+limit;
 26 |             endq=limit+q-1;
 27 |         end
 28 |         if (endt>size(data,1))
 29 |             % t=t-64;
 30 |             endt=size(data,1);
 31 |         end
 32 |         if (endq>size(data,2))
 33 |             %  q=q-64;
 34 |             endq=size(data,2);
 35 |         end
 36 |     %% Counting the number of pixels in each contextual area    
 37 |         for i=t:endt
 38 |             for j=q:endq
 39 |                 
 40 |                 if data(x,y)==data(i,j)
 41 |                     eqdata(x,y)=eqdata(x,y)+1;
 42 |                 end
 43 |                 
 44 |             end
 45 |         end
 46 |         
 47 |         
 48 |     end
 49 | end
 50 | 
 51 | %% Second Pass: Calculate partial rank, redistributed area and output values.
 52 | 
 53 | output=zeros(size(data,1),size(data,2));
 54 | cliplimit=0.3;                                  % Cliplimit can vary between 0 to 1.
 55 | t=1;
 56 | endt=limit;
 57 | for x=1:size(data,1)
 58 |     q=1;
 59 |     endq=limit;
 60 |     %% TO move Window to right and bottom, after exceeding the limit
 61 |     for y=1:size(data,2)
 62 |         
 63 |         cliptotal=0;
 64 |         partialrank=0;
 65 |         if (x>t+limit-1)
 66 |             t=t+limit;
 67 |             endt=limit+t-1;
 68 |         end
 69 |         if (y>q+limit-1)
 70 |             q=q+limit;
 71 |             endq=limit+q-1;
 72 |         end
 73 |         if (endt>size(data,1))
 74 |             % t=t-64;
 75 |             endt=size(data,1);
 76 |         end
 77 |         if (endq>size(data,2))
 78 |             % q=q-64;
 79 |             endq=size(data,2);
 80 |         end
 81 |         
 82 |         %% For each pixel (x,y), compare with cliplimit and accordingly do the clipping. Calculate partialrank. 
 83 |         for i=t:endt
 84 |             for j=q:endq
 85 |                 
 86 |                 
 87 |                 if eqdata(i,j)>cliplimit
 88 |                     
 89 |                     incr=cliplimit/eqdata(i,j);
 90 |                 else
 91 |                     incr=1;
 92 |                     
 93 |                 end
 94 |                 cliptotal=cliptotal+(1-incr);
 95 |                 
 96 |                 if data(x,y)>data(i,j)
 97 |                     partialrank=partialrank+incr;
 98 |                     
 99 |                 end
100 |                 
101 |             end
102 |             
103 |         end
104 |         %% New distributed pixel values can be found from redistr and will be incremented by partial rank.
105 |         
106 |         redistr=(cliptotal/(limit*limit)).*data(x,y);
107 |         output(x,y)=partialrank+redistr;
108 |         
109 |     end
110 | end
111 | figure('name','ASHWINI SINGH','NumberTitle','off')
112 | %da=adapthisteq(data);
113 | imshow([data uint8(output)]);          % Concatenate original and CLAHE image
114 | 
115 | 
116 | end


--------------------------------------------------------------------------------