Binning.m

function [BinImages,NUM_BIN_IMAGES,MAX_DISTANCE] = Binning( image,BinSizes)

%% This function Bins the images based on BinSizes and returns a set of Binary Images(:BinSizes) ,the number of such Images(:BUM_BIN_IMAGES)
%  And the maximum value of a pixel(for grey scale it's 255)
%CODE

image = histeq(image);


MAX_DISTANCE = 255;

NUM_BIN_IMAGES = calculateNumBins_2Level(BinSizes,MAX_DISTANCE);


[row,col,~] = size(image);


BinImages = false(row,col,NUM_BIN_IMAGES);



q_offset = 0;
DistanceMatrix = zeros(row,col);

for r = 1:row
    for c = 1:col
        if size(image,3) == 1
            DistanceMatrix(r,c) = image(r,c);   %%ASSUMED GRAY SCALE IMAGE,OTHERWISE VALUE ARE RGB Euclidean distance
        else
            DistanceMatrix(r,c) = image(r,c);
        end
        
    end
end

for i = 1:numel(BinSizes)
    main_offset = ceil(MAX_DISTANCE/BinSizes(i));
    k = ceil((BinSizes(i)/2)) -1;
    % fprintf("\nMapping Image to Bin Size: %d",BinSizes(i));
    for r = 1:row
        for c = 1:col
            
            value = DistanceMatrix(r,c);
            
            x = q_offset+floor(value/BinSizes(i))+1;
            BinImages(r,c,x) = 1;
            
            if value>k && value<(((main_offset-1)*BinSizes(i))+k)        %%CHANGES IN MAX DISTANCE MADE
                y = q_offset+main_offset+ceil((value-k)/BinSizes(i));
                BinImages(r,c,y) = 1;
            end
            
        end
    end
    
    q_offset = q_offset+2*main_offset-1;
end
end