%Kuan filter for speckle noise reduction
%Usage - kuan(I)
%I is the noisy image (gray level image m x n x 1)

function [kn]=kuan(I)
[x y z]=size(I)
I=double(I);
for i=1:x
    i
    for j=1:y
        % Checking first and last pixel of first row% 
        if (i==1 & j==1)
            mat(1)=0;
            mat(2)=0;
            mat(3)=0;
            mat(4)=0;
            mat(5)=I(i,j);
            mat(6)=I(i,j+1);
            mat(7)=0;
            mat(8)=I(i+1,j);
            mat(9)=I(i+1,j+1);
        end
        
        if (i==1 & j==y)
            mat(1)=0;
            mat(2)=0;
            mat(3)=0;
            mat(4)=I(i,j-1);
            mat(5)=I(i,j);
            mat(6)=0;
            mat(7)=I(i+1,j-1);
            mat(8)=I(i+1,j);
            mat(9)=0;
        end
        
        % Checking first and last pixel of last row% 
        if (i==x & j==1)
            mat(1)=0;
            mat(2)=I(i-1,j);
            mat(3)=I(i-1,j+1);
            mat(4)=0;
            mat(5)=I(i,j);
            mat(6)=I(i,j+1);
            mat(7)=0;
            mat(8)=0;
            mat(9)=0; 
        end
        
        if (i==x & j==y)
            mat(1)=I(i-1,j-1);
            mat(2)=I(i-1,j);
            mat(3)=0;
            mat(4)=I(i,j-1);
            mat(5)=I(i,j);
            mat(6)=0;
            mat(7)=0;
            mat(8)=0;
            mat(9)=0;
        end
        % Checking rest of the image%
        
        if (i>1 & i<x & j>1 & j<y)
            mat(1)=I(i-1,j-1);
            mat(2)=I(i-1,j);
            mat(3)=I(i-1,j+1);
            mat(4)=I(i,j-1);
            mat(5)=I(i,j);
            mat(6)=I(i,j+1);
            mat(7)=I(i+1,j-1);
            mat(8)=I(i+1,j);
            mat(9)=I(i+1,j+1);
        end
        y1=I(i,j);
        ybar=mean(mean(mat));
        ystad=std2(mat);
        ENL=(ybar/ystad)^2;
        sx2=((ENL*(ystad)^2)-(ybar)^2)/(ENL+1);
        xcap=ybar+(sx2*(y1-ybar))/(sx2+((ybar^2+sx2)/ENL));
        N(i,j)=xcap;
    end
end
kn=uint8(N);