thankgod1wlov.m

its a noise removal algorithm which works effectively

clc;
close all;
clear all;
global zp;
q=imread('cameraman.tif');
[r g b]=size(q);
if (b==3)
    q=rgb2gray(q);
end
%n1=q;
n1=imnoise(q,'gaussian',0,.02);
n1=imresize(n1,[256 256]);
subplot(2,2,1),imshow(n1);
[a b]=size(n1);
zp=zeros(a+9,b+9);
[s1 s2]=size(zp);

for i=10:s1-9
    for j=10:s2-9
        zp(i,j)=n1(i-8,j-8);
    end
end
% imshow(uint8(zp));
zp1=zp;
for i=10:s1-9
    for j=10:s2-9
        w=zp1(i-1:i+1,j-1:j+1);
        m=mean2(w);
        zp1(i,j)=m;
    end
end
subplot(2,2,2),imshow(uint8(zp1));
g=gradient(zp1);
%subplot(2,3,3),imshow((g));
g1=abs(g);
[a1 b1]=size(g1);
arr=[];
o=[6 8 10 12 14 15 17 18 19 20];
%   for n=1:10
%       op=zeros(size(zp));
for i=9:a1-9
    for j=9:b1-9
        if(g1(i,j)<17)
            g2(i,j)=1;

        else
            g2(i,j)=0;
        end
    end
end
[l,num]=bwlabel(g2,8);
for k=1:num
    va=[];
    [r c]=find(l==k);
    %         for i=1:size(r,1)
    %             va(i)=zp(r(i),c(i));
    %         end
    arsize(k)=size(r,1);
    %         v(k)=var(va);
end
[sorted index]=sort(arsize,'descend');
index1=index(1);
[r1 c1]=find(l==index1);
for i=1:size(r1,1)
    var1(i)=zp(r1(i),c1(i));
end
v=var(var1);
th=median(v).*.3;
n=1;
flag=0;
for i=9:a1-9
    for j=9:b1-9
        n=1;
        vari=switch1(i,j,n);
        if (vari<th)
            w1=zp(i-n:i+n,j-n:j+n);
            zp1(i,j)=mean2(w1);
        else
            while((vari>th) && (flag==0))
                n=n+1;
                vari=switch1(i,j,n);
               
                if (n==7)
                    flag=1;
                end
            end
            w1=zp(i-n:i+n,j-n:j+n);
            zp1(i,j)=mean2(w1);
        end

    end
end
figure,imshow(uint8(zp1));
%     if(l==1)
%         arr=[arr zp(i,j)];
%     end
%      num1(n)=[ num];
%      [r c]=find(l~=0);
%      for ii=1:size(r,1)
%          op(r(ii),c(ii))=zp(r(ii),c(ii));
%      end
%      v(n)=[ var(var(op))];
%     end
%      subplot(2,2,3:4),stem(o,num1);
%      xlabel('threshold');
%      ylabel('number of conn region');
%
% subplot(2,3,4),imshow(g1);
% l=bwlabeln(g1,8);
% subplot(2,3,5),imshow(l);
% subplot(2,3,6),plot(num,m);
% n=1;
% flag=0;
% varia=[];
% for i=10:a1-9
%     for j=10:b1-9
%         w=sir(i,j,n);
%         while (w==0)& (flag==0)
%             n=n+1;
%             if (n==5)
%                 flag=1;
%             end
%         end
%         w1=zp(i-n:i+n,j-n:j+n);
%         varia=[ (var(w1))];
%     end
% end