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MATLAB code for Linear filtering without using imfilter function

  Linear Filter :          
      Linear filtering technique is used for reducing random noise, sharpening the edges and correcting unequal illuminations.           
                                                                          
  The procedure is carried out by filtering the image by correlation with an appropriate filter kernel.  The value of output pixel is calculated as a weighted sum of neighboring pixels.
                                                                                                                                             




MATLAB CODE:


 A=imread('eight.tif');
 figure,imshow(A);
 title('Original Image');

corr=[0 0.5 0.5;-1 0.5 0.2; 0.4 0.2 0;];
%corr=[0.5
   %    0.4
   %    0.1];
      
%corr=ones(5,5)/25;
      
%To pad the input image with zeros based on the kernel size.
Array padding can also be done using matlab built_in function padarray.


Example:


Let M=[4 5 6; 1 1 4; 7 8 8;];


M= [ 4     5     6
     1     1     4
     7     8     8]
                                                            
                                                 
M1=padarray(M,[1 1])
%Pad with zeros on all sides
M1 =


     0     0     0     0     0
     0     4     5     6     0
     0     1     1     4     0
     0     7     8     8     0
     0     0     0     0     0
                                                             
                                                                   
                                                                    
  

                                                               

>> M2=padarray(M,[2 2])
%pad with two rows and columns of zeros on all sides              
                                                         


M2 =


     0     0     0     0     0     0     0
     0     0     0     0     0     0     0
     0     0     4     5     6     0     0
     0     0     1     1     4     0     0
     0     0     7     8     8     0     0
     0     0     0     0     0     0     0
     0     0     0     0     0     0     0


>> M3=padarray(M,[1 2])
%Pad 1 row and 2 columns with zeros on all sides
M3 =


     0     0     0     0     0     0     0
     0     0     4     5     6     0     0
     0     0     1     1     4     0     0
     0     0     7     8     8     0     0
     0     0     0     0     0     0     0

   
pad1=size(corr,1)-1;
pad2=size(corr,2)-1;
output=uint8(zeros(size(A)));
if(size(corr,1)==1)
   
 B=zeros(size(A,1),size(A,2)+pad2);
 m=0;
 n=floor(size(corr,2)/2);
 sz1=size(B,1);
 sz2=size(B,2)-pad2;
elseif(size(corr,2)==1)
    B=zeros(size(A,1)+pad1,size(A,2));
    m=floor(size(corr,1)/2);
    n=0;
    sz1=size(B,1)-pad1;
   sz2=size(B,2);
else
    B=zeros(size(A,1)+pad1,size(A,2)+pad2);
    m=floor(size(corr,1)/2);
    n=floor(size(corr,2)/2);
   
    sz1=size(B,1)-pad1;
 sz2=size(B,2)-pad2;
end
 for i=1:size(A,1)
     for j=1:size(A,2)
         B(i+m,j+n)=A(i,j);
     end
 end
 szcorr1=size(corr,1);
 szcorr2=size(corr,2);
for i=1:sz1
    for j=1:sz2
        sum=0;
        m=i;
        n=j;
        for x=1:szcorr1
          for y=1:szcorr2
       %The weighted sum of the neighborhood pixels is calculated.
               sum=sum+(B(m,n)*corr(x,y));
               n =n+1;                    
           end
             n=j;
            m=m+1;
       end
        output(i,j)= sum;
    end
end
    figure,imshow(output);
    title('After linear filtering');



%For the correlation kernel ones(5,5)/25;




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5 comments:

ios198 said... Reply to comment

Your blog is so amazing! I followed this tutorial for Linear filtering. But the results of original imfilter in matlab and your method are not the same. Could you explain for me about that?

cyril auburtin said... Reply to comment

why not using corr2?

Robert Antony said... Reply to comment

Sir can u send cervix cancer images..

gomalian78 said... Reply to comment

It is interesting and good for students

farman Shah said... Reply to comment

its very usefull and amazing

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