Part 3: Median Filter - RGB Image

MATLAB CODE:

clear all

%READ THE RGB IMAGE

I = imread('peppers.png');

A = imnoise(I,'Salt & pepper',0.1);

figure,imshow(A);title('IMAGE WITH SALT AND PEPPER NOISE');

%DEFINE THE WINDOW SIZE MXN

M=3;

N=3;

%PAD THE MATRIX WITH ZEROS ON ALL SIDES

modifyA=padarray(A,[floor(M/2),floor(N/2)]);

B = zeros([size(A,1) size(A,2)]);

med_indx = round((M*N)/2); %MEDIAN INDEX

for i = 1:size(modifyA,1)-(M-1)

    for j = 1:size(modifyA,2)-(N-1)

       

       

        temp = modifyA(i:i+(M-1),j:j+(N-1),:);

        %RED,GREEN AND BLUE CHANNELS ARE TRAVERSED SEPARATELY

        for k = 1:3

          tmp = temp(:,:,k);

          B(i,j,k) = median(tmp(:));

        end

      

       

    end

end

%CONVERT THE IMAGE TO UINT8 FORMAT.

B = uint8(B);

figure,imshow(B);

title('IMAGE AFTER MEDIAN FILTERING');

EXPLANATION:

·        The image is read into the matrix I.  

·        Salt and pepper noise is added to the image.  Learn howto add 'salt and pepper noise to an image'.

·        Define the window size MxN example: 3x3, 7x7, 5x3

·        Pad the image with zeros on all sides. This is done to perform the filtering on the border pixels. Learn howto pad with zeros using MATLAB built_in function padarray.

·        Median is the middle point of the series. The index that is obtained by dividing the total number of elements in a window by 2 gives the position.

·        A sliding window of size M x N is used on each channel (Red, Green and Blue) separately and the elements in the window are sorted and the middle element from the sorted array is chosen.