Average filter Matlab - matlab

Question

I have written the 3x3 average filter. It works fine but it shows the same output image three times instead of one. How to resolve the problem?
The code is
function [filtr_image] = avgFilter(noisy_image)
[x,y] = size(noisy_image);
filtr_image = zeros(x,y);
for i = 2:x-1
for j =2:y-1
sum = 0;
for k = i-1:i+1
for l = j-1:j+1
sum = sum+noisy_image(k,l);
end
end
filtr_image(i,j) = sum/9.0;
filtr_image = uint8(filtr_image);
end
end
end
thanks in advance

Answer 1

What is most likely happening is the fact that you are supplying a colour image when the code is specifically meant for grayscale. The reason why you see "three" is because when you do this to allocate your output filtered image:
[x,y] = size(noisy_image)
If you have a 3D matrix, the number of columns reported by size will be y = size(noisy_image,2)*size(noisy_image,3);. As such, when you are iterating through each pixel in your image, in column major order each plane would be placed side by side each other. What you should do is either convert your image into grayscale from RGB or filter each plane separately.
Also, you have an unnecessary casting performed in the loop. Just do it once outside of the loop.
Option #1 - Filter per plane
function [filtr_image] = avgFilter(noisy_image)
[x,y,z] = size(noisy_image);
filtr_image = zeros(x,y,z,'uint8');
for a = 1 : z
for i = 2:x-1
for j =2:y-1
sum = 0;
for k = i-1:i+1
for l = j-1:j+1
sum = sum+noisy_image(k,l,a);
end
end
filtr_image(i,j,a) = sum/9.0;
end
end
end
end
Then you'd call it by:
filtr_image = avgFilter(noisy_image);
Option #2 - Convert to grayscale
filtr_image = avgFilter(rgb2gray(noisy_image));
Minor Note
You are using sum as a variable. sum is an actual function in MATLAB and you would be overshadowing this function with your variable. This will have unintended consequences if you have other functions that rely on sum later down the line.

Answer 2

I can't see why your code would repeat the image (unless it's a pattern cause by an integer overflow :/ ) but here are some suggestions:
if you want to use loops, at least drop the inner loops:
[x,y] = size(noisy_image);
filtr_image = zeros(x,y);
for i = 2:x-1
for j =2:y-1
% // you could do this in 1 line if you use mean2(...) instead
sub = noisy_image(i-1:i+1, j-1:j+1);
filtr_image = uint8(mean(sub(:)));
end
end
However do you know about convolution? Matlab has a built in function for this:
filter = ones(3)/9;
filtr_image = uint8(conv2(noisy_image, filter, 'same'));