# Median filter without medfilt2

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Franzi on 7 Jun 2020
Commented: Rik on 19 Jun 2020
This question was flagged by Image Analyst
Hello everyone,

#### 1 Comment

Rik on 19 Jun 2020
Question recovered from Google cache:
Hello everyone,
I have to implement the median filter for a gray-scale picture and a variable window(for example 3x3, 5x5, 9x9, etc) without the built in function medfilt2. It's allowed to use median() and sort() and reshape(). In the edges where you cannot build the median, we should output the original value.
Can someone help me?

Matt J on 7 Jun 2020
Edited: Matt J on 7 Jun 2020
Since it's a homework assignment, I don't think you need to be computationally eficient. Just loop over all the appropriately sized sub-matrices of the image and apply median() to each... You could alos use blockproc()

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Franzi on 7 Jun 2020
ok, so there is now way in between medfilt2 and loops?
Matt J on 7 Jun 2020
None that minimizes memory consumption, I don't believe. You could unfold all of the window data using a very small loop like so,
Image=rand(300); %fake image
N=3; %window size
C=cell(1,N^2);
for i=1:N
for j=1:N
C{i,j} = reshape( Image(i:end+i-N,j:end+j-N) ,[],1);
end
end
C=cell2mat(C(:).');
Now you have a matrix C whos rows are the different NxN window data. You can now conveniently operate across the rows using sort() or whatever you want.. But note that this consumes N^2 times the amount of memory as a single image:
>> whos C
Name Size Bytes Class Attributes
C 88804x9 6393888 double
Franzi on 8 Jun 2020
ok, thank you!

Image Analyst on 7 Jun 2020
Franzi: I think I already gave you my nlfilter demo in your other question. All you had to do was change the function to do median() instead of thresholding. Here, I've attached a new m-file where I've done this easy change for you. I just replaced about 5 lines of code with a call to median - pretty easy.

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Franzi on 8 Jun 2020
ok, thank you!