To find the MSE value



%Let me explain with the same example.
%To the input image Iimg applied the 'Salt & Pepper noise' with the noise ratio of 20% and named as 'Nimg'.
%Now for the 'Nimg' i applied median filter and named as Mimg.
%Now i need to find the 'Mean Square Error' MSE comparison between Mimg and Nimg.


clear all
close all
clc;
Iimg=imread('moon.tif');
[r c]=size(  Iimg );
d=ndims( Iimg );
if d == 3
     Iimg =rgb2gray( Iimg );
end
Iimg=double( Iimg );
Iimg= Iimg /225;
Nimg=imnoise( Iimg ,'salt & pepper',0.2);
Mimg=medfilt2( Nimg ,[5 5]);
clc;
Diff= Nimg - Mimg ;
MSE= sum(sum(Diff.* Diff)) / (r * c);
fprintf('\n\nThe Mse value is:  %d',MSE1);
subplot(1,2,1);imshow( Nimg );title('Noised image');
subplot(1,2,2);imshow( Mimg );title('Denoised image');


RESULT:


The Mse value is:  2.521604e-002

i.e, MSE ~ 0.0252


Comments

  1. navyaApril 26, 2013 at 3:26 PM

    Hey.. You have Nice Blog..


    Image Processing India

    ReplyDelete
  2. AnonymousSeptember 24, 2013 at 7:08 PM

    How u convert that Mse value?? Will u pls explain??

    ReplyDelete
    Replies
    1. Digital image procesingFebruary 16, 2014 at 11:10 PM

      MSE is an average of the squares of the difference between the actual observations and those predicted observations. MSE gives larger result values for larger errors and gives small result values for small errors.

      Delete
  3. UnknownMarch 8, 2017 at 2:38 AM

    Plz I need to calculate mse from SD how can I do it ?
    Mse= SD*SD/n?????
    Is this write or wrong?

    ReplyDelete
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