MATLAB Answers

MSE Mean Square Error

547 views (last 30 days)
Soum
Soum on 3 Jul 2013
Commented: Salako on 9 Mar 2021
I De-noise some images and I want to evaluate them so I calculate SNR but I want to use another like Mean Square Error (MSE) I saw some people use it but I don't know what is express in my case I have a noisy image like input and De-noised one in the out put Or maybe PSNR please help me
  3 Comments
Salako
Salako on 9 Mar 2021
I have two RGB images to determine their MSE and PSNR.
Sir, kindly help me with the information required to get the task done.
My emmail is: kunlesky@gmail.com
Thankl you

Sign in to comment.

Accepted Answer

Image Analyst
Image Analyst on 3 Jul 2013
See my demo:
% Demo to calculate PSNR of a gray scale image.
% http://en.wikipedia.org/wiki/PSNR
% Clean up.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
%------ GET DEMO IMAGES ----------------------------------------------------------
% Read in a standard MATLAB gray scale demo image.
grayImage = imread('cameraman.tif');
[rows columns] = size(grayImage);
% Display the first image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Gray Scale Image', 'FontSize', fontSize);
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
% Get a second image by adding noise to the first image.
noisyImage = imnoise(grayImage, 'gaussian', 0, 0.003);
% Display the second image.
subplot(2, 2, 2);
imshow(noisyImage, []);
title('Noisy Image', 'FontSize', fontSize);
%------ PSNR CALCULATION ----------------------------------------------------------
% Now we have our two images and we can calculate the PSNR.
% First, calculate the "square error" image.
% Make sure they're cast to floating point so that we can get negative differences.
% Otherwise two uint8's that should subtract to give a negative number
% would get clipped to zero and not be negative.
squaredErrorImage = (double(grayImage) - double(noisyImage)) .^ 2;
% Display the squared error image.
subplot(2, 2, 3);
imshow(squaredErrorImage, []);
title('Squared Error Image', 'FontSize', fontSize);
% Sum the Squared Image and divide by the number of elements
% to get the Mean Squared Error. It will be a scalar (a single number).
mse = sum(sum(squaredErrorImage)) / (rows * columns);
% Calculate PSNR (Peak Signal to Noise Ratio) from the MSE according to the formula.
PSNR = 10 * log10( 256^2 / mse);
% Alert user of the answer.
message = sprintf('The mean square error is %.2f.\nThe PSNR = %.2f', mse, PSNR);
msgbox(message);
  8 Comments
hayat ali
hayat ali on 21 Feb 2019
thank yuo for your cooperation. but I have question
what are the range values that can be used in D, M,and V in both salt & pepper and gaussian
I = imread('eight.tif');
J = imnoise(I,'salt & pepper', D);
figure, imshow(I), figure, imshow(J)
J = imnoise(I,'gaussian ',M,V)

Sign in to comment.

More Answers (4)

ashkan abbasi
ashkan abbasi on 11 Apr 2014
% MSE & PSNR for a grayscale image (cameraman.tif) & its filtered
% version
clear
clc
im=imread('cameraman.tif');
im=im2double(im);
h1=1/9*ones(3,3);
imf1=imfilter(im,h1,'replicate');
h2=1/25*ones(5,5);
imf2=imfilter(im,h2,'replicate');
%
MSE1=mean(mean((im-imf1).^2));
MSE2=mean(mean((im-imf2).^2));
MaxI=1;% the maximum possible pixel value of the images.
PSNR1=10*log10((MaxI^2)/MSE1);
PSNR2=10*log10((MaxI^2)/MSE2);
  6 Comments
Salako
Salako on 9 Mar 2021
Good afternoon, sir.
Sir, I have two RGB images to determine their MSE and PSNR.
Sir, kindly help me with the information required to get the task done.
My email: kunlesky2@gmail.com
Thankl you, sir

Sign in to comment.


jensi asir
jensi asir on 18 Jan 2014
im also getting the same message which show 3 times psnr values ? whats the wrong in it.can you please help me
  1 Comment
Image Analyst
Image Analyst on 18 Jan 2014
You probably changed my demo to use a color image of your own.

Sign in to comment.


iza
iza on 20 Jan 2015
Can anyone check mine? Is it correct?...
%Load single MRI image I = imread('IM_00042.tif');
% addition of graininess (i.e. noise) I_noise = imnoise(I, 'gaussian', 0.09);
% the average of 3^2, or 9 values(filters the multidimensional array A with the multidimensional filter h) h = ones(3,3) / 3^2; I2 = imfilter(I_noise,h);
% Measure signal-to-noise ratio img=I; img=double(img(:)); ima=max(img(:)); imi=min(img(:)); mse=std(img(:)); snr=20*log10((ima-imi)./mse)
% Measure Peak SNR [peaksnr, snr] = psnr(I_noise, I); fprintf('\n The Peak-SNR value is %0.4f', peaksnr); fprintf('\n The SNR value is %0.4f \n', snr); fprintf('\n The MSE value is %0.4f \n', mse);
%Plot original & filtered figure
subplot(1,2,1), imshow(I_noise), title('Original image')
subplot(1,2,2), imshow(I2), title('Filtered image')
text(size(I,2),size(I,1)+15, ...
'Gaussian = 0.09', ...
'FontSize',10,'HorizontalAlignment','right');

Desmond Michael
Desmond Michael on 10 Feb 2016
Hello everyone, I've found a website regarding the above and its very helpful. http://vaaiibhav.me/calculating-the-psnr-and-mse-code-matlab/
  5 Comments
Image Analyst
Image Analyst on 27 Mar 2019
You have to decide what you want when you think of PSNR for a color image. Maybe you want the average PSNR of each color channel.

Sign in to comment.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!