MSE Mean Square Error
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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
采纳的回答
Image Analyst
2013-7-3
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);
9 个评论
rashed
2014-1-14
Sir, Please see the attached image. I copy and paste the code and found the result. I do not know what they are meaning. I am developing a steganography apps and for this analysis part i have to calculate the MSE and PSNR of the stego image and original image. Please help me out of this confussion sir. Thanks
Image Analyst
2014-1-14
That message box could not have been generated by my code if you look at my code. I only state the values once, not 3 times. Why don't you start a new discussion and post both your m-file and your image and we'll see how we can fix this?
rashed
2014-1-15
Sir I have told you that i only copy and paste this code but my result shows me like this. That's why i upload the message box why it show 3 times. Thanks
Image Analyst
2014-1-18
Somehow your cameraman.tif must have turned into a color image. The version of it that ships with MATLAB is definitely a grayscale image. What does this say:
[rows, columns, numberOfColorChannels] = size(grayImage)
It should say 256, 256, 1. If the third number is 3 then either you changed my demo to use a color image (most likely) or else somehow your cameraman.tif image is not the original one.
Rasheed Khankan
2016-3-14
I think that the maximum value is 255 not 256.
JDC
2017-10-2
That may well be. But he's referring to the dimensions of the image, not the pixel value.
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);
K = imnoise(I,'gaussian ',M,V);
From the imnoise() synopsis:
J = imnoise(I,'salt & pepper',D) adds "salt and pepper" noise to the
image I, where D is the noise density. This affects approximately
D*numel(I) pixels. The default for D is 0.05.
So D can obviously be anything from 0 to 1. Values outside that range will result in an error message.
Also from the synopsis:
The mean and variance parameters for 'gaussian', 'localvar', and
'speckle' noise types are always specified as if for a double image
in the range [0, 1].
So M can be anything real, and V can be anything real and positive. Given the fact that we're working in unit-scale though, it wouldn't make sense for V to be very large or for the magnitude of M to be far from zero.
更多回答（2 个）
ashkan abbasi
2014-4-11
% 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);
3 个评论
ameena begam
2015-6-10
hai,,ashkan my question is why u r using mean in MSE ,,why not using SUM function,,,thankyou,,please tell me
Image Analyst
2015-6-10
The M in MSE means "Mean". He should use immse() and psnr(), the built in functions, though, if he has a recent enough version of MATLAB.
Rasheed Khankan
2016-3-14
Great, concise, and operative code... Thanks a lot.
Desmond Michael
2016-2-10
编辑：Rik
2022-2-2
0 个投票
Hello everyone, I've found a website regarding the above and its very helpful. http://vaaiibhav.me/calculating-the-psnr-and-mse-code-matlab/
6 个评论
Image Analyst
2016-2-10
I don't see anything there at that web site - no zip file or download link like it says. Anyway, since my answer above, MATLAB has added built-in functions immse() and psnr() to make it easy for you.
Shaveta Arora
2016-2-13
编辑：Image Analyst
2016-2-13
Why is my Matlab is displaying
immse not found
and also psnr() is not there. Which versions support these built in functions?
Image Analyst
2016-2-13
编辑：Image Analyst
2016-2-13
immse() was introduced in R2014b and psnr() was introduced in R2014a. See my attached demo where I do it without toolbox functions, and as given in my Answer way up at the top.
indrani dalui
2019-3-26
This code are also calculate the PSNR for color image ?
Image Analyst
2019-3-27
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.
DGM
2023-2-12
Note that if you have a version newer than R2014x and you don't have psnr() or immse(), bear in mind that both are still part of the Image Processing Toolbox, so you'll also need that.
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