- Calculate the error (subtraction)
- Square it
- Apply a mean filter to the result with a filter size you feel appropriate
Matlab: Mean Square Error
5 views (last 30 days)
Show older comments
Hi I am new to Matlab and I am having difficulties understanding the logic behind Mean Square Error. I have been given a signal and I am able to generate it and calculate SNR of the signal, is there a way to find mean square error between original signal and SNR signal?
% Number of Samples.
n = 1:512;
% Given Signal
signal = exp(-5*(n-250).^2/100000).cos(pi(n-250)/6);
% Range of SNR
Snr = 30:-5:-10
% Calculate and display MSE between the original signal and noisy signal
??????
3 Comments
Adam
on 2 May 2015
I'm still not sure exactly what aspect you are struggling on.
signal - noisy_signal;
is a subtraction.
a.^2
is a squaring of the an array a.
The Mathlab documentation includes plenty of help on applying a simple mean filter to the result of that.
Answers (1)
Image Analyst
on 1 May 2015
If you have the Image Processing Toolbox, use immse() or psnr().
4 Comments
Image Analyst
on 2 May 2015
Like Adam, I'm confused why this is so complicated and confusing to you. The name tells you how to do it. Let me do it in multiple steps.
Get the error
theError = signal - noisySignal;
Square it
squaredError = theError .^ 2;
Get the mean
% Use the mean() function.
I can't do every single step for you because it sounds like homework but the last step is unbelievably trivial.
One thing to get clarification on from your instructor is if the SNR is calculated based on the maximum signal, or is is supposed to apply on a element by element basis, which means the noise on the right will be less than on the left because the signal decays.
See Also
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!