Removing noise from a signal

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MINA 2016-9-20

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评论： Star Strider 2021-4-7

I have a following signal, and I want to correct the part which has a sharp jump, based on the value of the signal sometimes before the jump and its future values.

Instead of that jump I want something like a red line or green line, or something in between (sth that is most likely to be the signal instead of that noise based on the behavior of the signal in the pas and in the future.) Any suggestions?

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Answer 1

Image Analyst 2016-9-20

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在 MATLAB Online 中打开

You can use a modified median filter. Basically compute the median. Then find any points where the actual signal is some factor higher than the median signal. Replace those points with the median. Something like

medianSignal = medfilt1(signal, 5); % Smooth signal
badIndexes = abs(signal-medianSignal) > someValue; % Find bad ones
signal(badIndexes) = medianSignal(badIndexes); % Repair signal

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Image Analyst 2016-9-21

You want something more complicated? Usually we hear the opposite - the solutions we offer are too complicated and the poster wants something simpler. There are tons of denoising algorithms out there. I'm not as familiar with 1-D signal denoising algorithms as with 2-D image denoising algorithms. You could do Fourier filtering in the spectral domain like Star suggested. This will filter the entire signal. So you have to ask yourself if it's okay to filter the entire signal or if you want just the spike fixed and all the other values to remain untouched. Keep in mind though that Fourier filtering will get rid of the spike more than it will affect the small little humps. You may not observe too much change in those small humps. I'm not sure if 2-D methods will work on a 1-D vector but they might. And you'll be happy to hear they're much more complicated. And they work better. State of the art image denoising algorithms include BM3D, non-local means, wavelets, K-SVD, K-LLD, UINTA, etc.

For a whole bunch of info on denoising, click here or here

A nice overview of a bunch of image filters can be found here: https://users.soe.ucsc.edu/~milanfar/publications/journal/ModernTour.pdf

Usually BM3D is found to be the best and state of the art, except of course when someone is publishing a paper trying to top it. However non-local means might be good in your case. There is a version of non-local means in the File Exchange that has been applied to 1-D ECG signals http://www.mathworks.com/matlabcentral/fileexchange/41762-non-local-means--nlm--denoising-for-time-series--applied-to-ecg

Chappi 2020-2-11

aahhh. I want to try out your suggestion but I dont have signal processing toolbox. Would you please recommend sth else silimar with medfilt ? THank you

Christine Tobler 2020-2-11

The function smoothdata in basic MATLAB (introduced in R2017a) has a median filter.

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Answer 2

Star Strider 2016-9-20

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The ‘spike’ creates broadband, high-frequency noise. I would first do a fft of your signal to understand the frequency composition, then design a lowpass or bandpass filter to keep your frequencies of interest, and use it to filter your signal.

There are many ways to design filters in MATLAB, probably the easiest being designfilt. My IIR filter design procedure is outlined in: How to design a lowpass filter for ocean wave data in Matlab? Remember to do the actual filtering with the filtfilt function.

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632541 2021-4-7

Can i use built in function for LPF in matlab instead of designfilt or filtfilt

Star Strider 2021-4-7

I would use the lowpass function (introduced in R2018a) if you have it. Otherwise, designing the filter from command-line functions is the only option.

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