STM experiment (HOPG) data analysis/image processing

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Discussion Overview

The discussion revolves around the analysis and image processing of STM (Scanning Tunneling Microscopy) data from a HOPG (Highly Ordered Pyrolytic Graphite) sample. Participants are exploring methods to reduce noise in the captured image using MATLAB, specifically through techniques like Fourier transform.

Discussion Character

  • Exploratory, Technical explanation, Homework-related

Main Points Raised

  • One participant shares a picture of carbon atoms in a graphene sample and seeks advice on removing noise from the image using MATLAB.
  • Another participant suggests using Fourier transform to eliminate high-frequency noise by setting components above a certain cut-off to zero before back-transforming.
  • A subsequent reply expresses excitement about the image quality and requests guidance on implementing the cut-off in MATLAB.
  • A later post indicates that setting elements of a matrix to zero is feasible in MATLAB, implying a potential solution.

Areas of Agreement / Disagreement

Participants generally agree on the potential of using Fourier transform for noise reduction, but specific implementation details remain unresolved.

Contextual Notes

Limitations: The discussion does not clarify the specific methods for applying the cut-off in MATLAB or the exact nature of the noise present in the image.

Who May Find This Useful

Researchers and students working with STM data analysis, image processing in MATLAB, or those interested in noise reduction techniques in microscopy images.

itzik26
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hi,
I've got a really great picture of the carbon atoms in a graphine (HOPG) sample, using STM technique (picture attached). I would like to remove from the picture all the data came from noise etc.. I'm working with MATLAB, and I tried to use fast Fourier transform (fft2), but didn't know how to move on from there. I've also tried to use the "filter" command, but without any success. Does somebody have any idea? thanks
 

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The picture looks pretty good as it is, why not show it without more processing?

Otherwise, you can try to Fourier transform it. Then select a cut-off and set the Fourier components above that to zero, then back-transform. This will remove high-frequency noise.
 
it really looks good, doesn't it?? I got really excited :)

do you know how can I do this cut-off in matlab?
 
Setting elements of a matrix to zero? You should be able to do that in Matlab...
 

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