Best post processing procedure to filter data in thermography
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Hi.
I have some data from thermographic analysis, stored in a third dimensional tensor (pixel-pixel-time). The tensor contains just the amplitude of the signal captured by the thermocamera during the experiment.
In post-processing I am using the following steps in the following order:
- I am removing the background noise
- For each signal contained at each pixel (512 x 640 pixels) I am applying a moving average to smooth the data
- I am removing the gaussian noise
- I am removing the salt and pepper noise
- I am applying a custom made LowPassFilter at very low frequency
I was wondering if this is the most common sequence of steps in MATLAB.
Greetings
Luca
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