This book (Practical Electron Microscopy and Database) is a reference for TEM and SEM students, operators, engineers, technicians, managers, and researchers.

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Some spectra, e.g. the spectra from FK edge, can be very noisy so that deconvolution is needed to reduce the noise. The deconvolution can be performed, for instance, by Pixon based method [1, 2] In this process, the corresponding low loss spectra are used as a pointresponse function (PRF). The restored spectra are summed with the main peak position aligned at the same energy so that the remaining statistical noise is reduced.
However, in many cases with the presence of random noise, even the application of deconvolution (e.g. RL deconvolution) will still not allow the reliable determination of relatively small resonance features in the spectra.
If the noise in an EELS profile is large , a practical procedure to study the profile, e.g. SSD, is:
i) Use SavitzkyGolay filter to smoothen the raw spectra.
ii) Compute the first derivative.
iii) Find the useful information, for instance, related to electronic structures of the materials.
[1] S. Muto, R. C. Puetter and K. Tatsumi: J. Electron Microscopy 55
(2006) 215–223.
[2] S. Muto, K. Tatsumi, R. C. Puetter, T. Yoshida, Y. Yamamoto and Y. Sasano: J. Electron Microscopy 55 (2006) 225–230.
