Fourier self-deconvolution in coherent anti-Stokes Raman scattering spectrum analysis
Fedyunina, Olga (2009)
Diplomityö
Fedyunina, Olga
2009
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe200905181495
https://urn.fi/URN:NBN:fi-fe200905181495
Tiivistelmä
Coherent anti-Stokes Raman scattering (CARS) microscopy is rapidly developing into a unique microscopic tool in biophysics, biology and the material sciences. The nonlinear nature of CARS spectroscopy complicates the analysis of the received spectra. There were developed mathematical methods for signal processing and for calculations spectra. Fourier self-deconvolution is a special high pass FFT filter which synthetically narrows the effective trace bandwidth features. As Fourier self-deconvolution can effectively reduce the noise, which may be at a higher spatial frequency than the peaks, without losing peak resolution. The idea of the work is to experiment the possibility of using wavelet decomposition in spectroscopic for background and noise removal, and Fourier transformation for linenarrowing.