Noise and background removal in Raman spectra of ancient pigments using wavelet transform
✍ Scribed by Pablo Manuel Ramos; Itziar Ruisánchez
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 352 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0377-0486
- DOI
- 10.1002/jrs.1370
No coin nor oath required. For personal study only.
✦ Synopsis
The wavelet transform was applied to Raman spectra to remove heteroscedastic noise from ancient pigments such as azurite and ultramarine blue. Wavelets from the Daubechies, Coiflet and Symmlet families were evaluated. Two different thresholding strategies on the detail coefficients were applied; the first is a one-dimensional variance adaptive thresholding and the second is a block threshold denoising. The block thresholding strategy removes the noise and preserves the band shapes best. Background removal during the denoising process was also investigated and the results were very good when the block thresholding strategy was used to suppress background at the optimal level of the denoising process.
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## Abstract The Raman spectra of ethanolic solutions of CCl~4~ of different concentrations were measured and de‐noised by the wavelet transform method. The results show that noise can be filtered efficiently without changing the peak positions and the linear relationships between the peak intensity