WAVELET DENOISING OF INFRARED-SPECTRA

The application of wavelet denoising to infrared spectra was investiga ted, Six different wavelet denoising methods (SURE, VISU, HYBRID, MINM AX, MAD and WAVELET PACKETS) were applied to pure infrared spectra wit h various added levels of homo- and heteroscedastic noise, The perform ances of the wavelet denoising methods were compared with the standard Fourier and moving mean filtering in terms of root mean square errors between the pure and denoised spectra and visual quality of the denoi sed spectrum, The use of predictive ability as a possible objective cr iterion for denoising performance was also investigated, The main conc lusion is that for very low signal-to-noise ratios (SIN) the standard denoising methods (Fourier and moving mean) are comparable to the more sophisticated methods, At higher SIN levels the wavelet denoising met hods, in particular the HYBRID and VISU methods, are better, Wavelet m ethods are also better in restoring the visual quality of the denoised infrared spectra.