@article {1544, title = {Automated estimation of white Gaussian noise level in a spectrum with or without spike noise using a spectral shifting technique}, journal = {Applied Spectroscopy}, volume = {60}, number = {7}, year = {2006}, note = {ISI Document Delivery No.: 063UWTimes Cited: 0Cited Reference Count: 19Schulze, H. Georg Yu, Marcia M. L. Addison, Christopher J. Blades, Michael W. Turner, Robin F. B.}, month = {Jul}, pages = {820-825}, type = {Article}, abstract = {Various tasks, for example, the determination of signal-to-noise ratios, require the estimation of noise levels in a spectrum. This is generally accomplished by calculating the standard deviation of manually chosen points in a region of the spectrum that has a flat baseline and is otherwise devoid of artifacts and signal peaks. However, an automated procedure has the advantage of being faster and operator-independent. In principle, automated noise estimation in a single spectrum can be carried out by taking that spectrum, shifting a copy thereof by one channel, and subtracting the shifted spectrum from the original spectrum. This leads to an addition of independent noise and a reduction of slowly varying features such as baselines and signal peaks; hence, noise can be more readily determined from the difference spectrum. We demonstrate this technique and a spike-discrimination variant on white Gaussian noise, in the presence and absence of spike noise, and show that highly accurate results can be obtained on a series of simulated Raman spectra and consistent results obtained on real-world Raman spectra. Furthermore, the method can be easily adapted to accommodate heteroscedastic noise.}, keywords = {ALGORITHM, automated noise determination, DETECTION LIMITS, limit of detection, NOISE, noise estimation, RAMAN, REMOVAL, signal-to-noise ratio, spectral noise, standard deviation}, isbn = {0003-7028}, url = {://000239046400016}, author = {Schulze, H. G. and Yu, M. M. L. and Addison, C. J. and Blades, M. W. and Turner, R. F. B.} }