Improved double-threshold denoising method based on the wavelet transform

Preprocessing of spectral data is a key part of infrared spectroscopy and is an important basis for building robust models. Therefore, the measured signal needs to be preprocessed to achieve accurate and reliable measurement results. After sketching out the basic principles and basic methods of the wavelet transform, a new modified double-threshold denoising method combined with the proposed threshold method is presented in the paper. Two sets of comparative simulation experiments are also done to demonstrate the performance of the new denoising method. Block signals with a signal length of 2000 and the sinusoidal signal with a signal length of 1000 and the measured spectra are used for denoising with traditional schemes and the proposed method. The results of simulation data have demonstrated that the proposed method outperforms the traditional thresholding schemes for increasing the signal-to-noise ratio (SNR) without distorting the signal. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement