Study on de-noising of near infrared spectrum for wood based on wavelet transform modulus maximum

Spectral data of wood samples gathered by spectrometers are disturbed by a series of noise and interferences, therefore a proper data preprocessing is very important for model establishment and achievement of accurate analytical result. This paper directly applies wavelet transform and first derivative in spectrum preprocessing of Chinese fir. The results show that the combination of first derivative and wavelet transform modulus maximum can eliminate spectral noise and interference but reserve major information. It contributes to increase analysis quality and precision of the near infrared.