欢迎访问林业科学,今天是

林业科学 ›› 2008, Vol. 44 ›› Issue (10): 109-112.doi: 10.11707/j.1001-7488.20081019

• 论文 • 上一篇    下一篇

基于小波模极大值的木材近红外光谱去噪

王学顺1,2 戚大伟1 黄安民3   

  1. 1.东北林业大学理学院,哈尔滨150040;2.北京林业大学理学院,北京100083;3.中国林业科学研究院木材工业研究所,北京100091
  • 收稿日期:2008-04-18 修回日期:1900-01-01 出版日期:2008-10-25 发布日期:2008-10-25

Denoising of Near Infrared Spectroscopy in Wood Based on Wavelet Transform Modulus Maximum

Wang Xueshun1,2,Qi Dawei1,Huang Anmin3   

  1. 1.College of Science,Northeast Forestry University Harbin 150040; 2. College of Science,Beijing Forestry University Beijing 100083;3.Research Institute of Wood Industry,CAF Beijing 100091
  • Received:2008-04-18 Revised:1900-01-01 Online:2008-10-25 Published:2008-10-25

摘要: 将光谱一阶导数与小波变换相结合,对杉木木材近红外光谱数据进行预处理,采用db3小波对光谱数据进行4尺度分解,在各分解尺度上根据信号和噪声的不同传播特性,保留信号的模极大值,去除噪声的模极大值。结果表明:光谱导数+小波变换模极大值能够有效消除光谱噪声和各种因素干扰,并很好保留了光谱信号特征,使光谱信噪比有了较大提高。

关键词: 近红外光谱, 小波变换, 模极大值, 去噪

Abstract: Spectroscopic data of wood samples gathering by spectroscopic instruments are disturbed by a series of noises and interferences,therefore the proper data preprocessing is very important for model establishment and achievement of accurate analytical result. This paper was direct application of wavelet transform combined with first derivative in spectrum preprocessing of Chinese Fir. Using the db3 wavelet to resolve spectrum data in four races. In addition,according to the different characteristics of transformation between signal and noise in different resolve races,to hold back the maximum of signal model and dislodge the minimum of the noise model.The results showed that the combination of first derivative and wavelet transform modulus maximum was able to eliminate spectroscopic noises and interferences as well as reserve major information. It contributed to increase analysis quality and precision of the near infrared.

Key words: near infrared spectroscopy, wavelet transform, modulus maximum, denoising