Peak Detection for Infrared Spectrum Based on Continuous Wavelet Transform

In spectrum analysis, peak detection is an essential step for subsequent analysis. Traditionally, peak detection procedure is divided into three consequent parts: smoothing, baseline correction and peak finding. The existing peak detection method based on continuous wavelet transform can combine the...

Full description

Saved in:
Bibliographic Details
Published in:Fēnxī huàxué 2011-06, Vol.39 (6), p.911-914
Main Authors: Cai, Tao, Wang, Xian-Pei, Du, Shuang-Yu, Yang, Jie
Format: Article
Language:chi ; eng
Subjects:
Continuous wavelet transform
Finishes
Infrared
Liapunov exponents
Noise
Ridges
Smoothing
Wavelet transforms
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In spectrum analysis, peak detection is an essential step for subsequent analysis. Traditionally, peak detection procedure is divided into three consequent parts: smoothing, baseline correction and peak finding. The existing peak detection method based on continuous wavelet transform can combine the baseline correction and peak finding into one part. It simplified the traditional peak detection procedure, but this method still has two parts. A method based on continuous wavelet transform which finishes the three parts at a time was proposed in this study. The baseline's function of original signal is monotone and linear, so after wavelet transform, there is no information of baseline in the wavelet coefficients. What we need do is deal with the coefficients. First, remove the noise in the coefficients based on Liapunov Exponent. Then, find the ridge mentioned in this study. The position of ridge is the peak's position. The proposed method further simplifies the peak detection procedure.
ISSN:0253-3820
DOI:10.3724/SP.J.1096.2011.00911