A Comparison of Fourier and Wavelet Transforms in the Processing of near Infrared Spectroscopic Data: Part 1. Data Compression-Reference-Cited by-同舟云学术

A Comparison of Fourier and Wavelet Transforms in the Processing of near Infrared Spectroscopic Data: Part 1. Data Compression

Published:2003-02 Issue:1 Volume:11 Page:3-15
ISSN:0967-0335
Container-title:Journal of Near Infrared Spectroscopy
language:en
Short-container-title:Journal of Near Infrared Spectroscopy

Author:

Fearn Tom¹,Davies Anthony M.C.²

Affiliation:

1. Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK

2. Norwich Near Infrared Consultancy, 75 Intwood Road, Cringleford, Norwich NR4 6AA, UK

Abstract

The advent of spectral imaging and recent trends towards the compilation of large spectral databases have caused renewed interest in the compression of near infrared spectra for purposes of storage. A comparison of approaches using Fourier and wavelet transforms shows that wavelets are generally, though not always, more efficient than Fourier at compressing near infrared spectra. The Daubechies extremal phase wavelet of order 4 is a good choice for this purpose.

Publisher

SAGE Publications

Subject

Spectroscopy

Link

http://journals.sagepub.com/doi/pdf/10.1255/jnirs.349

Reference16 articles.

1. The Use of Trigonometric Polynomials to Approximate Visible and near Infrared Spectra of Agricultural Products

2. An algorithm for the machine calculation of complex Fourier series

3. Fourier Analysis Enhances NIR Diffuse Reflectance Spectroscopy

4. McClure W.F. and Davies A.M.C., in Analytical Applications of Spectroscopy, Ed by Creaser C.S. and Davies A.M.C. Royal Society of Chemistry, London, p. 414 (1988).

5. Near infrared analysis of foods. Near infrared analysis in the Fourier domain with special reference to process control

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prototype near-infrared (NIR) reflectance spectrometer for the analysis of maize flour;Instrumentation Science & Technology;2021-02-27

2. Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue—Critical Overview;Sensors;2020-09-24

3. Non-destructive prediction of soluble solids and dry matter contents in eight apple cultivars using near-infrared spectroscopy;Postharvest Biology and Technology;2019-05

4. Discrimination of organic and conventional rice by chemometric analysis of NIR spectra: a pilot study;Journal of Food Measurement and Characterization;2018-10-03

5. Optimization criteria in sample selection step of local regression for quantitative analysis of large soil NIRS database;Chemometrics and Intelligent Laboratory Systems;2012-01