Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Principal frequency component analysis based on modulate chopper technique used in diffuse reflectance spectroscopy measurement

Not Accessible

Your library or personal account may give you access

Abstract

Diffuse reflectance spectroscopy (DRS) is significantly affected from the interference of the ambient light and dark current of the instrument. Optical choppers, together with lock-in/synchronous amplification, can overcome these interferences. However, in spectral measurement, the sampling rate of the spectrometer is different from the Δ-pulse sampling, which is not high enough because of the integration time. In addition, the energy distribution is not perfectly concentrated as expected in modulate chopper technology. Therefore, in this study, based on the modulate chopper technique, we proposed a principal frequency component analysis (PFCA) method for DRS. This technique not only effectively eliminated the interference and dark current of the instrument but also improved the measurement precision using the energy of different frequencies. First, experiments were designed to successfully verify the function of optical choppers, eliminating the interference of the ambient light. Second, a set of 64 mixture solutions was designed and measured by DRS using the PFCA method to prove the feasibility of the proposed method. The solution was mixed with intralipid-20% suspension, India ink, and rhodamine B. These samples were analyzed by DRS under different conditions: no-chopper with overlapping and averaging, chopper demodulated by Fourier transform, and chopper demodulated by PFCA. The partial least square regression analysis was implemented to predict the concentration. Compared to the result of three methods, DRS equipped with chopper using the PFCA method showed the best results. The results of this study showed that the PFCA method not only satisfactorily eliminated the interference signals but also extracted useful information as much as possible, improving the analysis accuracy.

© 2018 Optical Society of America

Full Article  |  PDF Article
More Like This
Comparison of a physical model and principal component analysis for the diagnosis of epithelial neoplasias in vivo using diffuse reflectance spectroscopy

Melissa C. Skala, Gregory M. Palmer, Kristin M. Vrotsos, Annette Gendron-Fitzpatrick, and Nirmala Ramanujam
Opt. Express 15(12) 7863-7875 (2007)

Accuracy improvement of quantitative analysis in VIS-NIR spectroscopy using the GKF-WTEF algorithm

Xingwei Hou, Mengqiu Zhang, Gang Li, Han Tian, Shuqiang Yang, Xin Feng, Ling Lin, and Zhigang Fu
Appl. Opt. 58(28) 7836-7843 (2019)

In situ aberration measurement technique based on principal component analysis of aerial image

Lifeng Duan, Xiangzhao Wang, Anatoly Y. Bourov, Bo Peng, and Peng Bu
Opt. Express 19(19) 18080-18090 (2011)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (6)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (2)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (6)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.