Volltext-Downloads (blau) und Frontdoor-Views (grau)

Supervised classification of monomodal and multimodal hyperspectral data in vibrational microspectroscopy: A comprehensive comparison

  • The application of Raman and infrared (IR) microspectroscopy is leading to hyperspectral data containing complementary information concerning the molecular composition of a sample. The classification of hyperspectral data from the individual spectroscopic approaches is already state-of-the-art in several fields of research. However, more complex structured samples and difficult measuring conditions might affect the accuracy of classification results negatively and could make a successful classification of the sample components challenging. This contribution presents a comprehensive comparison in supervised pixel classification of hyperspectral microscopic images, proving that a combined approach of Raman and IR microspectroscopy has a high potential to improve classification rates by a meaningful extension of the feature space. It shows that the complementary information in spatially co-registered hyperspectral images of polymer samples can be accessed using different feature extraction methods and, once fused on the feature-level, is in general more accurately classifiable in a pattern recognition task than the corresponding classification results for data derived from the individual spectroscopic approaches.

Download full text files

Export metadata

Additional Services

Search Google Scholar Check availability


Show usage statistics
Document Type:Article
Author:Christoph Pomrehn, Daniel Klein, Andreas Kolb, Peter Kaul, Rainer Herpers
Parent Title (English):Chemometrics and Intelligent Laboratory Systems
First Page:112
Last Page:122
Publishing Institution:Hochschule Bonn-Rhein-Sieg
Date of first publication:2018/11/28
Copyright:© 2018 The Authors. This is an open access article under the CC BY license.
Funding Information:This work was funded by the German Research Foundation (DFG) as part of the research training group GRK 1564 "Imaging New Modalities". We further acknowledge the doctoral scholarship provided by the Department of Computer Science at the Hochschule Bonn-Rhein-Sieg University of Applied Sciences.
Keyword:Chemical imaging; Multimodal hyperspectral data; Pattern recognition; Supervised classification; Vibrational microspectroscopy
Departments, institutes and facilities:Fachbereich Informatik
Fachbereich Angewandte Naturwissenschaften
Institut für Sicherheitsforschung (ISF)
Institute of Visual Computing (IVC)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
Entry in this database:2019/01/09
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International