Merging two spectra from compact spectrometers with different detector technologies
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Oliver Lischtschenko
Oliver Lischtschenko studied physics at Greifswald University with a minor in economics. He received his PhD in physics from Greifswald University. Following a postdoc position at the Dutch FOM institute Rijnhuizen (currently called FOM DIFFER), he joint Rhein-Waal University of Applied Science in Kleve, Germany as a research professor for photometry & radiometry. Since 2011 Oliver Lischtschenko is supporting Germany´s researchers as Sales Engineer at OceanOptics. His interest is in optical spectroscopy and taking spectroscopy to new applications to make the world a cleaner, healthier and safer place.
and
Achim Kehrein
Achim Kehrein studied mathematics with minor subject physics at Duisburg University and Louvain University (B). He received his Ph.D. in mathematics from Auburn University (USA). He had postdoc positions at Hohenheim University working on error-correcting codes and at Dortmund University doing research in computer algebra. He had been senior researcher at Shell International (NL), but returned to academia to lecture at Wildau University. Since 2011 he is professor of Applied Mathematics at Rhine-Waal University. His research interests are widely spread with an emphasis on mathematical modelling and evolutionary algorithms.
Abstract
This paper describes the merging of spectra measured by two different spectrometers. Different concepts for merging data from different instruments are presented. All existing approaches violate the conservation law of energy when comparing measurements from two different instruments. The fundamental cause behind violation of the energy conservation law lies in the properties of the measurement device itself. Data can only be merged successfully if the distortion caused by both instruments is small. Typical real-life examples for spectral measurements are shown and the applicability of merging of the data is evaluated for these cases.
Zusammenfassung
Diese Arbeit beschreibt die Zusammenführung von Spektren, welche von zwei verschiedenen Spektrometern stammen. Verschiedene Konzepte für die Zusammenführung von Daten aus verschiedenen Instrumenten werden vorgestellt. Alle existierenden Ansätze verletzen den Energieerhaltungssatz, wenn man Messungen von zwei verschiedenen Instrumenten vergleicht. Die grundlegende Ursache für die Verletzung des Energieerhaltungssatzes liegt in den Eigenschaften des Messgerätes selbst. Daten können nur dann erfolgreich zusammengeführt werden, wenn die von beiden Geräten verursachte Verzerrung klein gegenüber typischen charakteristischen Skalen ist. Es werden typische Beispiele aus der Praxis für Spektralmessungen gezeigt und die Anwendbarkeit der Datenfusion für diese Fälle bewertet.
About the authors
Oliver Lischtschenko studied physics at Greifswald University with a minor in economics. He received his PhD in physics from Greifswald University. Following a postdoc position at the Dutch FOM institute Rijnhuizen (currently called FOM DIFFER), he joint Rhein-Waal University of Applied Science in Kleve, Germany as a research professor for photometry & radiometry. Since 2011 Oliver Lischtschenko is supporting Germany´s researchers as Sales Engineer at OceanOptics. His interest is in optical spectroscopy and taking spectroscopy to new applications to make the world a cleaner, healthier and safer place.
Achim Kehrein studied mathematics with minor subject physics at Duisburg University and Louvain University (B). He received his Ph.D. in mathematics from Auburn University (USA). He had postdoc positions at Hohenheim University working on error-correcting codes and at Dortmund University doing research in computer algebra. He had been senior researcher at Shell International (NL), but returned to academia to lecture at Wildau University. Since 2011 he is professor of Applied Mathematics at Rhine-Waal University. His research interests are widely spread with an emphasis on mathematical modelling and evolutionary algorithms.
References
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2. Brady, D. J.: Optical Imaging and Spectroscopy. John Wiley & Sons, 2009. doi:10.1002/9780470443736. In particular Chapter 9.2.Search in Google Scholar
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