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A frequentistic and a bayesian approach for optimal optical filter design

: Taphanel, M.

Volltext urn:nbn:de:0011-n-3262801 (1.7 MByte PDF)
MD5 Fingerprint: 3a9464d089f0c29a53c928509b975777
Erstellt am: 10.2.2015

Beyerer, Jürgen (Ed.); Pak, Alexey (Ed.):
Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 2013. Proceedings : July, 21 - 27, 2013, Triberg-Nussbach in Germany
Karlsruhe: KIT Scientific Publishing, 2014 (Karlsruher Schriften zur Anthropomatik 17)
ISBN: 978-3-7315-0212-8
ISBN: 3-7315-0212-7
DOI: 10.5445/KSP/1000040668
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) <2013, Triberg-Nussbach>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

This report discusses three merit functions to optimize optical interference filter coatings. The applications of these filters are intentionally optical 3D sensors, e.g. a chromatic confocal triangulation sensor. Optimizing these optical filters is done by minimizing the measurement uncertainty of the sensor. The measurement task is handled as a parameter estimation problem and the sensor is considered as a physical experiment. As part of the experimental design, the optical filters are optimized to achieve measurements with lower uncertainty. The first merit function is based on a frequentistic statistic utilizing the Cramér-Rao lower bound. An example is used to point out disadvantages and two alternative merit functions are proposed. Instead of a lower bound, the other merit functions incorporate a specific estimator function.