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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
S.127-137
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) <2013, Triberg-Nussbach>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Abstract
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.

: http://publica.fraunhofer.de/dokumente/N-326280.html