Extended noise equalisation for image compression in microscopical applications
Today’s camera systems used for machine vision and scientific applications have intra-scene dynamic ranges up to 16 bit and therefore A/D converters with up to 16 bit resolution per pixel. Unfortunately, the linear amplification of electrons also forces a linear or even quadratic increase of the ima...
Gespeichert in:
| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
23.05.2019
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| In: |
Technisches Messen
Year: 2019, Jahrgang: 86, Heft: 7/8, Pages: 422-432 |
| ISSN: | 2196-7113 |
| DOI: | 10.1515/teme-2019-0022 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1515/teme-2019-0022 Verlag, Volltext: https://www.degruyterbrill.com/view/j/teme.2019.86.issue-7-8/teme-2019-0022/teme-2019-0022.xml 
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| Verfasserangaben: | Daniel M. Kirchhöfer, Gerhard A. Holst, Fred S. Wouters, Stephan Hock, Bernd Jähne |
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| 520 | |a Today’s camera systems used for machine vision and scientific applications have intra-scene dynamic ranges up to 16 bit and therefore A/D converters with up to 16 bit resolution per pixel. Unfortunately, the linear amplification of electrons also forces a linear or even quadratic increase of the image noise variance with the signal. Based on a method published in 2016 (B. Jähne, M. Schwarzbauer, tm-Technisches Messen 83.1), this paper describes a more general nonlinear transformation which equalizes the combined effect of temporal noise and photo-response non-uniformity (PRNU) and/or temporal noise in the illumination system of an image sensor. With this generalisation it is possible to use the equalisation also for microscopic applications for which an example is discussed. | ||
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