Publication

Image and video denoising for distributed optical fibre sensors

Luc Thévenaz, Marcelo Alfonso Soto Hernandez
2017
Conference Papers

Résumé

A technique based on a multi-dimensional signal processing approach is here described for performance enhancement of distributed optical fibre sensors. In particular, the main features of linear and nonlinear image denoising techniques are described for signal-to-noise ratio enhancement in Brillouin optical time-domain analysers. Experimental results demonstrate the possibility to enhance the performance of distributed Brillouin sensors by more than 13 dB using a nonlinear image denoising approach, while more than 20 dB enhancement can be obtained with video denoising.

Source officielle

https://infoscience.epfl.ch/entities/publication/3fd89889-e460-4719-8c8e-6d702835f915

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Luc Thévenaz, Marcelo Alfonso Soto Hernandez
2017
Conference Papers

Résumé

Source officielle

https://infoscience.epfl.ch/entities/publication/3fd89889-e460-4719-8c8e-6d702835f915

À propos de ce résultat

Concepts associés (14)

Débruitage

Le débruitage est une technique d'édition qui consiste à supprimer des éléments indésirables (« bruit »), afin de rendre un document, un signal (numérique ou analogique) ou un environnement plus intelligible ou plus pur. Ne pas confondre le débruitage avec la réduction de bruit. Sur le plan sonore, le débruitage consiste à réduire ou anéantir le rendu d'ondes sonores « parasites » (ou « bruit »).

Rapport signal sur bruit

En électronique, le rapport signal sur bruit (SNR, ) est le rapport des puissances entre la partie du signal qui représente une information et le reste, qui constitue un bruit de fond. Il est un indicateur de la qualité de la transmission d'une information. L'expression d'un rapport signal sur bruit se fonde implicitement sur le principe de superposition, qui pose que le signal total est la somme de ces composantes. Cette condition n'est vraie que si le phénomène concerné est linéaire.

Total variation denoising

In signal processing, particularly , total variation denoising, also known as total variation regularization or total variation filtering, is a noise removal process (filter). It is based on the principle that signals with excessive and possibly spurious detail have high total variation, that is, the integral of the absolute is high. According to this principle, reducing the total variation of the signal—subject to it being a close match to the original signal—removes unwanted detail whilst preserving important details such as .

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