Publication
Image and video denoising for distributed optical fibre sensors
Publications associées (32)
Enhanced Signal-Associated Noise in a φ-OTDR System
Luc Thévenaz, Malak Mohamed Hossameldeen Omar Mohamed Galal, Suneetha Sebastian
Owing to their high sensitivity with respect to external measurands, Rayleigh-based distributed optical fiber sensors (DOFS) find their way into applications in many industrial and academic sectors. To further transcend the limit of these sensors in terms ...
2022Evaluating measurement uncertainty in Brillouin distributed optical fibre sensors using image denoising
Luc Thévenaz, Marcelo Alfonso Soto Hernandez, Zhisheng Yang, Simon Adrien Zaslawski
In 2016, our research team proposed in an issue of Nature Communications1 the use of multidimensional signal processing, especially image denoising techniques, to improve the signal-to-noise ratio (SNR) of distributed optical fibre sensors. The benefits of t ...
2021Blind Universal Bayesian Image Denoising With Gaussian Noise Level Learning
Sabine Süsstrunk, Majed El Helou
Blind and universal image denoising consists of using a unique model that denoises images with any level of noise. It is especially practical as noise levels do not need to be known when the model is developed or at test time. We propose a theoretically-gr ...
IEEE2020On the 2D Post-Processing of Brillouin Optical Time-Domain Analysis
Luc Thévenaz, Zhisheng Yang, Simon Adrien Zaslawski
The benefits and limitations inherent to the 2D post-processing of measurements from Brillouin optical time-domain analyzers are investigated from a fundamental point of view. In a preliminary step, the impact of curve fitting on the precision of the estim ...
2020High Signal-to-Noise Ratio Stimulated Brillouin Scattering Gain Spectrum Measurement
Luc Thévenaz, Marcelo Alfonso Soto Hernandez, Zhisheng Yang, Kenny Hey Tow, Flavien Gyger
A technique to measure nonlinear processes, such as stimulated Brillouin scattering, with a very-high signal-to-noise ratio (SNR) is presented. Brillouin gain measurement with 77dB SNR is demonstrated over a 2m-long section of single-mode fiber. ...
Optical Society of America2018An illustrated comparison of processing methods for MR phase imaging and QSM: combining array coil signals and phase unwrapping
José Pedro Rebelo Ferreira Marques, Diana Khabipova
Phase imaging benefits from strong susceptibility effects at very high field and the high signal-to-noise ratio (SNR) afforded by multi-channel coils. Combining the information from coils is not trivial, however, as the phase that originates in local field ...
Wiley2017A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms
Jean-Philippe Thiran, Fabian Braun, Martin Proença
Electrical impedance tomography (EIT) is an emerging technology for real-time monitoring of patients under mechanical ventilation. EIT has the potential to offer continuous medical monitoring while being noninvasive, radiation free, and low cost. Due to th ...
Ieee-Inst Electrical Electronics Engineers Inc2017Intensifying the response of distributed optical fibre sensors using 2D and 3D image restoration
Luc Thévenaz, Marcelo Alfonso Soto Hernandez
Distributed optical fibre sensors possess the unique capability of measuring the spatial and temporal map of environmental quantities that can be of great interest for several field applications. Although existing methods for performance enhancement have e ...
Nature Publishing Group2016Sampling and Reconstruction of Shapes with Algebraic Boundaries
Martin Vetterli, Arash Amini, Mitra Fatemi
We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of to the image plane, where denotes the indicator function and is some r ...
2016A consensus algorithm for networks with process noise and quantization error
Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego
In this paper we address the problem of quantized consensus where process noise or external inputs corrupt the state of each agent at each iteration. We propose a quantized consensus algorithm with progressive quantization, where the quantization interval ...
IEEE2015