Publications associées à Edge-preserving smoothing

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

On combining denoising with learning-based image decoding

Touradj Ebrahimi, Michela Testolina

Noise is an intrinsic part of any sensor and is present, in various degrees, in any content that has been captured in real life environments. In imaging applications, several pre- and post-processing solutions have been proposed to cope with noise in captu ...

SPIE2022

Image Denoising with Control over Deep Network Hallucination

Sabine Süsstrunk, Majed El Helou, Qiyuan Liang

Deep image denoisers achieve state-of-the-art results but with a hidden cost. As witnessed in recent literature, these deep networks are capable of overfitting their training distributions, causing inaccurate hallucinations to be added to the output and ge ...

Society for Imaging Science and Technology (IS&T)2022

Penalized denoising of vehicle trajectories collected by a swarm of drones

Nikolaos Geroliminis, Emmanouil Barmpounakis, Georgios Anagnostopoulos

Vehicle trajectory datasets collected in urban traffic environments with drones pose unique chal- lenges in terms of denoising due to extensive visual restrictions, perspective distortions and human- induced errors. This article taps into the unexplored po ...

2022

Evaluating 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 ...

2021

Blind 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 ...

IEEE2020

Image Restoration using Plug-and-Play CNN MAP Denoisers

Siavash Arjomand Bigdeli, David Honzátko

Plug-and-play denoisers can be used to perform generic image restoration tasks independent of the degradation type. These methods build on the fact that the Maximum a Posteriori (MAP) optimization can be solved using smaller sub-problems, including a MAP d ...

SCITEPRESS2020

Symplectic Model-Reduction with a Weighted Inner Product

Jan Sickmann Hesthaven, Babak Maboudi Afkham

In the recent years, considerable attention has been paid to preserving structures and invariants in reduced basis methods, in order to enhance the stability and robustness of the reduced system. In the context of Hamiltonian systems, symplectic model redu ...

2018

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Edge-preserving smoothing

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

On combining denoising with learning-based image decoding

Image Denoising with Control over Deep Network Hallucination

Penalized denoising of vehicle trajectories collected by a swarm of drones

Coarse graining and large-N behavior of the d-dimensional N-clock model

Evaluating measurement uncertainty in Brillouin distributed optical fibre sensors using image denoising

A reflected forward-backward splitting method for monotone inclusions involving Lipschitzian operators

Blind Universal Bayesian Image Denoising With Gaussian Noise Level Learning

Image Restoration using Plug-and-Play CNN MAP Denoisers

Symplectic Model-Reduction with a Weighted Inner Product

Graph Chatbot

Chattez avec Graph Search

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

Coarse graining and large-N behavior of the d-dimensional N-clock model

On combining denoising with learning-based image decoding

Blind Universal Bayesian Image Denoising With Gaussian Noise Level Learning

Image Denoising with Control over Deep Network Hallucination

A reflected forward-backward splitting method for monotone inclusions involving Lipschitzian operators

Evaluating measurement uncertainty in Brillouin distributed optical fibre sensors using image denoising

Penalized denoising of vehicle trajectories collected by a swarm of drones

Image Restoration using Plug-and-Play CNN MAP Denoisers

Symplectic Model-Reduction with a Weighted Inner Product