Publications associées à Débruitage par patchs

Geometrically-Conditioned Point Diffusion Models

Pascal Fua, Eduard Trulls Fortuny, Michal Jan Tyszkiewicz

Diffusion models generating images conditionally on text, such as Dall-E 2 [51] and Stable Diffusion[53], have recently made a splash far beyond the computer vision com- munity. Here, we tackle the related problem of generating point clouds, both unconditi ...

2023

Towards learning-based denoising of light fields

Touradj Ebrahimi, Michela Testolina, Tomás Soares De Carvalho Feith

In recent years, new emerging immersive imaging modalities, e.g. light fields, have been receiving growing attention, becoming increasingly widespread over the years. Light fields are often captured through multi-camera arrays or plenoptic cameras, with th ...

2023

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

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

Deep Gaussian denoiser epistemic uncertainty and decoupled dual-attention fusion

Sabine Süsstrunk, Majed El Helou, Xiaoyu Lin, Xiaoqi Ma

Following the performance breakthrough of denoising networks, improvements have come chiefly through novel architecture designs and increased depth. While novel denoising networks were designed for real images coming from different distributions, or for sp ...

2021

W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping

Sabine Süsstrunk, Daniel Sage, Thierry Laroche, Arne Seitz, Majed El Helou, Ruofan Zhou

In fluorescence microscopy live-cell imaging, there is a critical trade-off between the signal-to-noise ratio and spatial resolution on one side, and the integrity of the biological sample on the other side. To obtain clean high-resolution (HR) images, one ...

2020

On 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 ...

2020

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

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Débruitage par patchs

Geometrically-Conditioned Point Diffusion Models

Towards learning-based denoising of light fields

On combining denoising with learning-based image decoding

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

Deep Gaussian denoiser epistemic uncertainty and decoupled dual-attention fusion

W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping

On the 2D Post-Processing of Brillouin Optical Time-Domain Analysis

Image Restoration using Plug-and-Play CNN MAP Denoisers

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

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

Graph Chatbot

Chattez avec Graph Search

Towards learning-based denoising of light fields

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

W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping

On the 2D Post-Processing of Brillouin Optical Time-Domain Analysis

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Geometrically-Conditioned Point Diffusion Models

Deep Gaussian denoiser epistemic uncertainty and decoupled dual-attention fusion

On combining denoising with learning-based image decoding

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

Image Restoration using Plug-and-Play CNN MAP Denoisers