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Blind Universal Bayesian Image Denoising With Gaussian Noise Level Learning

Publications associées (152)

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Sociologists have long been interested in the theoretical possibility of a universal ritual. Despite a growing number of indicators of world society and globalization, there have not been attempts to observe and analyze the international reach of particula ...

2021

Sociologists have long been interested in the theoretical possibility of a universal ritual. Despite a growing number of indicators of world society and globalization, there haven’t been attempts to observe and analyze the international reach of particular ...

2021

Systematic analysis of wavelet denoising methods for neural signal processing

Silvestro Micera

Objective. Among the different approaches for denoising neural signals, wavelet-based methods are widely used due to their ability to reduce in-band noise. All wavelet denoising algorithms have a common structure, but their effectiveness strongly depends o ...

IOP PUBLISHING LTD2020

Nowadays, efficient and remote health monitoring is becoming increasingly important, given both the ageing of population and the combined action of an increase in obesity level and cardiovascular diseases. The healthcare industry is becoming more reliant o ...

EPFL2020

Modeling for Ultra Low Noise CMOS Image Sensors

Raffaele Capoccia

The low-light performance of a CMOS image sensor (CIS) is one of the most important performance metrics in a camera, whether it is used in products for consumer electronics or in an image-acquisition system for machine vision or the Internet-of-Things (IoT ...

EPFL2020

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

Adaptive phase correction of diffusion-weighted images

Jean-Philippe Thiran, Marco Pizzolato, Maxime Descoteaux

Phase correction (PC) is a preprocessing technique that exploits the phase of images acquired in Magnetic Resonance Imaging (MRI) to obtain real-valued images containing tissue contrast with additive Gaussian noise, as opposed to magnitude images which fol ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2020

Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning

Sabine Süsstrunk, Majed El Helou

Blind and universal image denoising consists of 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-grounded ...

2019

A Bit Too Much? High Speed Imaging from Sparse Photon Counts

Edoardo Charbon, Claudio Bruschini, Samuel Burri

Recent advances in photographic sensing technologies have made it possible to achieve light detection in terms of a single photon. Photon counting sensors are being increasingly used in many diverse applications. We address the problem of jointly recoverin ...

IEEE2019

Learning Hawkes Processes Under Synchronization Noise

Patrick Thiran, Matthias Grossglauser, Negar Kiyavash, Seyed Jalal Etesami, William Trouleau

Multivariate Hawkes processes (MHP) are widely used in a variety of fields to model the occurrence of discrete events. Prior work on learning MHPs has only focused on inference in the presence of perfect traces without noise. We address the problem of lear ...

PMLR2019