Publications associées à Progressive Coding of 3-D Objects Based on Overcomplete Decompositions

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 Institute of Electrical and Electronics Engineers2023

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Touradj Ebrahimi

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

IEEE COMPUTER SOC2023

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Yunus Inan

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

EPFL2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Gionata Ghiggi, Anne-Claire Marie Billault--Roux

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo, Chaofan He

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Learned Compressive Representations for Single-Photon 3D Imaging

Claudio Bruschini, Edoardo Charbon, Andrei Ardelean, Mohit Gupta

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that ...

Ieee Computer Soc2023

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Thomas Jean Debarre

The goal of this thesis is to study continuous-domain inverse problems for the reconstruction of sparse signals and to develop efficient algorithms to solve such problems computationally. The task is to recover a signal of interest as a continuous function ...

EPFL2022

Analysis-aware defeaturing of complex geometries

Ondine Gabrielle Chanon, Pablo Antolin Sanchez

Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non-negligible error ...

2022

A Functional Perspective on Information Measures

Amedeo Roberto Esposito

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

EPFL2022

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Jonathan Paul Sauder

Countless signal processing applications include the reconstruction of signals from few indirect linear measurements. The design of effective measurement operators is typically constrained by the underlying hardware and physics, posing a challenging and of ...

2022

Graph signal processing tailored for subgraph focus and community structure

Miljan Petrovic

Community structure in graph-modeled data appears in a range of disciplines that comprise network science. Its importance relies on the influence it bears on other properties of graphs such as resilience, or prediction of missing connections. Nevertheless, ...

EPFL2022

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression

Pascal Frossard, Thomas Maugey, Roberto Gerson De Albuquerque Azevedo

State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs). Although CNNs offer promising perspectives for 2D image compression, extending such models to omnidirectional images is not straightforward. First, omn ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Learning-based Image Coding: Early Solutions Reviewing and Subjective Quality Evaluation

Touradj Ebrahimi, Pinar Akyazi

Nowadays, image and video are the data types that consume most of the resources of modern communication channels, both in fixed and wireless networks. Thus, it is vital to compress visual data as much as possible, while maintaining some target quality leve ...

SPIE-INT SOC OPTICAL ENGINEERING2021

Characterization of Non-Stationary Signals in Electric Grids: a Functional Dictionary Approach

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

With the expanding role of converter-interfaced distributed energy resources, modern power grids are evolving towards low-inertia networks that are increasingly vulnerable to extreme dynamics. Consequently, advanced signal processing techniques are needed ...

IEEE Institute of Electrical and Electronics Engineers2021

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

Competitive Dehydrogenation and Backbone Fragmentation of Superhydrogenated PAHs: A Laboratory Study

Robert Richter, Eduardo Carrascosa Casado

Superhydrogenated polycyclic aromatic hydrocarbons (PAHs) have been suggested to catalyze the formation of H-2 in certain regions of space, but it remains unclear under which circumstances this mechanism is viable given the reduced carbon backbone stabilit ...

2021

High-Throughput Lossy-to-Lossless 3D Image Compression

Félix Schmidt, Gilles Fourestey

The rapid increase in medical and biomedical image acquisition rates has opened up new avenues for image analysis, but has also introduced formidable challenges. This is evident, for example, in selective plane illumination microscopy where acquisition rat ...

Institute of Electrical and Electronics Engineers2021

Characterization of Real-World Power System Signals in Non-Stationary Conditions using a Dictionary Approach

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

As power grids transition towards low-inertia net-works based on converter-interfaced renewable energy resources, they become increasingly vulnerable to extreme dynamics. Currently, the most advanced methods for signal processing in power systems are embed ...

IEEE2021

On the optimal sampling design for the Graph Total Variation decoder: recovering piecewise-constant graph signals from a few vertex measurements

Rodrigo Cerqueira Gonzalez Pena

Compressed Sensing teaches us that measurements can be traded for offline computation if the signal being sensed has a simple enough representation. Proper decoders can exactly recover the high-dimensional signal of interest from a lower-dimensional vector ...

EPFL2020

Fourier Sampling in Signal Processing and Numerical Linear Algebra

Amir Zandieh

This thesis focuses on developing efficient algorithmic tools for processing large datasets. In many modern data analysis tasks, the sheer volume of available datasets far outstrips our abilities to process them. This scenario commonly arises in tasks incl ...

EPFL2020