Publications de Eric Bezzam | EPFL Graph Search

Towards Robust and Generalizable Lensless Imaging With Modular Learned Reconstruction

Lensless cameras disregard the conventional design that imaging should mimic the human eye. This is done by replacing the lens with a thin mask, and moving image formation to the digital post-processing. State-of-the-art lensless imaging techniques use lea ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

Let There Be Light: Robust Lensless Imaging Under External Illumination With Deep Learning

Martin Vetterli, Eric Bezzam

Lensless cameras relax the design constraints of traditional cameras by shifting image formation from analog optics to digital post-processing. While new camera designs and applications can be enabled, lensless imaging is very sensitive to unwanted interfe ...

IEEE2025

Generalizing Learning-Based Lensless Image Reconstruction to Mask Pattern Changes

Martin Vetterli, Eric Bezzam

Previous work has not shown if learned components for lensless image reconstruction can generalize to physical modifications. In this work, we train a reconstruction approach on an open-sourced, multi-mask dataset, and demonstrate improved generalizability ...

Optical Society of America2024

A Modular and Robust Physics-Based Approach for Lensless Image Reconstruction

Martin Vetterli, Eric Bezzam, Yohann Loïc Yann Perron

In this paper, we present a modular approach for reconstructing lensless measurements. It consists of three components: a newly-proposed pre-processor, a physics-based camera inverter to undo the multiplexing of lensless imaging, and a post-processor. The ...

IEEE2024

Hardware-in-the-loop training for lensless imaging with a programmable mask

Martin Vetterli, Eric Bezzam

Lensless imaging can drastically relax traditional camera constraints by replacing lenses with optical masks, enabling lighter, cheaper, and thinner systems. However, unlike lenses, there is a lack of clear criteria for optical mask design. Most approaches ...

SPIE2024

DigiCam: Single-Shot Lensless Sensing with a Low-Cost Programmable Mask

Martin Vetterli, Eric Bezzam, Matthieu Martin Jean-André Simeoni

We propose an LCD-based lensless camera for compressive and programmable sensing. The system is low-cost (less than 100 USD) and reproducible. We model the proposed system, and demonstrate experimental results for imaging and classification. ...

Optical Society of America2023

LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry Pi

Martin Vetterli, Eric Bezzam, Sepand Kashani, Matthieu Martin Jean-André Simeoni

This toolkit has everything you need to perform imaging with a lensless camera. We make use of a low-cost implementation of DiffuserCam, namely replacing the lens with a piece of tape and using the Raspberry Pi HQ camera sensor. Similar principles and meth ...

Zenodo2023

pyFFS: A Python Library for Fast Fourier Series Computation and Interpolation with GPU Acceleration

Martin Vetterli, Paul Hurley, Eric Bezzam, Sepand Kashani, Matthieu Martin Jean-André Simeoni

Fourier transforms are an often necessary component in many computational tasks, and can be computed efficiently through the fast Fourier transform (FFT) algorithm. However, many applications involve an underlying continuous signal, and a more natural choi ...

SIAM2022

A Study on More Realistic Room Simulation for Far-Field Keyword Spotting

Eric Bezzam, Robin Scheibler

We investigate the impact of more realistic room simulation for training far-field keyword spotting systems without fine-tuning on in-domain data. To this end, we study the impact of incorporating the following factors in the room impulse response (RIR) ge ...

IEEE2020

Teaching Practical DSP with Off-the-Shelf Hardware and Free Software

Paolo Prandoni, Eric Bezzam, Adrien Guillaume Olivier Hoffet

In this paper we describe our approach to teaching applied digital signal processing (DSP) using freely-available software and inexpensive off-the-shelf hardware components. The pedagogical framework is built around simple real-time audio processing algori ...

IEEE2019