Olivier Flasseur

Postdoc in signal & image processing

Observatory of Lyon


I am a postdoc at the Astrophysics Research Center of Lyon (Observatory of Lyon). I am working on the development of signal and image processing methods to detect and reconstruct objects from faint signals in images. The main application of my current research work is high-contrast imaging for direct detection of circumstellar disks.

Previously, I was a PhD student at the Hubert Curien Laboratory of Saint-Etienne under the supervision of Corinne Fournier and Loïc Denis. I worked on the development of algorithms dedicated to the detection of exoplanets by direct imaging, in astronomy, and of particles by digital holography, in microscopy. Emphasis was put on the development of common methodological tools, particularly in terms of statistical modeling of the background noise, robustness of the proposed methods, and the exploitation of temporo-spectral information redundancy.


  • Detection & estimation
  • Inverse problems
  • Image reconstruction
  • Faint signals
  • Time & spectral series
  • Direct imaging (astronomy)
  • Holography (microscopy)


  • PhD in Image & Vision, 2019

    University of Lyon, University of Saint-Etienne

  • Engineer degree in Signal, Image, Communication, Multimedia, 2015

    Phelma, Grenoble INP



Postdoc in signal & image processing

Astrophysical Research Center of Lyon

Feb 2020 – Present Saint-Genis-Laval, France
Reconstruction of extended objects in the low signal-to-noise ratio regime.

PhD student in signal & image processing

Hubert Curien Laboratory

Oct 2016 – Nov 2019 Saint-Etienne, France
Object detection and characterization from faint signals in images: applications in astronomy and microscopy.

Teaching assistant in engineering school

Télécom Saint-Etienne

Oct 2016 – Nov 2019 Saint-Etienne, France
Tutorials in signal & image processing to students at Bachelor and Master level.



REXPACO: An algorithm for high contrast reconstruction of the circumstellar environment by angular differential imaging

Context. Direct imaging is a method of choice for probing the close environment of young stars. Even with the coupling of adaptive …

The SPHERE infrared survey for exoplanets (SHINE). II. Observations, data reduction and analysis, detection performances and early-results

Context. Over the past decades, direct imaging has confirmed the existence of substellar companions (exoplanets or brown dwarfs) on …

Unveiling the β Pictoris system, coupling high contrast imaging, interferometric, and radial velocity data

Context. The nearby and young β Pictoris system hosts a well resolved disk, a directly imaged massive giant planet orbiting at ≃9 au, …

PACO ASDI: an algorithm for exoplanet detection and characterization in direct imaging with integral field spectrographs

Context. Exoplanet detection and characterization by direct imaging both rely on sophisticated instruments (adaptive optics and …

Robustness to bad frames in angular differential imaging: a local weighting approach

Context. The detection of exoplanets by direct imaging is very challenging. It requires an extreme adaptive-optics (AO) system and a …

VLT/SPHERE exploration of the young multiplanetary system PDS70

Context. PDS 70 is a young (5.4 Myr), nearby (~113 pc) star hosting a known transition disk with a large gap. Recent observations with …

Determining mass limits around HD 163296 through SPHERE direct imaging data

HD 163296 is a Herbig Ae/Be star known to host a protoplanetary disk with a ringed structure. To explain the disk features, previous …

Reconstruction of in-line holograms: combining model-based and regularized inversion

In-line digital holography is a simple yet powerful tool to image absorbing and/or phase objects. Nevertheless, the loss of the phase …

Exoplanet detection in angular differential imaging by statistical learning of the nonstationary patch covariances – The PACO algorithm

Context. The detection of exoplanets by direct imaging is an active research topic in astronomy. Even with the coupling of an extreme …

Self-calibration for lensless color microscopy

Lensless color microscopy (also called in-line digital color holography) is a recent quantitative 3D imaging method used in several …


International conferences

Finding meaningful detections: false discovery rate control in correlated detection maps

The detection of faint sources is a key step in several areas of signal and image processing. The reliability of the detection depends …

Exoplanet imaging data challenge: benchmarking the various image processing methods for exoplanet detection

The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image …

Accounting for the nonstationary correlated noise in digital holography

In in-line digital holography, the background of the recorded images is sometimes much higher than the signal of interest. It can …

ExPACO: detection of an extended pattern under nonstationary correlated noise by patch covariance modeling

In several areas of imaging, it is necessary to detect the weak signal of a known pattern superimposed over a background. Because of …

Numerical reconstruction of holograms using inverse problems approaches

Several reconstruction approaches based on inverse problems (also called compressive sensing, Bayesian approaches, model fitting) have …

Reconstruction of in-line holograms combining model fitting and image-based regularized inversion

We propose to reconstruct in-line holograms using a joint forward model on samples composed of a simple subpart estimated by model …

An unsupervised patch-based approach for exoplanet detection by direct imaging

The search for exoplanet is a very active topic in astronomy. Exoplanet detection by direct imaging requires both dedicated instruments …

Exoplanet detection in angular and spectral differential imaging: local learning of background correlations for improved detection

The search for new exoplanets by direct imaging is a very active research topic in astronomy. The detection is particularly challenging …

Improving color lensless microscopy reconstructions by self-calibration

Lensless color microscopy is a recent 3D quantitative imaging method allowing to retrieve physical parameters characterizing …

Optimizing phase object reconstruction using an in-line digital holographic microscope and a reconstruction based on a Lorenz Mie model

Among the various configurations that may be used in digital holography, the original in-line “Gabor” configuration is the simplest …

Robust object characterization from lensless microscopy videos

Lensless microscopy, also known as in-line digital holography, is a 3D quantitative imaging method used in various fields including …


National conferences

Détection d’exoplanètes par une modélisation statistique locale de la covariance spatio-temporelle du fond

La détection d’exoplanètes par imagerie directe est une tâche ardue : le faible signal des objets d’intérêt est noyé dans un fond …

Détection d’exoplanètes basée sur une modélisation statistique locale des patchs

La détection d’exo-planètes par imagerie directe est un problème difficile car les observations sont dominées par les fuites …


Workshops, Seminars, etc.


Object detection and characterization from faint signals in images: applications in astronomy and microscopy

Detecting and characterizing objects in images in the low signal-to-noise ratio regime is a critical issue in many areas such as astronomy or microscopy. In astronomy, the detection of exoplanets and their characterization by direct imaging from the Earth is a hot topic. A target star and its close environment (hosting potential exoplanets) are observed on short exposures. In microscopy, in-line holography is a cost-effective method for characterizing microscopic objects. Based on the recording of a hologram, it allows a digital focusing in any plane of the imaged 3-D volume. In these two fields, the object detection problem is made difficult by the low contrast between the objects and the nonstationary background of the recorded images.
In this thesis, we propose an unsupervised exoplanet detection and characterization algorithm based on the statistical modeling of background fluctuations. The method, based on a modeling of the statistical distribution of patches, captures their spatial covariances. It reaches a performance superior to state-of-the-art techniques on several datasets of the European high-contrast imager SPHERE operating at the Very Large Telescope. It produces statistically grounded and spatially-stationary detection maps in which detections can be performed at a constant probability of false alarm. It also produces photometrically unbiased spectral energy distributions of the detected sources. The use of a statistical model of the data leads to reliable photometric and astrometric accuracies. This methodological framework can be adapted to the detection of spatially-extended patterns in strong structured background, such as the diffraction patterns in holographic microscopy. We also propose robust approaches based on weighting strategies to reduce the influence of the numerous outliers present in real data. We show on holographic videos that the proposed weighting approach achieves a bias/variance tradeoff. In astronomy, the robustness improves the performance of our detection method in particular at close separations where the stellar residuals dominate. Our algorithms are adapted to benefit from the possible spectral diversity of the data, which improves the detection and characterization performance. All the algorithms developed are unsupervised: weighting and/or regularization parameters are estimated in a data-driven fashion. Beyond the applications in astronomy and microscopy, the signal processing methodologies introduced are general and could be applied to other detection and estimation problems.