PeX 1. Multi-spectral expansion of residual speckles for planet detection

The detection of exoplanets in coronographic images is severely limited by residual starlight speckles. Dedicated post-processing can drastically reduce this "stellar leakage" and thereby increase the faintness of detectable exoplanets. Based on a multi-spectral series expansion of the diffraction pattern, we derive a multi-mode model of the residuals which can be exploited to estimate and thus remove the residual speckles in multi-spectral coronographic images. Compared to other multi-spectral processing methods, our model is physically grounded and is suitable for use in an (optimal) inverse approach. We demonstrate the ability of our model to correctly estimate the speckles in simulated data and demonstrate that very high contrasts can be achieved. We further apply our method to removing speckles from a real data cube obtained with the SPHERE IFS instrument.Comment: accepted for publication in MNRAS on 25th of August 2017, 17 pages, 15 figure

Image Reconstruction in Optical Interferometry

This tutorial paper describes the problem of image reconstruction from interferometric data with a particular focus on the specific problems encountered at optical (visible/IR) wavelengths. The challenging issues in image reconstruction from interferometric data are introduced in the general framework of inverse problem approach. This framework is then used to describe existing image reconstruction algorithms in radio interferometry and the new methods specifically developed for optical interferometry.Comment: accepted for publication in IEEE Signal Processing Magazin

Image Reconstruction in Optical Interferometry

International audienceInverse problem approach is a suitable framework to analyze the challenging issues in image reconstruction from interferometric data. It can be exploited to describe and formally compare the new methods specifically developed for optical interferometry

Joint deconvolution and demosaicing

International audienceWe present a new method to jointly perform deblurring and color- demosaicing of RGB images. Our method is derived following an inverse problem approach in a MAP framework. To avoid noise am- plification and allow for interpolation of missing data, we make use of edge-preserving spatial regularization and spectral regularization. We demonstrate the improvements brought by our algorithm by processing both simulated and real RGB images obtained with a Bayer's color filter and with different types of blurring

Multi-wavelength imaging algorithm for optical interferometry

International audienceOptical interferometers provide multiple wavelength measurements. In order to fully exploit the spectral and spatial resolution of these instruments, new algorithms for image reconstruction have to be developed. Early attempts to deal with multi-chromatic interferometric data have consisted in recovering a gray image of the object or independent monochromatic images in some spectral bandwidths. The main challenge is now to recover the full 3-D (spatio-spectral) brightness distribution of the astronomical target given all the available data. We describe a new approach to implement multi-wavelength image reconstruction in the case where the observed scene is a collection of point-like sources. We show the gain in image quality (both spatially and spectrally) achieved by globally taking into account all the data instead of dealing with independent spectral slices. This is achieved thanks to a regularization which favors spatially sparsity and spectral grouping of the sources. Since the objective function is not differentiable, we had to develop a specialized optimization algorithm which also takes into account the non-negativity of the brightness distribution

Détection de sources en interférométrie optique hyperspectrale}

National audienceEn faisant interférer la lumière provenant de plusieurs télescopes, l'interférométrie optique fournit des mesures à très haute résolution angulaire (de l'ordre de la milliseconde d'arc). Chaque mesure estime la valeur en une fréquence spatiale de la transformée de Fourier de la distribution spatiale d'intensité émise par l'objet observé dans chacun des canaux spectraux. Le problème traité ici est la détection, la localisation précise et l'extraction sans biais du spectre de chacune des étoiles d'un amas observé en interférométrie. C'est un verrou important pour l'étude des étoiles au voisinage du trou noir central de notre galaxie, but scientifique du futur instrument GRAVITY du VLTI. A la suite de nos précédent travaux, nous présentons ici une méthode de reconstruction basée sur la méthode de multiplicateur à directions alternées (ADMM). Cela permet d'utiliser dans le même temps les données interférométriques et photométriques. L'introduction de variables auxiliaires permet de découper le problème de reconstruction en sous problèmes plus faciles à traiter. Des tests sur des simulations montrent que la méthode proposée permet de détecter toutes les étoiles d'un amas et de d'estimer leurs spectres avec un biais négligeable

Restoration of hyperspectral astronomical data with spectrally varying blur

International audienceIn this paper we present a method for hyper-spectral image restoration for integral field spectrographs (IFS) data. We specifically address two topics: (i) the design of a fast approximation of spectrally varying operators and (ii) the comparison between two kind of regularization functions: quadratic and spatial sparsity functions. We illustrate this method with simulations coming from the Multi Unit Spectroscopic Explorer (MUSE) instrument. It shows the clear increase of the spatial resolution provided by our method as well as its denoising capability

Fast automatic myopic deconvolution of angiogram sequence

International audienceWe present a fast unsupervised myopic deconvolution method dedicated to quasi-real time processing of video sequences such as angiograms. Our method is based on a Bayesian approach of which the tuning parameters are automatically set thanks to the marginalized likelihood of the observed image. We demonstrate the effectiveness of our approach on simulated and empirical images

Fast model of space-variant blurring and its application to deconvolution in astronomy

International audienceImage deblurring is essential to high resolution imaging and is therefore widely used in astronomy, microscopy or com- putational photography. While shift-invariant blur is modeled by convolution and leads to fast FFT-based algorithms, shift- variant blurring requires models both accurate and fast. When the point spread function (PSF) varies smoothly across the field, these two opposite objectives can be reached by inter- polating from a grid of PSF samples. Several models for smoothly varying PSF co-exist in the literature. We advocate that one of them is both physically- grounded and fast. Moreover, we show that the approximation can be largely improved by tuning the PSF samples and inter- polation weights with respect to a given continuous model. This improvement comes without increasing the computa- tional cost of the blurring operator. We illustrate the developed blurring model on a deconvo- lution application in astronomy. Regularized reconstruction with our model leads to large improvements over existing re- sults

Un modèle rapide de flou variable dans le champ de flou variable dans le champ et son application a la déconvolution en astronomie

National audienceLa déconvolution d'images est essentielle pour l'imagerie haute résolution et est par conséquent largement utilisée en astronomie et en microscopie. Alors qu'un flou invariant dans le champ est modélisé par une convolution conduisant à des algorithmes rapides à base de FFT, les flous variant dans le champ nécessitent des modèles à la fois précis et suffisamment rapides. Lorsque la réponse impulsionnelle (RI) varie continument dans le champ, un compromis entre ces deux objectifs contradictoires peut être atteint en interpolant une grille de RI. Plusieurs modèles pour les RI variant continûment dans le champ co-existent dans la littérature. Nous montrons que l'un d'entre eux est à la fois bien fondé physiquement et rapide. De plus, nous montrons que la qualité d'approximation peut être améliorée en ajustant les RI et les poids d'interpolation par rapport à un modèle continu choisi. Cette amélioration ne modifie pas la complexité de l'application de l'opérateur de flou. Nous illustrons le modèle développé sur une application de déconvolution en astronomie et montrons qu'une reconstruction régularisée avec le modèle proposé améliore largement les résultats existants