Fusion rapide d'images multispectrales et hyperspectrales en astronomie infrarouge.

Le James Webb Space Telescope (JWST) sera lancé en octobre 2021 et fournira des images multispectrales (à basse résolution spectrale) sur de larges champs de vue (avec une haute résolution spatiale) et des images hyperspectrales (à haute résolution spectrale) sur des petits champs de vue (avec une plus basse résolution spatiale). Les travaux de cette thèse ont pour but de développer des méthodes de fusion qui combinent ces images pour reconstruire la scène astrophysique observée à haute résolution spatiale et spectrale. Le produit fusionné permettra une amélioration de l'interprétation scientifique des données. Ces travaux s'inscrivent dans le programme d'observation prioritaire Early Release Science "Radiative Feedback of Massive Stars" qui sera mené lors de la première vague des missions scientifiques du JWST en septembre 2022. Le problème de fusion d'images de résolutions spatiales et spectrales différentes a été largement étudié dans un contexte d'observation de la Terre. Les méthodes les plus performantes sont basées sur la résolution de problèmes inverses, en minimisant un critère de fidélité aux données complété par un terme de régularisation. Le terme d'attache aux données est formulé d'après un modèle direct des instruments d'observation. Le terme de régularisation peut être interprété comme une information a priori sur l'image fusionnée. Les principaux enjeux de la fusion de données pour le JWST sont le très gros volume des données fusionnées, considérablement plus grand que la taille typique des images rencontrées en observation de la Terre, et la complexité des deux instruments d’observation. Dans cette thèse, nous proposons d'abord un cadre générique permettant de simuler des observations telles qu'elles seront fournies par deux instruments embarqués sur le JWST: l'imageur multispectral NIRCam et le spectromètre NIRSpec. Ce protocole repose principalement sur une image de référence à hautes résolutions spatiale et spectrale et sur la modélisation des instruments considérés. Dans ces travaux, l'image de référence est synthétiquement créée en exploitant une factorisation réaliste des caractéristiques spatiales et spectrales d'une région de photodissociation. Pour simuler les images multi- et hyperspectrales, nous établissons un modèle d’observation précis respectant les spécifications des instruments NIRCam et de NIRSpec. Ce modèle direct tient compte des particularités des instruments d'observation astrophysique, à savoir un flou spectralement variant pour chacun des instruments, et de leurs caractéristiques de bruit particulières. Ce cadre générique, inspiré par le célèbre protocole de Wald et al. (2005), rend possible la simulation de données réalistes qui seront utilisées pour évaluer les performances des algorithmes de fusion. Ensuite, nous exploitons le modèle direct précédemment établi pour formuler la tâche de fusion comme un problème inverse. En complément du terme d'attache aux données obtenu, un certain nombre de régularisations sont explorées. Tout d'abord, une régularisation spectrale est définie en suivant une hypothèse de rang faible sur l’image fusionnée. Ensuite, les régularisations spatiales suivantes sont eßxplorées : régularisation de type Sobolev, régularisation de type Sobolev à poids, représentation par patch et apprentissage de dictionnaires. Pour surmonter la complexité des modèles instrumentaux ainsi que la très grande taille des données, une implémentation rapide est proposée, en résolvant le problème dans le domaine spatial de Fourier et dans un sousespace spectral. Une importance particulière a été accordée à une prise en compte des incertitudes liées au problème : erreurs de pointage du télescope et de recalage des images

TSPO PET Imaging: From Microglial Activation to Peripheral Sterile Inflammatory Diseases?

Peripheral sterile inflammatory diseases (PSIDs) are a heterogeneous group of disorders that gathers several chronic insults involving the cardiovascular, respiratory, gastrointestinal, or musculoskeletal system and wherein inflammation is the cornerstone of the pathophysiology. In PSID, timely characterization and localization of inflammatory foci are crucial for an adequate care for patients. In brain diseases, in vivo positron emission tomography (PET) exploration of inflammation has matured over the last 20 years, through the development of radiopharmaceuticals targeting the translocator protein-18 kDa (TSPO) as molecular biomarkers of activated microglia. Recently, TSPO has been introduced as a possible molecular target for PSIDs PET imaging, making this protein a potential biomarker to address disease heterogeneity, to assist in patient stratification, and to contribute to predicting treatment response. In this review, we summarized the major research advances recently made in the field of TSPO PET imaging in PSIDs. Promising preliminary results have been reported in bowel, cardiovascular, and rheumatic inflammatory diseases, consolidated by preclinical studies. Limitations of TSPO PET imaging in PSIDs, regarding both its large expression in healthy peripheral tissues, unlike in central nervous system, and the production of peripheral radiolabeled metabolites, are also discussed, regarding their possible consequences on TSPO PET signal’s quantification

The structure of protostellar envelopes derived from submillimeter continuum images

High dynamic range imaging of submillimeter dust emission from the envelopes of eight young protostars in the Taurus and Perseus star-forming regions has been carried out using the SCUBA submillimeter camera on the James Clerk Maxwell Telescope. Good correspondence between the spectral classifications of the protostars and the spatial distributions of their dust emission is observed, in the sense that those with cooler spectral energy distributions also have a larger fraction of the submillimeter flux originating in an extended envelope compared with a disk. This results from the cool sources having more massive envelopes rather than warm sources having larger disks. Azimuthally-averaged radial profiles of the dust emission are used to derive the power-law index of the envelope density distributions, p (defined by rho proportional to r^-p), and most of the sources are found to have values of p consistent with those predicted by models of cloud collapse. However, the youngest protostars in our sample, L1527 and HH211-mm, deviate significantly from the theoretical predictions, exhibiting values of p somewhat lower than can be accounted for by existing models. For L1527 heating of the envelope by shocks where the outflow impinges on the surrounding medium may explain our result. For HH211-mm another explanation is needed, and one possibility is that a shallow density profile is being maintained in the outer envelope by magnetic fields and/or turbulence. If this is the case star formation must be determined by the rate at which the support is lost from the cloud, rather than the hydrodynamical properties of the envelope, such as the sound speed.Comment: Accepted for publication in the Astrophysical Journa

Sub-arcsecond imaging of SiO in the HH 211 protostellar jet

We present images of the HH 211 molecular jet in the SiO v=0, J=1-0 line at 43 GHz made with the Very Large Array at approximately 0.5 arcsec resolution. The SiO emission appears to trace primarily internal bowshocks in the outflow, suggesting that the dust and molecular gas are accelerated via prompt entrainment at internal working surfaces in the jet. There is also some evidence for limb-brightening of the SiO emission, indicating that SiO emission may also arise from entrainment in the jet's boundary layer. Excitation temperatures of >~150-200 K are inferred from the SiO emission. Enhancements in the SiO abundance of ~10^6 over interstellar values are observed, and the possible origin of the SiO is discussed.Comment: 14 pages, 4 figures. Needs aastex, epsfig, times.sty. To appear in the Astrophysical Journal, July 200

Welfare issues and potential solutions for laying hens in free range and organic production systems: A review based on literature and interviews

In free-range and organic production systems, hens can make choices according to their needs and desires, which is in accordance with welfare definitions. Nonetheless, health and behavioral problems are also encountered in these systems. The aim of this article was to identify welfare challenges observed in these production systems in the EU and the most promising solutions to overcome these challenges. It is based on a review of published literature and research projects complemented by interviews with experts. We selected EU specific information for welfare problems, however, the selected literature regarding solutions is global. Free range use may increase the risk of infection by some bacteria, viruses and parasites. Preventive methods include avoiding contamination thanks to biosecurity measures and strengthening animals' natural defenses against these diseases which can be based on nutritional means with new diet components such as insect-derived products, probiotics and prebiotics. Phytotherapy and aromatherapy can be used as preventive and curative medicine and vaccines as alternatives to antibiotics and pesticides. Bone quality in pullets and hens prevents keel deviations and is favored by exercise in the outdoor range. Free range use also lead to higher exposure to variable weather conditions and predators, therefore shadow, fences and guard animals can be used to prevent heat stress and predation respectively. Granting a free range provides opportunities for the expression of many behaviors and yet many hens usually stay close to the house. Providing the birds with trees, shelters or attractive plants can increase range use. Small flock sizes, early experiences of enrichment and personality traits have also been found to enhance range use. Severe feather pecking can occur in free range production systems, although flocks using the outdoor area have better plumage than indoors. While many prevention strategies are facilitated in free range systems, the influence of genetics, prenatal and nutritional factors in free range hens still need to be investigated. This review provides information about practices that have been tested or still need to be explored and this information can be used by stakeholders and researchers to help them evaluate the applicability of these solutions for welfare improvement

PDRs4All: A JWST Early Release Science Program on Radiative Feedback from Massive Stars

22 pags., 8 figs., 1 tab.Massive stars disrupt their natal molecular cloud material through radiative and mechanical feedback processes. These processes have profound effects on the evolution of interstellar matter in our Galaxy and throughout the universe, from the era of vigorous star formation at redshifts of 1-3 to the present day. The dominant feedback processes can be probed by observations of the Photo-Dissociation Regions (PDRs) where the far-ultraviolet photons of massive stars create warm regions of gas and dust in the neutral atomic and molecular gas. PDR emission provides a unique tool to study in detail the physical and chemical processes that are relevant for most of the mass in inter-and circumstellar media including diffuse clouds, proto-planetary disks, and molecular cloud surfaces, globules, planetary nebulae, and star-forming regions. PDR emission dominates the infrared (IR) spectra of star-forming galaxies. Most of the Galactic and extragalactic observations obtained with the James Webb Space Telescope (JWST) will therefore arise in PDR emission. In this paper we present an Early Release Science program using the MIRI, NIRSpec, and NIRCam instruments dedicated to the observations of an emblematic and nearby PDR: the Orion Bar. These early JWST observations will provide template data sets designed to identify key PDR characteristics in JWST observations. These data will serve to benchmark PDR models and extend them into the JWST era. We also present the Science-Enabling products that we will provide to the community. These template data sets and Science-Enabling products will guide the preparation of future proposals on star-forming regions in our Galaxy and beyond and will facilitate data analysis and interpretation of forthcoming JWST observations.Support for JWST-ERS program ID 1288 was provided through grants from the STScI under NASA contract NAS5-03127 to STScI (K.G., D.V.D.P., M.R.), Univ. of Maryland (M.W., M.P.), Univ. of Michigan (E.B., F.A.), and Univ. of Toledo (T.S.-Y.L.). O.B. and E.H. are supported by the Programme National “Physique et Chimie du Milieu Interstellaire” (PCMI) of CNRS/INSU with INC/INP co-funded by CEA and CNES, and through APR grants 6315 and 6410 provided by CNES. E. P. and J.C. acknowledge support from the National Science and Engineering Council of Canada (NSERC) Discovery Grant program (RGPIN-2020-06434 and RGPIN-2021-04197 respectively). E.P. acknowledges support from a Western Strategic Support Accelerator Grant (ROLA ID 0000050636). J.R.G. and S.C. thank the Spanish MCINN for funding support under grant PID2019-106110GB-I00. Work by M.R. and Y.O. is carried out within the Collaborative Research Centre 956, subproject C1, funded by the Deutsche Forschungsgemeinschaft (DFG)—project ID 184018867. T.O. acknowledges support from JSPS Bilateral Program, grant No. 120219939. M.P. and M.W. acknowledge support from NASA Astrophysics Data Analysis Program award #80NSSC19K0573. C.B. is grateful for an appointment at NASA Ames Research Center through the San José State University Research Foundation (NNX17AJ88A) and acknowledges support from the Internal Scientist Funding Model (ISFM) Directed Work Package at NASA Ames titled: “Laboratory Astrophysics—The NASA Ames PAH IR Spectroscopic Database.”Peer reviewe

Fast fusion of multispectral and hyperspectral images for infrared astronomy

Le James Webb Space Telescope (JWST) sera lancé en octobre 2021 et fournira des images multispectrales (à basse résolution spectrale) sur de larges champs de vue (avec une haute résolution spatiale) et des images hyperspectrales (à haute résolution spectrale) sur des petits champs de vue (avec une plus basse résolution spatiale). Les travaux de cette thèse ont pour but de développer des méthodes de fusion qui combinent ces images pour reconstruire la scène astrophysique observée à haute résolution spatiale et spectrale. Le produit fusionné permettra une amélioration de l'interprétation scientifique des données. Ces travaux s'inscrivent dans le programme d'observation prioritaire Early Release Science "Radiative Feedback of Massive Stars" qui sera mené lors de la première vague des missions scientifiques du JWST en septembre 2022. Le problème de fusion d'images de résolutions spatiales et spectrales différentes a été largement étudié dans un contexte d'observation de la Terre. Les méthodes les plus performantes sont basées sur la résolution de problèmes inverses, en minimisant un critère de fidélité aux données complété par un terme de régularisation. Le terme d'attache aux données est formulé d'après un modèle direct des instruments d'observation. Le terme de régularisation peut être interprété comme une information a priori sur l'image fusionnée. Les principaux enjeux de la fusion de données pour le JWST sont le très gros volume des données fusionnées, considérablement plus grand que la taille typique des images rencontrées en observation de la Terre, et la complexité des deux instruments d’observation. Dans cette thèse, nous proposons d'abord un cadre générique permettant de simuler des observations telles qu'elles seront fournies par deux instruments embarqués sur le JWST: l'imageur multispectral NIRCam et le spectromètre NIRSpec. Ce protocole repose principalement sur une image de référence à hautes résolutions spatiale et spectrale et sur la modélisation des instruments considérés. Dans ces travaux, l'image de référence est synthétiquement créée en exploitant une factorisation réaliste des caractéristiques spatiales et spectrales d'une région de photodissociation. Pour simuler les images multi- et hyperspectrales, nous établissons un modèle d’observation précis respectant les spécifications des instruments NIRCam et de NIRSpec. Ce modèle direct tient compte des particularités des instruments d'observation astrophysique, à savoir un flou spectralement variant pour chacun des instruments, et de leurs caractéristiques de bruit particulières. Ce cadre générique, inspiré par le célèbre protocole de Wald et al. (2005), rend possible la simulation de données réalistes qui seront utilisées pour évaluer les performances des algorithmes de fusion. Ensuite, nous exploitons le modèle direct précédemment établi pour formuler la tâche de fusion comme un problème inverse. En complément du terme d'attache aux données obtenu, un certain nombre de régularisations sont explorées. Tout d'abord, une régularisation spectrale est définie en suivant une hypothèse de rang faible sur l’image fusionnée. Ensuite, les régularisations spatiales suivantes sont eßxplorées : régularisation de type Sobolev, régularisation de type Sobolev à poids, représentation par patch et apprentissage de dictionnaires. Pour surmonter la complexité des modèles instrumentaux ainsi que la très grande taille des données, une implémentation rapide est proposée, en résolvant le problème dans le domaine spatial de Fourier et dans un sousespace spectral. Une importance particulière a été accordée à une prise en compte des incertitudes liées au problème : erreurs de pointage du télescope et de recalage des images.The James Webb Space Telescope (JWST) will be launched in 2021 and will provide multispectral images (with low spectral resolution) on wide fields of view (with high spatial resolution) and hyperspectral images (with high spectral resolution) on small fields of view (with lower spatial resolution). This Ph.D. thesis aims at developing fusion methods that will combine those images to reconstruct the astrophysical scene at high spatial and spectral resolutions. The fused product will make data analysis significantly easier. This Ph.D. project is part of the Early Release Science observing program "Radiative Feedback of Massive Stars" which will be conducted in the first wave of the JWST scientific mission in September 2022. Fusing images of different spatial and spectral resolutions has been deeply investigated for remote sensing in Earth observation. The most powerful methods are based on the resolution of an inverse problem, i.e., by minimizing a cost function composed of a data fidelity term complemented by a regularization term. The data fidelity term is formulated from a forward model of the observation instruments. The regularization term can be interpreted as a prior information on the fused image. The main challenges of data fusion for the JWST are due to the very large scale of the fused data, considerably larger than the size encountered in remote sensing, as well as complexity of both instruments. In a first part of this thesis, one proposes a generic framework which allows observations to be simulated as they would have been provided by two instruments on board the JWST: the NIRCam multispectral imager and the NIRSpec spectrometer. This protocol is mainly based on a reference image with high spatial and spectral resolutions and on the modeling of the instruments considered. In this work, the reference image is synthetically created by exploiting a realistic factorization of the spatial and spectral characteristics of a photodissociation region. To simulate multi- and hyperspectral images, one derives an accurate observation model that satisfies the specifications of the NIRCam and NIRSpec instruments. This direct model takes into account the specificities of astrophysical observation instruments, namely a spectrally varying blur for each of the instruments, and their particular noise characteristics. This generic framework, inspired by the famous protocol of Wald \emph{et al.} (2005), allows realistic data sets to be simulated, that will be subsequently used to evaluate the performance of the fusion algorithms. Then, one exploits the direct model previously established to formulate the fusion task as an inverse problem. In addition to the data fitting term, various regularizations are explored. First, a spectral regularization is defined by following a low rank hypothesis on the fused image. Then, the following spatial regularizations are envisioned: Sobolev, weighted Sobolev, patch-based representations and dictionary learning. To overcome the complexity of the instrumental models as well as the very large data volume, a fast implementation is proposed, by solving the problem in the Fourier spatial domain and in a spectral subspace. Particular importance is given to taking into account the uncertainties associated with the problem: errors in telescope jitter and in image misregistration

Hyperspectral and Multispectral Image Fusion Under Spectrally Varying Spatial Blurs – Application to High Dimensional Infrared Astronomical Imaging

International audienceHyperspectral imaging has become a significant source of valuable data for astronomers over the past decades. Current instrumental and observing time constraints allow direct acquisition of multispectral images, with high spatial but low spectral resolution, and hyperspectral images, with low spatial but high spectral resolution. To enhance scientific interpretation of the data, we propose a data fusion method which combines the benefits of each image to recover a high spatio-spectral resolution datacube. The proposed inverse problem accounts for the specificities of astronomical instruments, such as spectrally variant blurs. We provide a fast implementation by solving the problem in the frequency domain and in a low-dimensional subspace to efficiently handle the convolution operators as well as the high dimensionality of the data. We conduct experiments on a realistic synthetic dataset of simulated observation of the upcoming James Webb Space Telescope, and we show that our fusion algorithm outperforms state-of-the-art methods commonly used in remote sensing for Earth observation

Informed spatial regularizations for fast fusion of astronomical images

International audienceThis paper introduces two informed spatial regularizations dedicated to multiband image fusion. The fusion process combines a multispectral image with high spatial resolution and a hyperspectral image with high spectral resolution, with the aim of recovering a full resolution data-cube. In this work, we propose two spatial regularizations that exploit the spatial information of the multispectral image. A weighted Sobolev regularization identifies the sharp structures locations to locally mitigate a smoothness-promoting Sobolev regularization. A dictionary-based regularization takes advantage of spatial redundancy to recover spatial textures using a dictionary learned on the multispectral image. The proposed regularizations are evaluated on realistic simulations of James Webb Space Telescope (JWST) observations of the Orion Bar and show a better reconstruction of sharp structures compared to a non-informed regularization. Since JWST is now in orbit, we expect to use this method on real data in the near future

Fusion of hyperspectral and multispectral infrared astronomical images (SPARS 2019)

National audienceIn this contribution, we introduce a multispectral and hyper-spectral image fusion method in an astrophysical observation context. Wedefine an observation forward model and solve a approximate regularizedinverse problem in the Fourier domain by a conjugate gradient algorithm.The fusion model is evaluated on simulated observations of the OrionBar by the NIRCam imager and the NIRSpec spectrometer, embeddedon the James Webb Space Telescope