Optimisation jointe de la chaîne codage/débruitage pour les images satellite

National audienceIn this paper, we propose to study the problem of optimal noisy source coding/denoising. This problem can be formulated as an optimization problem where the criterion to minimize is the global distortion, that is the error between the noise-free image and the denoised image. This problem is challenging since a global optimization is usually difficult to perform as the global fidelity criterion needs to be optimized in the same time over the sets of both coding and denoising parameters. We show here how to express the global distortion in closed-form and we present an algorithm to minimize this distortion with respect to these parameters. We show results of this joint optimization algorithm on classical test images and on a high dynamic range image, visually and in a rate-distortion sense.Dans ce travail, nous proposons d'étudier le problème du codage/débruitage optimal d'une source bruitée. Ce problème peut se formaliser comme un problème d'optimisation où le critère à minimiser est la distorsion globale, c'est-à-dire l'erreur entre l'image d'origine non bruitée et l'image décodée débruitée. Ce problème est complexe à traiter car une optimisation globale est habituellement difficile à effectuer puisque le critère global doit être optimisé en même temps par rapport aux paramètres de codage et de débruitage. Nous montrons ici comment écrire analytiquement les différents termes de la distorsion globale et nous présentons un algorithme pour minimiser cette distorsion par rapport à ces paramètres. Nous montrons des résultats de cet algorithme d'optimisation jointe sur des images classiques et sur une image satellite haute dynamique, visuellement et d'un point de vue débit-distorsion

Thermalizing a telescope in Antarctica: Analysis of ASTEP observations

The installation and operation of a telescope in Antarctica represent particular challenges, in particular the requirement to operate at extremely cold temperatures, to cope with rapid temperature fluctuations and to prevent frosting. Heating of electronic subsystems is a necessity, but solutions must be found to avoid the turbulence induced by temperature fluctua- tions on the optical paths. ASTEP 400 is a 40 cm Newton telescope installed at the Concordia station, Dome C since 2010 for photometric observations of fields of stars and their exoplanets. While the telescope is designed to spread star light on several pixels to maximize photometric stability, we show that it is nonetheless sensitive to the extreme variations of the seeing at the ground level (between about 0.1 and 5 arcsec) and to temperature fluctuations between --30 degrees C and --80 degrees C. We analyze both day-time and night-time observations and obtain the magnitude of the seeing caused by the mirrors, dome and camera. The most important effect arises from the heating of the primary mirror which gives rise to a mirror seeing of 0.23 arcsec K--1 . We propose solutions to mitigate these effects.Comment: Appears in Astronomical Notes / Astronomische Nachrichten, Wiley-VCH Verlag, 2015, pp.1-2

́Evaluer la qualité d’une fragmentation de graphe multi-niveaux

International audienc

Joint coding-denoising optimization of noisy images

In this paper, we propose to study the problem of noisy source coding/denoising. The challenge of this problem is that a global optimization is usually difficult to perform as the global fidelity criterion needs to be optimized in the same time over the sets of both coding and denoising parameters. Most of the bibliography in this domain is based on the fact that, for a specific criterion, the global optimization problem can be simply separated into two independent optimization problems: The noisy image should be first optimally denoised and this denoised image should then be optimally coded. In many applications however, the layout of the acquisition imaging chain is fixed and cannot be changed, that is a denoising step cannot be inserted before coding. For this reason, we are concerned here with the problem of global joint optimization in the case the denoising step is performed, as usual, after coding/decoding. In this configuration, we show how to express the global distortion as a function of the coding and denoising parameters. We present then an algorithm to minimize this distortion and to get the optimal values of these parameters. We show results of this joint optimization algorithm on classical test images and on a high dynamic range image, visually and in a rate-distortion sense

Joint coding-denoising optimization of noisy images

In this paper, we propose to study the problem of noisy source coding/denoising. The challenge of this problem is that a global optimization is usually difficult to perform as the global fidelity criterion needs to be optimized in the same time over the sets of both coding and denoising parameters. Most of the bibliography in this domain is based on the fact that, for a specific criterion, the global optimization problem can be simply separated into two independent optimization problems: The noisy image should be first optimally denoised and this denoised image should then be optimally coded. In many applications however, the layout of the acquisition imaging chain is fixed and cannot be changed, that is a denoising step cannot be inserted before coding. For this reason, we are concerned here with the problem of global joint optimization in the case the denoising step is performed, as usual, after coding/decoding. In this configuration, we show how to express the global distortion as a function of the coding and denoising parameters. We present then an algorithm to minimize this distortion and to get the optimal values of these parameters. We show results of this joint optimization algorithm on classical test images and on a high dynamic range image, visually and in a rate-distortion sense

A satellite imaging chain based on the Compressed Sensing technique

International audienceSatellite imaging has been the focus of intense works in remote sensing for the last years. The ability of satellite optical systems to produce high-resolution images has indeed been of a great interest in applications such as change detection or image classification. The design of a satellite acquisition chain is however quite challenging as it involves expensive processes such as sampling and coding. In this work, we investigate the performances of a low-resource satellite imaging chain based on the Compressed Sensing (CS) acquisition technique. We propose a reconstruction algorithm which takes into account the degradations of the satellite imaging chain and we present results on a real satellite data

On the optimization of the satellite imaging chain

In this paper, we focus on the global optimization of the satellite imaging chain. The theoretical analysis of the satellite imaging chain optimization is a difficult problem that needs lot of approximations. In order to consider the complex real satellite imaging chain, we propose to address this problem numerically and we present, based on numerical experiments, techniques to optimize the quality of the reconstructed final image. We first focus on the common question of the position of the restoration step in the imaging chain, that is on-board before coding or on-ground after coding. Then, we present several methods to remove the coding artifacts inherent in wavelet based coder schemes. From these numerical results we propose a new satellite imaging chain and we show visual and rate-distortion results on a real satellite image

Global rate-distortion optimization of satellite imaging chains

International audienceThe joint compression/restoration optimization of a satellite imaging chain is a challenging problem which has been little investigated so far. Some works have been done in designing an optimal coding/decoding structure which takes into account the characteristics of the imaging chain (Parisot, 2001), but, to the best of our knowledge, the study of the global system optimization has not devoted much work; so that each process is usually optimized separately. In this paper, we focus on the global optimization of the satellite imaging chain including both compression and restoration. We propose a closed-form expression of the global distortion as a function of the chain parameters and we show how to optimize this distortion, for a given rate, to obtain the parameters of the restoration and the compression algorithms which lead to the minimal distortion

Plk4 Regulates Centriole Asymmetry and Spindle Orientation in Neural Stem Cells

Defects in mitotic spindle orientation (MSO) disrupt the organization of stem cell niches impacting tissue morphogenesis and homeostasis. Mutations in centrosome genes reduce MSO fidelity, leading to tissue dysplasia and causing several diseases such as microcephaly, dwarfism, and cancer. Whether these mutations perturb spindle orientation solely by affecting astral microtubule nucleation or whether centrosome proteins have more direct functions in regulatingMSO is unknown. To investigate this question, we analyzed the consequences of deregulating Plk4 (the master centriole duplication kinase) activity in Drosophila asymmetrically dividing neural stem cells. We found that Plk4 functions upstream of MSO control, orchestrating centriole symmetry breaking and consequently centrosome positioning. Mechanistically, we show that Plk4 acts through Spd2 phosphorylation, which induces centriole release from the apical cortex. Overall, this work not only reveals a role for Plk4 in regulating centrosome function but also links the centrosome biogenesis machinery with the MSO apparatus.ERC starting grant CentroStemCancer [242598]; Institut Curie; CNRS; NCI [P30CA23074]; NIGMS [R01 GM110166, GM126035]; FRM; IC; FRM installation grant; ATIP grantOpen access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

BLAST: Correlations in the Cosmic Far-Infrared Background at 250, 350, and 500 microns Reveal Clustering of Star-Forming Galaxies

We detect correlations in the cosmic far-infrared background due to the clustering of star-forming galaxies in observations made with the Balloon-borne Large Aperture Submillimeter Telescope, BLAST, at 250, 350, and 500 microns. We perform jackknife and other tests to confirm the reality of the signal. The measured correlations are well fit by a power law over scales of 5-25 arcminutes, with Delta I/I = 15.1 +/- 1.7%. We adopt a specific model for submillimeter sources in which the contribution to clustering comes from sources in the redshift ranges 1.3 <= z <= 2.2, 1.5 <= z <= 2.7, and 1.7 <= z <= 3.2, at 250, 350, and 500 microns, respectively. With these distributions, our measurement of the power spectrum, P(k_theta), corresponds to linear bias parameters, b = 3.8 +/- 0.6, 3.9 +/- 0.6 and 4.4 +/- 0.7, respectively. We further interpret the results in terms of the halo model, and find that at the smaller scales, the simplest halo model fails to fit our results. One way to improve the fit is to increase the radius at which dark matter halos are artificially truncated in the model, which is equivalent to having some star-forming galaxies at z >= 1 located in the outskirts of groups and clusters. In the context of this model we find a minimum halo mass required to host a galaxy is log (M_min / M_sun) = 11.5 (+0.4/-0.1), and we derive effective biases $b_eff = 2.2 +/- 0.2, 2.4 +/- 0.2, and 2.6 +/- 0.2, and effective masses log (M_eff / M_sun) = 12.9 +/- 0.3, 12.8 +/- 0.2, and 12.7 +/- 0.2, at 250, 350, and 500 microns, corresponding to spatial correlation lengths of r_0 = 4.9, 5.0, and 5.2 +/- 0.7 h^-1 Mpc, respectively. Finally, we discuss implications for clustering measurement strategies with Herschel and Planck.Comment: Accepted for publication in the Astrophysical Journal. Maps and other results available at http://blastexperiment.info