Dynamical spectral unmixing of multitemporal hyperspectral images

In this paper, we consider the problem of unmixing a time series of hyperspectral images. We propose a dynamical model based on linear mixing processes at each time instant. The spectral signatures and fractional abundances of the pure materials in the scene are seen as latent variables, and assumed to follow a general dynamical structure. Based on a simplified version of this model, we derive an efficient spectral unmixing algorithm to estimate the latent variables by performing alternating minimizations. The performance of the proposed approach is demonstrated on synthetic and real multitemporal hyperspectral images.Comment: 13 pages, 10 figure

On the minimization of total mean curvature

International audienceIn this paper we are interested in possible extensions of an inequality due to Minkowski: $\int_{\partial\Omega} H\,dA \geq \sqrt{4\pi A(\partial\Omega)}$ valid for any regular open set $\Omega\subset\mathbb{R}^3$, where $H$ denotes the scalar mean curvature and $A$ the area. We prove that this inequality holds true for axisymmetric domains which are convex in the direction orthogonal to the axis of symmetry. We also show that this inequality cannot be true in more general situations. However we prove that $\int_{\partial\Omega} |H|\,dA \geq \sqrt{4\pi A(\partial\Omega)}$ remains true for any axisymmetric domain

Blind hyperspectral unmixing using an Extended Linear Mixing Model to address spectral variability

International audienceThe Linear Mixing Model is often used to perform Hyperspec-tral Unmixing because of its simplicity, but it assumes that a single spectral signature can be completely representative of an endmember. However, in many scenarios, this assumption does not hold since many factors such as illumination conditions and intrinsic variability of the endmembers have consequences on the spectral signatures of the materials. In this paper, we propose a simple yet flexible algorithm to unmix hyperspectral data using a recently proposed Extended Linear Mixing Model. This model allows a pixelwise variation of the endmembers, which leads to consider scaled versions of reference endmember spectra. The results on synthetic data show that the proposed technique outperforms other methods aimed at tackling spectral variability, and provides an accurate estimation of endmember variability along the observed scene thanks to the scaling factors estimation, provided the abundance of the corresponding material is sufficient

Blind hyperspectral unmixing using an Extended Linear Mixing Model to address spectral variability

International audienceSpectral Unmixing is one of the main research topics in hyperspectral imaging. It can be formulated as a source separation problem whose goal is to recover the spectral signatures of the materials present in the observed scene (called endmembers) as well as their relative proportions (called fractional abundances), and this for every pixel in the image. A Linear Mixture Model is often used for its simplicity and ease of use but it implicitly assumes that a single spectrum can be completely representative of a material. However, in many scenarios, this assumption does not hold since many factors, such as illumination conditions and intrinsic variability of the endmembers, induce modifications on the spectral signatures of the materials. In this paper, we propose an algorithm to unmix hyperspectral data using a recently proposed Extended Linear Mixing Model. The proposed approach allows a pixelwise spatially coherent local variation of the endmembers, leading to scaled versions of reference endmembers. We also show that the classic nonnegative least squares, as well as other approaches to tackle spectral variability can be interpreted in the framework of this model. The results of the proposed algorithm on two different synthetic datasets, including one simulating the effect of topography on the measured reflectance through physical modelling, and on two real datasets, show that the proposed technique outperforms other methods aimed at addressing spectral variability, and can provide an accurate estimation of endmember variability along the scene thanks to the scaling factors estimation

Semaine d'Etude Mathématiques et Entreprises 5 : Détection de marques de cylindres sur une ligne sidérurgique, ou comment séparer des sources périodiques dans une image bruitée

Lors de la fabrication de tôe par laminage, des défauts périodiques peuvent être marqués par les cylindres qui compressent le métal. Un contrôle automatique est incorporé dans le processus afin de détecter les défauts par traitement numérique des images prises par des capteurs. Ces images sont de grandes tailles et fortement bruitées de sorte que les défauts sont souvent à peine perceptibles. Arcelor Mittal propose ici de réfléchir sur des méthodes robustes et performantes qui permettraient l'extraction des composantes périodiques des images. Ce document est la synthèse des méthodes et pistes que nous avons explorées lors de cette cinquième édition de la SEME à l'Ecole des Mines de Nancy

Approximation of the critical buckling factor for composite panels

This article is concerned with the approximation of the critical buckling factor for thin composite plates. A new method to improve the approximation of this critical factor is applied based on its behavior with respect to lamination parameters and loading conditions. This method allows accurate approximation of the critical buckling factor for non-orthotropic laminates under complex combined loadings (including shear loading). The influence of the stacking sequence and loading conditions is extensively studied as well as properties of the critical buckling factor behavior (e.g concavity over tensor D or out-of-plane lamination parameters). Moreover, the critical buckling factor is numerically shown to be piecewise linear for orthotropic laminates under combined loading whenever shear remains low and it is also shown to be piecewise continuous in the general case. Based on the numerically observed behavior, a new scheme for the approximation is applied that separates each buckling mode and builds linear, polynomial or rational regressions for each mode. Results of this approach and applications to structural optimization are presented

Evidence for the Higgs-boson Yukawa coupling to tau leptons with the ATLAS detector

Results of a search for H → τ τ decays are presented, based on the full set of proton-proton collision data recorded by the ATLAS experiment at the LHC during 2011 and 2012. The data correspond to integrated luminosities of 4.5 fb−1 and 20.3 fb−1 at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV respectively. All combinations of leptonic (τ → `νν¯ with ` = e, µ) and hadronic (τ → hadrons ν) tau decays are considered. An excess of events over the expected background from other Standard Model processes is found with an observed (expected) significance of 4.5 (3.4) standard deviations. This excess provides evidence for the direct coupling of the recently discovered Higgs boson to fermions. The measured signal strength, normalised to the Standard Model expectation, of µ = 1.43 +0.43 −0.37 is consistent with the predicted Yukawa coupling strength in the Standard Model

Search for squarks and gluinos in events with isolated leptons, jets and missing transverse momentum at s√=8 TeV with the ATLAS detector

The results of a search for supersymmetry in final states containing at least one isolated lepton (electron or muon), jets and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. The search is based on proton-proton collision data at a centre-of-mass energy s√=8 TeV collected in 2012, corresponding to an integrated luminosity of 20 fb−1. No significant excess above the Standard Model expectation is observed. Limits are set on supersymmetric particle masses for various supersymmetric models. Depending on the model, the search excludes gluino masses up to 1.32 TeV and squark masses up to 840 GeV. Limits are also set on the parameters of a minimal universal extra dimension model, excluding a compactification radius of 1/R c = 950 GeV for a cut-off scale times radius (ΛR c) of approximately 30

Measurement of the top pair production cross section in 8 TeV proton-proton collisions using kinematic information in the lepton plus jets final state with ATLAS

A measurement is presented of the $t\bar{t}$ inclusive production cross-section in $pp$ collisions at a center-of-mass energy of $\sqrt{s}=8$ TeV using data collected by the ATLAS detector at the CERN Large Hadron Collider. The measurement was performed in the lepton+jets final state using a data set corresponding to an integrated luminosity of 20.3 fb$^{-1}$. The cross-section was obtained using a likelihood discriminant fit and $b$-jet identification was used to improve the signal-to-background ratio. The inclusive $t\bar{t}$ production cross-section was measured to be $260\pm 1{\textrm{(stat.)}} ^{+22}_{-23} {\textrm{(syst.)}}\pm 8{\textrm{(lumi.)}}\pm 4{\mathrm{(beam)}}$ pb assuming a top-quark mass of 172.5 GeV, in good agreement with the theoretical prediction of $253^{+13}_{-15}$ pb. The $t\bar{t}\to (e,\mu)+{\mathrm{jets}}$ production cross-section in the fiducial region determined by the detector acceptance is also reported.Comment: Published version, 19 pages plus author list (35 pages total), 3 figures, 2 tables, all figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/TOPQ-2013-06

Measurement of the charge asymmetry in dileptonic Decays of top quark pairs in pp collisions at √ s = 7 TeV using the ATLAS detector

A measurement of the top-antitop (tt) charge asymmetry is presented using data corresponding to an integrated luminosity of 4.6 fb −1 of LHC pp collisions at a centre- of-mass energy of 7 TeV collected by the ATLAS detector. Events with two charged leptons, at least two jets and large missing transverse momentum are selected. Two observables are studied: A tt/C, based on the reconstructed tt final state. The asymmetries are measured to be A ll/C = 0.024 +/- 0.015 (stat.) +/- 0.009 (syst.) Att/C = 0.021 +/- 0.025 (stat.) +/- 0.017 (syst.) The measured values are in agreement with the Standard Model predictions