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Morphological Component Analysis for the Inpainting of Grazing Incidence X-Ray Diffraction Images Used for the Structural Characterization of Thin Films

dc.rights.licenseopen
hal.structure.identifierCommissariat à l'énergie atomique et aux énergies alternatives [CEA]
dc.contributor.authorTZAGKARAKIS, G.
hal.structure.identifierLaboratoire de Chimie des Polymères Organiques [LCPO]
hal.structure.identifierTeam 4 LCPO : Polymer Materials for Electronic, Energy, Information and Communication Technologies
dc.contributor.authorPAVLOPOULOU, E.
hal.structure.identifierEquipe Image - Laboratoire GREYC - UMR6072
dc.contributor.authorFADILI, Jalal M.
hal.structure.identifierLaboratoire de Chimie des Polymères Organiques [LCPO]
hal.structure.identifierTeam 4 LCPO : Polymer Materials for Electronic, Energy, Information and Communication Technologies
dc.contributor.authorHADZIIOANNOU, Georges
hal.structure.identifierCommissariat à l'énergie atomique et aux énergies alternatives [CEA]
dc.contributor.authorSTARCK, J.-L.
dc.date.accessioned2020
dc.date.available2020
dc.date.issued2014
dc.identifier.issn1294-4475
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/19955
dc.description.abstractEnGrazing Incidence X-ray Diffraction (GIXD) is a widely used characterization technique, applied for the investigation of the structure of thin films. As far as organic films are concerned, the confinement of the film to the substrate results in anisotropic 2-dimensional GIXD patterns, such those observed for polythiophene-based films, which are used as active layers in photovoltaic applications. Potential malfunctions of the detectors utilized may distort the quality of the acquired images, affecting thus the analysis process and the structural information derived. Motivated by the success of Morphological Component Analysis (MCA) in image processing, we tackle in this study the problem of recovering the missing information in GIXD images due to potential detector’s malfunction. First, we show that the geometrical structures which are present in the GIXD images can be represented sparsely by means of a combination of over-complete transforms, namely, the curvelet and the undecimated wavelet transform, resulting in a simple and compact description of their inherent information content. Then, the missing information is recovered by applying MCA in an inpainting framework, by exploiting the sparse representation of GIXD data in these two over-complete transform domains. The experimental evaluation shows that the proposed approach is highly efficient in recovering the missing information in the form of either randomly burned pixels, or whole burned rows, even at the order of 50% of the total number of pixels. Thus, our approach can be applied for healing any potential problems related to detector performance during acquisition, which is of high importance in synchrotron-based experiments, since the beamtime allocated to users is extremely limited and any technical malfunction could be detrimental for the course of the experimental project. Moreover, the non-necessity of long acquisition times or repeating measurements, which stems from our results adds extra value to the proposed approach.
dc.language.isoen
dc.publisherInstitut Français du Pétrole
dc.title.enMorphological Component Analysis for the Inpainting of Grazing Incidence X-Ray Diffraction Images Used for the Structural Characterization of Thin Films
dc.typeArticle de revue
dc.identifier.doi10.2516/ogst/2012077
dc.subject.halPhysique [physics]
bordeaux.journalOil & Gas Science and Technology - Revue d'IFP Energies nouvelles
bordeaux.page261-277
bordeaux.volume69
bordeaux.hal.laboratoriesLaboratoire de Chimie des Polymères Organiques (LCPO) - UMR 5629*
bordeaux.issue2
bordeaux.institutionBordeaux INP
bordeaux.institutionUniversité de Bordeaux
bordeaux.peerReviewedoui
hal.identifierhal-01933374
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01933374v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Oil%20&%20Gas%20Science%20and%20Technology%20-%20Revue%20d'IFP%20Energies%20nouvelles&rft.date=2014&rft.volume=69&rft.issue=2&rft.spage=261-277&rft.epage=261-277&rft.eissn=1294-4475&rft.issn=1294-4475&rft.au=TZAGKARAKIS,%20G.&PAVLOPOULOU,%20E.&FADILI,%20Jalal%20M.&HADZIIOANNOU,%20Georges&STARCK,%20J.-L.&rft.genre=article


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