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dc.contributor.authorPiqueras Solsona, Saraes_ES
dc.contributor.authorMaeder, Marceles_ES
dc.contributor.authorTauler, Romàes_ES
dc.contributor.authorDe Juan, Annaes_ES
dc.identifier.citationChemometrics and Intelligent Laboratory Systems: 164: 32-42 (2017)es_ES
dc.description.abstractHyperspectral images collected with different spectroscopic techniques can be combined to benefit from complementary information and to improve the general description of chemical systems. The simultaneous analysis of images collected by different spectroscopic platforms can only be carried out when images are spatially matched with each other (i.e., different pixel sizes should be balanced and translation/rotation/scaling transformations should be done if required). The main goal of this work is the proposal of a general methodology to match image spatial properties that uses all pixels acquired in the images and, therefore, avoids the step of selecting analogous reference pixels to be compared. The effect of working with different kinds of image starting information on the robustness of the retrieved optimal translation and rotation parameters has also been assessed. The study has been tested in two different representative situations, namely: a) imaged sample with a clear contour b) imaged sample without defined contour. A final study on the effect of proper image matching is performed by applying Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to the multiset formed by the appended images from different spectroscopic platforms before and after matching. © 2017 Elsevier B.V.es_ES
dc.description.sponsorshipA. de Juan and R. Tauler acknowledge financial support from the European Research Council under the European Union's Seventh Framework Programme (FP/2007?2013) / ERC Grant Agreement no. 32073 (CHEMAGEB project). They also belong to the network of recognized research groups by the Catalan government (2014 SGR 1106). S. Piqueras acknowledge financial support from the Spanish government project CTQ2015-66254-C2-2-P.es_ES
dc.subjectImaging matchinges_ES
dc.subjectMultitechnique image analysises_ES
dc.subjectMultivariate Curve Resolution-Alternating Least Squares (MCR-ALS)es_ES
dc.titleA new matching image preprocessing for image data fusiones_ES
dc.description.peerreviewedPeer reviewedes_ES
dc.contributor.funderEuropean Research Counciles_ES
oprm.item.hasRevisionno ko 0 false*
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