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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Piqueras, Sara | es_ES |
dc.contributor.author | Maeder, Marcel | es_ES |
dc.contributor.author | Tauler, Romà | es_ES |
dc.contributor.author | de Juan, Anna | es_ES |
dc.date.accessioned | 2017-12-14T10:48:40Z | - |
dc.date.available | 2017-12-14T10:48:40Z | - |
dc.date.issued | 2017-05-15 | - |
dc.identifier.citation | Chemometrics and Intelligent Laboratory Systems: 164: 32-42 (2017) | es_ES |
dc.identifier.uri | http://hdl.handle.net/10261/158179 | - |
dc.description.abstract | Hyperspectral 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.sponsorship | A. 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.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/FP7/320737 | es_ES |
dc.relation.isversionof | Postprint | es_ES |
dc.rights | openAccess | en_EN |
dc.subject | Imaging matching | es_ES |
dc.subject | Multitechnique image analysis | es_ES |
dc.subject | Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) | es_ES |
dc.subject | MCR-ALS | es_ES |
dc.title | A new matching image preprocessing for image data fusion | es_ES |
dc.type | artículo | es_ES |
dc.identifier.doi | 10.1016/j.chemolab.2017.02.013 | - |
dc.description.peerreviewed | Peer reviewed | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.chemolab.2017.02.013 | es_ES |
dc.embargo.terms | 2019-05-15 | es_ES |
dc.rights.license | http://creativecommons.org/licenses/by-nc-nd/4.0/ | - |
dc.contributor.funder | European Research Council | es_ES |
dc.relation.csic | Sí | es_ES |
oprm.item.hasRevision | no ko 0 false | * |
dc.identifier.funder | http://dx.doi.org/10.13039/501100000781 | es_ES |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | es_ES |
item.openairetype | artículo | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
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A new matching image preprocessing for image data fusion.docx | 1,69 MB | Microsoft Word XML | Visualizar/Abrir |
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