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An integrated approach to registration and fusion of hyperspectral and multispectral images / Yuan Zhou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 5 (May 2020) . - pp 3020 - 3033 Titre : An integrated approach to registration and fusion of hyperspectral and multispectral images Type de document : Article/Communication Auteurs : Yuan Zhou, Auteur ; Anand Rangarajan, Auteur ; Paul D. Gader, Auteur Année de publication : 2020 Article en page(s) : pp 3020 - 3033 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] algorithme de fusion [Termes IGN] distorsion d'image [Termes IGN] fusion d'images [Termes IGN] image à haute résolution [Termes IGN] image hyperspectrale [Termes IGN] image multibande [Termes IGN] méthode des moindres carrés [Termes IGN] points registration [Termes IGN] tâche image d'un point Résumé : (auteur) Combining a hyperspectral (HS) image and a multispectral (MS) image—an example of image fusion—can result in a spatially and spectrally high-resolution image. Despite the plethora of fusion algorithms in remote sensing, a necessary prerequisite, namely registration, is mostly ignored. This limits their application to well-registered images from the same source. In this article, we propose and validate an integrated registration and fusion approach (code available at https://github.com/zhouyuanzxcv/Hyperspectral ). The registration algorithm minimizes a least-squares (LSQ) objective function with the point spread function (PSF) incorporated together with a nonrigid freeform transformation applied to the HS image and a rigid transformation applied to the MS image. It can handle images with significant scale differences and spatial distortion. The fusion algorithm takes the full high-resolution HS image as an unknown in the objective function. Assuming that the pixels lie on a low-dimensional manifold invariant to local linear transformations from spectral degradation, the fusion optimization problem leads to a closed-form solution. The method was validated on the Pavia University, Salton Sea, and the Mississippi Gulfport datasets. When the proposed registration algorithm is compared to its rigid variant and two mutual information-based methods, it has the best accuracy for both the nonrigid simulated dataset and the real dataset, with an average error less than 0.15 pixels for nonrigid distortion of maximum 1 HS pixel. When the fusion algorithm is compared with current state-of-the-art algorithms, it has the best performance on images with registration errors as well as on simulations that do not consider registration effects. Numéro de notice : A2020-231 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2941494 Date de publication en ligne : 12/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2941494 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94969 [article]

Non rigid registration of shapes via diffeomorphic point matching and clustering / Laurent Garcin (2005)  

Public Titre : Non rigid registration of shapes via diffeomorphic point matching and clustering Type de document : Article/Communication Auteurs : Laurent Garcin, Auteur ; Anand Rangarajan, Auteur ; Laurent Younes, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2005 Conférence : ICIP 2004, 11th IEEE International Conference on Image Processing 24/10/2004 27/10/2004 Singapour Singapour Proceedings IEEE Importance : pp 1703 - 1706 ou pp 3299 - 3302 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de groupement [Termes IGN] appariement de formes [Termes IGN] appariement de points [Termes IGN] méthode de réduction d'énergie [Termes IGN] semis de points Résumé : (auteur) We propose an algorithm achieving the matching of two point sets with unknown correspondence via the joint clustering of the two sets and estimation of a diffeomorphism linking the cluster centers via geodesic splines. Numéro de notice : C2004-048 Affiliation des auteurs : IGN+Ext (1940-2011) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICIP.2004.1421819 Date de publication en ligne : 18/04/2005 En ligne : https://doi.org/10.1109/ICIP.2004.1421819 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103043