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Uniformity-based superpixel segmentation of hyperspectral images / Arun M. Saranathan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 3 (March 2016) . - pp 1419 - 1430 Titre : Uniformity-based superpixel segmentation of hyperspectral images Type de document : Article/Communication Auteurs : Arun M. Saranathan, Auteur ; Mario Parente, Auteur Année de publication : 2016 Article en page(s) : pp 1419 - 1430 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] analyse des mélanges spectraux [Termes IGN] analyse infrapixellaire [Termes IGN] données géologiques [Termes IGN] image AVIRIS [Termes IGN] image hyperspectrale [Termes IGN] segmentation d'image Résumé : (Auteur) Superpixel segmentation algorithms attempt to group contiguous image pixels which are in homogeneous regions into segments (superpixels). Superpixel segmentation maps have proven successful in improving the performance of unmixing algorithms on hyperspectral images. For hyperspectral images (HSIs), segment members must contain spectrally similar pixels, a requirement we refer to as segment uniformity. Existing superpixel segmentation algorithms which have been applied to HSIs provide no guarantees on the uniformity inside segments. In the absence of such guarantees, the only viable option is to make the segments small enough that uniformity is always ensured; this leads to an oversegmentation of the image. An accurate uniformity measure would lead to a more accurate segmentation. We propose a graph-based agglomerative approach that enforces segment uniformity by setting a threshold for maximum variability inside segments. The threshold is computed by a statistical analysis of the within-class and between-class spectral divergences of several mineral families of interest. We show that the proposed algorithm can be used to generate parsimonious segmentations and facilitate the computation of accurate mineralogical summaries for several simulated and real HSIs of terrestrial and planetary geological surfaces. Numéro de notice : A2016-123 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2480863 En ligne : https://doi.org/10.1109/TGRS.2015.2480863 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80003 [article]

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