Centre de documentation
scientifique

Processing and analysis of hyperspectral data / Jie Chen (2020)  

Public Titre : Processing and analysis of hyperspectral data Type de document : Monographie Auteurs : Jie Chen, Éditeur scientifique ; Yingying Song, Éditeur scientifique ; Hengchao Li, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 140 p. ISBN/ISSN/EAN : 978-1-78985-109-0 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] apprentissage profond [Termes IGN] classification dirigée [Termes IGN] classification non dirigée [Termes IGN] image à haute résolution [Termes IGN] image hyperspectrale [Termes IGN] image proche infrarouge [Termes IGN] qualité des eaux [Termes IGN] signature spectrale [Termes IGN] turbidité des eaux Résumé : (Editeur) Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods. Note de contenu : Section One - Theoretical advances of hyperspectral image processing Chapter 1 - Hyperspectral endmember extraction techniques Chapter 2 - Hyperspectral image classification Chapter 3 - Hyperspectral image super-resolution using optimization and DCNN-based methods Chapter 4 - Fast chaotic encryption for hyperspectral images Section Two - Applications of hyperspectral image processing Chapter 5 - NIR hyperspectral imaging for mapping of moisture content distribution in tea buds during dehydration Chapter 6 - Use of hyperspectral remote sensing to estimate water quality Numéro de notice : 26560 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.78179 En ligne : http://doi.org/10.5772/intechopen.78179 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98243