Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data

Remote sensing hyperspectral images (HSIs) are quite often low rank, in the sense that the data belong to a low dimensional subspace/manifold. This has been recently exploited for the fusion of low spatial resolution HSI with high spatial resolution multispectral images in order to obtain super-reso...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on image processing Jg. 25; H. 1; S. 274 - 288
Hauptverfasser:	Veganzones, Miguel A., Simoes, Miguel, Licciardi, Giorgio, Yokoya, Naoto, Bioucas-Dias, Jose M., Chanussot, Jocelyn
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2016 Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithms Bands binary partition tree Computer Science data fusion dictionary learning Hyperspectral imagery Hyperspectral imaging Ill posed problems Manifolds multispectral imagery Partitions Sensors Signal and Image Processing Signal resolution Spatial resolution spectral unmixing Subspaces super-resolution data fusion spectral unmixing Hyperspectral imagery super-resolution multispectral imagery binary partition tree dictionary learning spectral un-mixing
ISSN:	1057-7149, 1941-0042
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!