Extended Collaborative Representation-Based Hyperspectral Imagery Classification

Collaborative representation (CR) has been demonstrated to be very effective for hyperspectral image classification. However, insufficient diversity of training samples often results in limited classification accuracy under small-training-sample conditions, especially when diverse spectral variation...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Hauptverfasser:	Xie, Bobo, Mei, Shaohui, Zhang, Ge, Zhang, Yifan, Feng, Yan, Du, Qian
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Benchmark testing Classification Collaboration Datasets Dictionaries Estimation Extended collaborative representation (CR) hyperspectral classification Hyperspectral imaging Image classification Imagery limited training samples Measurement errors Representations Singular value decomposition Spectra spectral variation Training Variation
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!