Hybrid Probabilistic Sparse Coding With Spatial Neighbor Tensor for Hyperspectral Imagery Classification

Under the umbrella of tensor algebra, this paper proposes a new sparse-coding-based classifier (SCC) for hyperspectral imagery classification (HIC). By utilizing the tensor forms of hyperspectral pixels, we advance a tensor sparse-coding model which preserves as many original spatial constraints of...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 56; H. 5; S. 2491 - 2502
Hauptverfasser:	Yang, Lixia, Wang, Min, Yang, Shuyuan, Zhao, Hui, Jiao, Licheng, Feng, Xiangchu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Classification Coding Encoding Hybrid probabilistic hyperspectral imagery classification (HIC) Hyperspectral imaging Image classification Imagery Mathematical analysis Maximization Pixels Probabilistic logic Probability theory Regularization spatial constraint State of the art Statistical analysis Tensile stress tensor sparse coding Tensors Training Uncertainty
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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