Deep High-Order Tensor Convolutional Sparse Coding for Hyperspectral Image Classification

Most hyperspectral image (HSI) data exist in the form of tensor; the tensor representation preserves the potential spatial-spectral structure information compared with the vector representation, which can help improve the classification performance of HSI. In this article, a deep high-order tensor c...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 60; S. 1 - 11
Hauptverfasser:	Cheng, Chunbo, Li, Hong, Peng, Jiangtao, Cui, Wenjing, Zhang, Liming
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Classification Convolution Convolutional codes Deep high-order tensor convolutional sparse coding (CSC) deep learning Feature extraction graph-based learning (GSL) hyperspectral image (HSI) classification Hyperspectral imaging Image classification Image coding Kernel Mathematical analysis Methods Representations Spectra Tensors
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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