Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction

Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction

Hyperspectral image compressive sensing reconstruction (HSI-CSR) is an important issue in remote sensing, and has recently been investigated increasingly by the sparsity prior based approaches. However, most of the available HSI-CSR methods consider the sparsity prior in spatial and spectral vector...

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Bibliographic Details
Main Authors: Jize Xue, Yongqiang Zhao, Wenzhi Liao, Jonathan Cheung-Wai Chan
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Remote Sensing
Subjects:
hyperspectral image
compressive sensing
structured sparsity
tensor sparse decomposition
tensor low-rank approximation
Online Access:http://www.mdpi.com/2072-4292/11/2/193

Internet

http://www.mdpi.com/2072-4292/11/2/193

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