Hyperspectral Image Superresolution Using Global Gradient Sparse and Nonlocal Low-Rank Tensor Decomposition With Hyper-Laplacian Prior

Hyperspectral Image Superresolution Using Global Gradient Sparse and Nonlocal Low-Rank Tensor Decomposition With Hyper-Laplacian Prior

This article presents a novel global gradient sparse and nonlocal low-rank tensor decomposition model with a hyper-Laplacian prior for hyperspectral image (HSI) superresolution to produce a high-resolution HSI (HR-HSI) by fusing a low-resolution HSI (LR-HSI) with an HR multispectral image (HR-MSI)....

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Bibliographic Details
Main Authors: Yidong Peng, Weisheng Li, Xiaobo Luo, Jiao Du
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Global gradient sparse
hyper-Laplacian
hyperspectral image
nonlocal low-rank
superresolution
total variation
Online Access:https://ieeexplore.ieee.org/document/9417623/

Internet

https://ieeexplore.ieee.org/document/9417623/

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