Enhancing Hyperspectral Images Compressive Sensing Reconstruction With Smooth Low-Rankness Joint Gradient Sparsity

The application of compressive sensing (CS) theory in hyperspectral images (HSI) reconstruction has been validated. The key to model-based reconstruction methods lies in effectively integrating prior knowledge of HSI. However, capturing multiple prior knowledge means that multiple regularization ter...

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Bibliographic Details

Published in:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Main Authors:	Yanyan Lv, Dan Li, Fanqiang Kong, Xinwei Wan, Qiang Wang
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Compressive sensing (CS) hyperspectral images (HSI) reconstruction multidimensional coupled gradient sparsity (MCGS) smooth spatial-spectral low-rank model (SSLR) the local smoothness
Online Access:	https://ieeexplore.ieee.org/document/11042909/