Loading [a11y]/accessibility-menu.js
Hyperspectral and Multispectral Image Fusion via Variational Tensor Subspace Decomposition | IEEE Journals & Magazine | IEEE Xplore
Scheduled Maintenance: On Monday, 27 January, the IEEE Xplore Author Profile management portal will undergo scheduled maintenance from 9:00-11:00 AM ET (1400-1600 UTC). During this time, access to the portal will be unavailable. We apologize for any inconvenience.

Hyperspectral and Multispectral Image Fusion via Variational Tensor Subspace Decomposition


Abstract:

The fusion of hyperspectral image (HSI) and multispectral image (MSI) refers to enhance the spatial resolution of HSI with the help of a corresponding MSI that has a high...Show More

Abstract:

The fusion of hyperspectral image (HSI) and multispectral image (MSI) refers to enhance the spatial resolution of HSI with the help of a corresponding MSI that has a high spatial resolution to finally obtain an HSI with high resolution in both spatial and spectral domains. In this letter, we propose a variational tensor subspace decomposition-based fusion method to fully explore the differences and correlations among three modes of the HSI tensor. Experimental results on two HSI datasets show that the proposed method can achieve superior performance compared with existing state-of-the-art fusion methods with high computational efficiency.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 19)
Article Sequence Number: 5001805
Date of Publication: 15 July 2021

ISSN Information:

Funding Agency:


References

References is not available for this document.