Spatial‐spectral feature extraction of hyperspectral images using tensor‐based collaborative graph analysis

Spatial‐spectral feature extraction of hyperspectral images using tensor‐based collaborative graph analysis

Abstract Although the collaborative graph‐based discriminant analysis (CGDA) method has shown promising performance for the feature extraction of the hyperspectral image (HSI), both the intrinsic local subspace structures and spatial structural information are ignored in CGDA. To address these probl...

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Bibliographic Details
Main Author: Lei Pan
Format: Article
Language:English
Published: Wiley 2021-07-01
Series:Electronics Letters
Subjects:
Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research
Optical, image and video signal processing
Image recognition
Computer vision and image processing techniques
Other topics in statistics
Combinatorial mathematics
Online Access:https://doi.org/10.1049/ell2.12109

Internet

https://doi.org/10.1049/ell2.12109

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