Superpixel-Based Weighted Collaborative Sparse Regression and Reweighted Low-Rank Representation for Hyperspectral Image Unmixing

Sparse unmixing with a semisupervised fashion has been applied to hyperspectral remote sensing imagery. However, the imprecise spatial contextual information, the lack of global feature and the high mutual coherences of a spectral library greatly limit the performance of sparse unmixing. In order to...

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Detalhes bibliográficos

Principais autores:	Hongjun Su, Cailing Jia, Pan Zheng, Qian Du
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2022-01-01
coleção:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Assuntos:	Hyperspectral image (HSI) unmixing reweighted low-rank representation (LRR) simple linear iterative clustering (SLIC) weighted collaborative sparse regression
Acesso em linha:	https://ieeexplore.ieee.org/document/9640522/
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