Endmember Constraint Non-Negative Tensor Factorization Via Total Variation for Hyperspectral Unmixing

• Published in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS pp. 3313 - 3316
• Main Authors: Wang, Jin-Ju, Wang, Ding-Cheng, Huang, Ting-Zhu, Huang, Jie
• Format: Conference Proceeding
• Language: English
• Published: IEEE 11.07.2021
• Subjects: Correlation; endmember constraint; Geoscience and remote sensing; Hyperspectral imaging; Hyperspectral unmixing; non-negative tensor factorization; Roads; Soil; Tensors

Hyperspectral unmixing (HU), estimating endmembers and the corresponding abundances, is crucial for the development of hyperspectral images (HSIs). To improve the unmixing performance, various spatial regularizers are imposed on the abundance matrix. Note that endmember information is also important...