Clustered multitask non-negative matrix factorization for spectral unmixing of hyperspectral data
Author:
Affiliation:
1. Qom University of Technology, Faculty of Electrical and Computer Engineering, Qom
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Earth and Planetary Sciences
Reference32 articles.
1. Spectral unmixing
2. Hyperspectral Unmixing in the Presence of Mixed Noise Using Joint-Sparsity and Total Variation
3. Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization
4. Improving Spatial–Spectral Endmember Extraction in the Presence of Anomalous Ground Objects
5. Modeling linear and intimate mixtures of materials in hyperspectral imagery with single-scattering albedo and kernel approaches
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