Bilinear Hyperspectral Unmixing via Tensor Decomposition
Author:
Affiliation:
1. School of Math., Southwest Jiaotong Univ.,Chengdu,China
2. School of Elec. Eng. & Computer Sci., Oregon State Univ.,Corvallis,OR,United States,97331
3. School of Math. Sci., Univ. of Elec. Sci. & Tech. of China,Chengdu,China
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10289698/10289713/10289962.pdf?arnumber=10289962
Reference27 articles.
1. A Simplex Volume Maximization Framework for Hyperspectral Endmember Extraction
2. Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search Are Related
3. Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery
4. Decompositions of a Higher-Order Tensor in Block Terms—Part II: Definitions and Uniqueness
5. A Review of Nonlinear Hyperspectral Unmixing Methods
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