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Spatial low-rank tensor factorization for hyperspectral image unmixing 

Navas-Auger, William J. (2021-05-14)
This work presents a method for hyperspectral image unmixing based on nonnegative tensor factorization. While traditional approaches may process spectral information without regard for spatial structures in the data set, ...

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AuthorNavas-Auger, William J. (1)AdvisorManian, Vidya (1)KeywordsHyperspectral Unmixing (1)Low-Rank (1)
Non-negative Tensor Factorization (1)
Remote Sensing (1)Signal Separation (1)... View MoreSubject HeadingCalculus of tensors (1)
Factorization (Mathematics) (1)
Remote sensing (1)Spatial analysis (Statistics) (1)Spectral imaging (1)Vector processing (Computer science) (1)TypeDissertation (1)Date2021 (1)DepartmentDepartment of Computer Science and Engineering (1)ProgramComputing and Information Sciences and Engineering (1)CollectionTheses & Dissertations (1)

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