Multiple Clustering Guided Nonnegative Matrix Factorization for Hyperspectral Unmixing
نویسندگان
چکیده
منابع مشابه
Nonnegative Matrix Factorization With Data-Guided Constraints For Hyperspectral Unmixing
Abstract: Hyperspectral unmixing aims to estimate a set of endmembers and corresponding abundances in pixels. Nonnegative matrix factorization (NMF) and its extensions with various constraints have been widely applied to hyperspectral unmixing. L1/2 and L2 regularizers can be added to NMF to enforce sparseness and evenness, respectively. In practice, a region in a hyperspectral image may posses...
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ژورنال
عنوان ژورنال: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2020
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2020.3020541