Nonlinear Unmixing of Hyperspectral Data Using Semi-Nonnegative Matrix Factorization
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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Unmixing of remote-sensing data using nonnegative matrix factorization has been considered recently. To improve performance, additional constraints are added to the cost function. The main challenge is to introduce constraints that lead to better results for unmixing. Correlation between bands of Hyperspectral images is the problem that is paid less attention to it in the unmixing algorithms. I...
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ژورنال
عنوان ژورنال: IEEE Transactions on Geoscience and Remote Sensing
سال: 2014
ISSN: 0196-2892,1558-0644
DOI: 10.1109/tgrs.2013.2251349