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A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation

By Min Zhao and others
Spectral unmixing is an important and challenging problem in hyperspectral data processing. This topic has been extensively studied and a variety of unmixing algorithms have been proposed in the literature. However, the lack of publicly available dataset with ground-truth makes it difficult to evaluate and compare the performance of unmixing... Show more
February 22, 2019
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A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation
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