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Title
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Spectral variability in a multilinear mixing model
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Author
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Abstract
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| We present a new method for spectral unmixing which takes both nonlinear mixing and spectral variability into account. This is accomplished by combining the multiple endmember spectral mixture analysis (MESMA) approach with the recently developed multilinear mixing model (MLM). As the traditional approach of nonlinear unmixing of all combinations is very time consuming, we investigate a second approach, where endmember model selection is linearly performed by a fast alternative for MESMA, followed by nonlinear unmixing. We show that this approach yields similar reconstruction errors (REs) as the full combinatorial approach, and hence results in a relatively fast method for nonlinear unmixing with variability. |
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Language
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English
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Source (journal)
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IEEE International Geoscience and Remote Sensing Symposium proceedings. - [New York]
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IEEE International Geoscience and Remote Sensing Symposium
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Source (book)
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38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS), JUL 22-27, 2018, Valencia, SPAIN
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Publication
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New york
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Ieee
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2018
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ISBN
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978-1-5386-7150-4
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978-1-5386-7150-4
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DOI
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10.1109/IGARSS.2018.8518635
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Volume/pages
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(2018)
, p. 4217-4220
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ISI
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000451039804048
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Full text (Publisher's DOI)
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Full text (open access)
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