Title
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Towards streaming hyperspectral endmember extraction
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Author
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Abstract
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A prevalent methodology for extracting pure pixels from hyperspectral images has been the use of linear-mixture geometry, which dictates that pure components must reside at the corners of a simplex enclosing all the remaining points (the mixtures). Recently, adaptations to popular algorithms for estimating the largest simplex (e.g. N-findr) have been proposed, aimed to reduce their number of iterations and so shorten the execution time. This paper goes a step further, by proposing to perform the simplex maximization in a streaming fashion, that is, by evaluating one pixel at a time without using large buffers or subsequent pixels. This is achieved by reformulating the simplex measurement in terms of distance-based geometry. Besides, a new streaming simplex-growing initialization procedure is proposed. Tested on several natural scenes, the proposed algorithm is found to yield results comparable to those produced by the reference methods. |
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Language
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English
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Source (book)
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IEEE IGARSS2011, IEEE International Geoscience and Remote Sensing Symposium , Vancouver, Canada, July 24-29, 2011
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Publication
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S.l.
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2011
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ISBN
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978-1-4577-1003-2
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DOI
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10.1109/IGARSS.2011.6049724
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Volume/pages
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p. 2519-2522
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ISI
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000297496302135
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Full text (Publisher's DOI)
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