Learning dependent sources using mixtures of Dirichlet: applications on hyperspectral unmixing
This paper is an elaboration of the DECA algorithm [1] to blindly unmix hyperspectral data. The underlying mixing model is linear, meaning that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. The proposed method, as DECA, is tailored to...
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| Format: | conferenceObject |
| Language: | eng |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/10400.21/921 |
| Country: | Portugal |
| Oai: | oai:repositorio.ipl.pt:10400.21/921 |