Parallel hyperspectral unmixing method on GPU
Many Hyperspectral imagery applications require a response in real time or near-real time. To meet this requirement this paper proposes a parallel unmixing method developed for graphics processing units (GPU). This method is based on the vertex component analysis (VCA), which is a geometrical based...
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| Other Authors: | , , |
| Format: | conferenceObject |
| Language: | eng |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10400.21/6139 |
| Country: | Portugal |
| Oai: | oai:repositorio.ipl.pt:10400.21/6139 |
| Summary: | Many Hyperspectral imagery applications require a response in real time or near-real time. To meet this requirement this paper proposes a parallel unmixing method developed for graphics processing units (GPU). This method is based on the vertex component analysis (VCA), which is a geometrical based method highly parallelizable. VCA is a very fast and accurate method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Experimental results obtained for simulated and real hyperspectral datasets reveal considerable acceleration factors, up to 24 times. |
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