Hyperspectral Image Unmixing Incorporating Adjacency Information
While the spectral information contained in hyperspectral images is rich, the spatial resolution of such images is in many cases very low. Many pixel spectra are mixtures of pure materials’ spectra and therefore need to be decomposed into their constituents. This work investigates new decomposition...
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| Superior document: | Forschungsberichte aus der Industriellen Informationstechnik / Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie |
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| : | |
| Year of Publication: | 2018 |
| Language: | English |
| Series: | Forschungsberichte aus der Industriellen Informationstechnik / Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie
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| Physical Description: | 1 electronic resource (XIII, 203 p. p.) |
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| 520 | |a While the spectral information contained in hyperspectral images is rich, the spatial resolution of such images is in many cases very low. Many pixel spectra are mixtures of pure materials’ spectra and therefore need to be decomposed into their constituents. This work investigates new decomposition methods taking into account spectral, spatial and global 3D adjacency information. This allows for faster and more accurate decomposition results. | ||
| 546 | |a English | ||
| 653 | |a Spektrale Entmischung | ||
| 653 | |a spectral unmixing | ||
| 653 | |a Blinde Quellentrennung | ||
| 653 | |a Hyperspectral image processing | ||
| 653 | |a Nichtnegative Matrixzerlegung | ||
| 653 | |a nonnegative matrix factorization | ||
| 653 | |a blind source separation | ||
| 653 | |a Hyperspektrale Bildverarbeitung | ||
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