Model-based co-clustering for hyperspectral images
A model-based co-clustering algorithm for hyperspectral images is presented. This algorithm, which relies on the probabilistic latent block model for continuous data, aims to cluster both the pixels and the spectral features of the images. This approach has been applied to a benchmark Raman imaging...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IM Publications Open
2016-10-01
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| Series: | Journal of Spectral Imaging |
| Subjects: | |
| Online Access: | https://www.impublications.com/download.php?code=I05_a3 |
| _version_ | 1798043773115039744 |
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| author | Julien Jacques Cyril Ruckebusch |
| author_facet | Julien Jacques Cyril Ruckebusch |
| author_sort | Julien Jacques |
| collection | DOAJ |
| description | A model-based co-clustering algorithm for hyperspectral images is presented. This algorithm, which relies on the probabilistic latent block model for continuous data, aims to cluster both the pixels and the spectral features of the images. This approach has been applied to a benchmark Raman imaging dataset and revealed relevant information for spatial–spectral exploratory investigation of the data. |
| first_indexed | 2024-04-11T22:53:45Z |
| format | Article |
| id | doaj.art-9665d1f90fc746d3be24b0006b3ab121 |
| institution | Directory Open Access Journal |
| issn | 2040-4565 2040-4565 |
| language | English |
| last_indexed | 2024-04-11T22:53:45Z |
| publishDate | 2016-10-01 |
| publisher | IM Publications Open |
| record_format | Article |
| series | Journal of Spectral Imaging |
| spelling | doaj.art-9665d1f90fc746d3be24b0006b3ab1212022-12-22T03:58:30ZengIM Publications OpenJournal of Spectral Imaging2040-45652040-45652016-10-015a310.1255/jsi.2016.a3Model-based co-clustering for hyperspectral imagesJulien Jacques0Cyril Ruckebusch1Université Lyon, Lumière Lyon 2, ERIC, Lyon, FranceUniversité de Lille, Sciences et technologies, LASIR CNRS, Lille, FrancA model-based co-clustering algorithm for hyperspectral images is presented. This algorithm, which relies on the probabilistic latent block model for continuous data, aims to cluster both the pixels and the spectral features of the images. This approach has been applied to a benchmark Raman imaging dataset and revealed relevant information for spatial–spectral exploratory investigation of the data.https://www.impublications.com/download.php?code=I05_a3co-clusteringlatent block modelhyperspectral images |
| spellingShingle | Julien Jacques Cyril Ruckebusch Model-based co-clustering for hyperspectral images Journal of Spectral Imaging co-clustering latent block model hyperspectral images |
| title | Model-based co-clustering for hyperspectral images |
| title_full | Model-based co-clustering for hyperspectral images |
| title_fullStr | Model-based co-clustering for hyperspectral images |
| title_full_unstemmed | Model-based co-clustering for hyperspectral images |
| title_short | Model-based co-clustering for hyperspectral images |
| title_sort | model based co clustering for hyperspectral images |
| topic | co-clustering latent block model hyperspectral images |
| url | https://www.impublications.com/download.php?code=I05_a3 |
| work_keys_str_mv | AT julienjacques modelbasedcoclusteringforhyperspectralimages AT cyrilruckebusch modelbasedcoclusteringforhyperspectralimages |