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A fully automated, faster noise rejection approach to increasing the analytical capability of chemical imaging for digital histopathology
Chemical hyperspectral imaging (HSI) data is naturally high dimensional and large. There are thus inherent manual trade-offs in acquisition time, and the quality of data. Minimum Noise Fraction (MNF) developed by Green et al. [1] has been extensively studied as a method for noise removal in HSI data...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481772/ https://www.ncbi.nlm.nih.gov/pubmed/31017894 http://dx.doi.org/10.1371/journal.pone.0205219 |