The effects of spectral dimensionality reduction on hyperspectral pixel classification: A case study

This paper presents a systematic study of the effects of hyperspectral pixel dimensionality reduction on the pixel classification task. We use five dimensionality reduction methods—PCA, KPCA, ICA, AE, and DAE—to compress 301-dimensional hyperspectral pixels. Compressed pixels are subsequently used t...

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Detalles Bibliográficos
Autores principales: Mantripragada, Kiran, Dao, Phuong D., He, Yuhong, Qureshi, Faisal Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9282587/
https://www.ncbi.nlm.nih.gov/pubmed/35834472
http://dx.doi.org/10.1371/journal.pone.0269174

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9282587/
https://www.ncbi.nlm.nih.gov/pubmed/35834472
http://dx.doi.org/10.1371/journal.pone.0269174

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