Automatic Extraction of Optimal Endmembers from Airborne Hyperspectral Imagery Using Iterative Error Analysis (IEA) and Spectral Discrimination Measurements

Pure surface materials denoted by endmembers play an important role in hyperspectral processing in various fields. Many endmember extraction algorithms (EEAs) have been proposed to find appropriate endmember sets. Most studies involving the automatic extraction of appropriate endmembers without a pr...

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Detalles Bibliográficos
Autores principales: Song, Ahram, Chang, Anjin, Choi, Jaewan, Choi, Seokkeun, Kim, Yongil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367322/
https://www.ncbi.nlm.nih.gov/pubmed/25625907
http://dx.doi.org/10.3390/s150202593

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4367322/
https://www.ncbi.nlm.nih.gov/pubmed/25625907
http://dx.doi.org/10.3390/s150202593

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