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Water column compensation workflow for hyperspectral imaging data

Our article describes a data processing workflow for hyperspectral imaging data to compensate for the water column in shallow, clear to moderate • Workflow calculates depth invariant indices for hyperspectral imaging data to compensate for the water column in shallow, clear to moderate optical water...

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Detalles Bibliográficos
Autores principales: Inamdar, Deep, Rowan, Gillian S.L., Kalacska, Margaret, Arroyo-Mora, J. Pablo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8693006/
https://www.ncbi.nlm.nih.gov/pubmed/34984174
http://dx.doi.org/10.1016/j.mex.2021.101601
Descripción
Sumario:Our article describes a data processing workflow for hyperspectral imaging data to compensate for the water column in shallow, clear to moderate • Workflow calculates depth invariant indices for hyperspectral imaging data to compensate for the water column in shallow, clear to moderate optical water types. • The applied principal component transformation generates features that account for a substantial amount of the variance from the depth invariant indices while reducing dimensionality. • The output (both depth invariant index image and principal component image) allows for the analysis of bottom type in shallow, clear to moderate optical water types.