Reducing the dimensionality of hyperspectral remotely sensed data with applications for maximum likelihood image classification

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Reducing the dimensionality of hyperspectral remotely sensed data with applications for maximum likelihood image classification

As well as the many benefits associated with the evolution of multispectral sensors into hyperspectral sensors there is also a considerable increase in storage space and the computational load to process the data. Consequently the remote sensing ommunity is investigating and developing statistical m...

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Bibliographic Details
Main Author:	Santich, Norman Ty
Format:	Thesis
Language:	English
Published:	Curtin University 2007
Subjects:	correlations hyperspectral image data HyMap instrument dimensionality maximum likelihood classification (MLC) hyperspectral remotely sensed data
Online Access:	http://hdl.handle.net/20.500.11937/741

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