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Erschienen in:

2010 | OriginalPaper | Buchkapitel

34. Dimensionality Reduction of Hyperspectral Imagery Data for FeatureClassification

verfasst von : Charles K. Chui, Jianzhong Wang

Erschienen in: Handbook of Geomathematics

Verlag: Springer Berlin Heidelberg

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Abstract

The objective of this chapter is to highlight the current research activities and recent progress in the area of dimensionality reduction of hyperspectral geological/geographical imagery data, which are widely used in image segmentation and feature classification. We will only focus on four topics of interest, namely hyperspectral image (HSI) data preprocessing, similarity/dissimilarity definition of HSI data, construction of dimensionality reduction (DR) kernels for HSI data, and HSI data dimensionality reduction algorithms based on DR kernels.

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Titel: Dimensionality Reduction of Hyperspectral Imagery Data for FeatureClassification
verfasst von: Charles K. Chui
Jianzhong Wang
Verlag: Springer Berlin Heidelberg
Buch: Handbook of Geomathematics
Print ISBN: 978-3-642-01545-8

Electronic ISBN: 978-3-642-01546-5

Copyright-Jahr: 2010
DOI: https://doi.org/10.1007/978-3-642-01546-5_34

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