Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox
Helmholtz-Zentrum Dresden-Rossendorf · Helmholtz Institute Freiberg for Resource Technology · +5 more institutions
Abstract
Hyperspectral images (HSIs) provide detailed spectral information through hundreds of (narrow) spectral channels (also known as dimensionality or bands), which can be used to accurately classify diverse materials of interest. The increased dimensionality of such data makes it possible to significantly improve data information content but provides a challenge to conventional techniques (the so-called curse of dimensionality) for accurate analysis of HSIs.
Citation impact
- FWCI
- 70.76
- Percentile
- 100%
- References
- 123
Authors
7- BRBehnood RastiCorresponding
Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology
- DHDanfeng Hong
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
- RHRenlong Hang
Nanjing University of Information Science and Technology
- PGPedram Ghamisi
Helmholtz-Zentrum Dresden-Rossendorf
- XKXudong Kang
Artificial Intelligence in Medicine (Canada)
Topics & keywords
- Hyperspectral imaging
- Toolbox
- Curse of dimensionality
- Pattern recognition (psychology)
- Feature extraction
- Feature (linguistics)
- Dimensionality reduction