Set-to-Set Distance-Based Spectral-Spatial Classification of Hyperspectral Images

A novel set-to-set distance-based spectral-spatial classification method for hyperspectral images (HSIs) is proposed. In HSIs, the spatially connected and spectrally similar pixels within each homogeneous region can be considered as one set of test samples, i.e., a test set, which should belong to t...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2016-12, Vol.54 (12), p.7122-7134
Main Authors: Ting Lu, Shutao Li, Leyuan Fang, Bruzzone, Lorenzo, Benediktsson, Jon Atli
Format: Article
Language:English
Subjects:
Adaptation models
Affine hull (AH) representation
hyperspectral image (HSI)
Hyperspectral imaging
Image edge detection
Image segmentation
Kernel
set-to-set distance
spectral–spatial classification
Training
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