Heterogeneous Spectral-Spatial Feature Transfer With Structure Preserved Distribution Alignment for Hyperspectral Image Classification

Heterogeneous Spectral-Spatial Feature Transfer With Structure Preserved Distribution Alignment for Hyperspectral Image Classification

Cross-scene knowledge transfer has been proven effective to deal with the small-sample problem in hyperspectral image (HSI) classification. Currently, most of the existing works are based on the homogeneous settings where the source and target HSIs are observed from the same feature space, while the...

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Bibliographic Details
Main Authors: Chongxiao Zhong, Junping Zhang, Qingle Guo, Ye Zhang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Distribution alignment
domain adaptation
heterogeneous transfer learning
HSI classification
multiscale spectral-spatial features
structure preservation
Online Access:https://ieeexplore.ieee.org/document/9813390/

Internet

https://ieeexplore.ieee.org/document/9813390/

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