Semisupervised Hyperspectral Image Classification via Superpixel-Based Graph Regularization With Local and Nonlocal Features

Semisupervised Hyperspectral Image Classification via Superpixel-Based Graph Regularization With Local and Nonlocal Features

Although a graph-based semisupervised learning (SSL) approach can utilize limited numbers of labeled samples for hyperspectral image (HSI) classification, it is difficult to use the large amount of pixels in an HSI to construct a large-scale graph. In this article, we therefore propose a superpixel-...

Full description

Bibliographic Details
Main Authors: Longshan Yang, Junhuan Peng, Yuebin Wang, Linlin Xu, Weiwei Zhu
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Anchor graph
feature-extraction
hyperspectral image
semisupervised classification
superpixel
Online Access:https://ieeexplore.ieee.org/document/9832660/

Internet

https://ieeexplore.ieee.org/document/9832660/

Similar Items