Noise reduction and feature extraction based on low-rank representation and pairwise constraint preserving for hyperspectral images
Author:
Affiliation:
1. Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1607980
Reference60 articles.
1. Semisupervised dimensionality reduction for hyperspectral images based on the combination of semisupervised learning and metric learning
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3. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
4. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
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