A Comparative Review of Manifold Learning Techniques for Hyperspectral and Polarimetric SAR Image Fusion

A Comparative Review of Manifold Learning Techniques for Hyperspectral and Polarimetric SAR Image Fusion

In remote sensing, hyperspectral and polarimetric synthetic aperture radar (PolSAR) images are the two most versatile data sources for a wide range of applications such as land use land cover classification. However, the fusion of these two data sources receive less attention than many other, becaus...

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Bibliographic Details
Main Authors: Jingliang Hu, Danfeng Hong, Yuanyuan Wang, Xiao Xiang Zhu
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Remote Sensing
Subjects:
data fusion
generalized graph fusion
hyperspectral image
data alignment
locality preserving projections
manifold alignment
manifold learning
MAPPER-induced manifold alignment
polarimetric SAR
MIMA
Online Access:https://www.mdpi.com/2072-4292/11/6/681

Internet

https://www.mdpi.com/2072-4292/11/6/681

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