Relative Total Variation Structure Analysis-Based Fusion Method for Hyperspectral and LiDAR Data Classification

Relative Total Variation Structure Analysis-Based Fusion Method for Hyperspectral and LiDAR Data Classification

The fusion of the hyperspectral image (HSI) and the light detecting and ranging (LiDAR) data has a wide range of applications. This paper proposes a novel feature fusion method for urban area classification, namely the relative total variation structure analysis (RTVSA), to combine various features...

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Bibliographic Details
Main Authors: Yinghui Quan, Yingping Tong, Wei Feng, Gabriel Dauphin, Wenjiang Huang, Wentao Zhu, Mengdao Xing
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
feature fusion
total variation
feature extraction
classification
remote sensing
Online Access:https://www.mdpi.com/2072-4292/13/6/1143

Internet

https://www.mdpi.com/2072-4292/13/6/1143

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