Hyperspectral Classification via Superpixel Kernel Learning-Based Low Rank Representation

Hyperspectral Classification via Superpixel Kernel Learning-Based Low Rank Representation

High dimensional image classification is a fundamental technique for information retrieval from hyperspectral remote sensing data. However, data quality is readily affected by the atmosphere and noise in the imaging process, which makes it difficult to achieve good classification performance. In thi...

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Bibliographic Details
Main Authors: Tianming Zhan, Le Sun, Yang Xu, Guowei Yang, Yan Zhang, Zebin Wu
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Remote Sensing
Subjects:
hyperspectral image
classification
superpixel kernel
multiple kernel learning
low rank representation
Online Access:http://www.mdpi.com/2072-4292/10/10/1639

Internet

http://www.mdpi.com/2072-4292/10/10/1639

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