A Novel Tri-Training Technique for the Semi-Supervised Classification of Hyperspectral Images Based on Regularized Local Discriminant Embedding Feature Extraction

A Novel Tri-Training Technique for the Semi-Supervised Classification of Hyperspectral Images Based on Regularized Local Discriminant Embedding Feature Extraction

This paper introduces a novel semi-supervised tri-training classification algorithm based on regularized local discriminant embedding (RLDE) for hyperspectral imagery. In this algorithm, the RLDE method is used for optimal feature information extraction, to solve the problems of singular values and...

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Bibliographic Details
Main Authors: Depin Ou, Kun Tan, Qian Du, Jishuai Zhu, Xue Wang, Yu Chen
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Remote Sensing
Subjects:
feature extraction
regularized local discriminant embedding (RLDE)
semi-supervised tri-training
hyperspectral imagery
Online Access:http://www.mdpi.com/2072-4292/11/6/654

Internet

http://www.mdpi.com/2072-4292/11/6/654

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