Label propagation–based semi-supervised classification for hyperspectral imagery

2014 ◽  
Author(s):  
Siyuan Hao ◽  
Liguo Wang
Keyword(s):  
Supervised Classification ◽  
Hyperspectral Imagery ◽  
Label Propagation

scholarly journals Kernel-Induced Label Propagation by Mapping for Semi-Supervised Classification

2019 ◽  
Vol 5 (2) ◽  
pp. 148-165 ◽  
Author(s):  
Zhao Zhang ◽  
Lei Jia ◽  
Mingbo Zhao ◽  
Guangcan Liu ◽  
Meng Wang ◽  
...  
Keyword(s):  
Supervised Classification ◽  
Label Propagation

scholarly journals Semi-Supervised Classification of Hyperspectral Images Based on Extended Label Propagation and Rolling Guidance Filtering

2018 ◽  
Vol 10 (4) ◽  
pp. 515 ◽  
Author(s):  
Binge Cui ◽  
Xiaoyun Xie ◽  
Siyuan Hao ◽  
Jiandi Cui ◽  
Yan Lu
Keyword(s):  
Supervised Classification ◽  
Label Propagation ◽  
Hyperspectral Images

scholarly journals COUPLE GRAPH BASED LABEL PROPAGATION METHOD FOR HYPERSPECTRAL REMOTE SENSING DATA CLASSIFICATION

2018 ◽  
Vol XLII-3 ◽  
pp. 1795-1798
Author(s):  
X. P. Wang ◽  
Y. Hu ◽  
J. Chen
Keyword(s):  
Manifold Learning ◽  
Classification Accuracy ◽  
Supervised Classification ◽  
Hyperspectral Image ◽  
Remote Sensing Data ◽  
Graph Laplacian ◽  
Hyperspectral Data ◽  
Label Propagation ◽  
Hyperspectral Image Classification ◽  
Adjacency Graph

Graph based semi-supervised classification method are widely used for hyperspectral image classification. We present a couple graph based label propagation method, which contains both the adjacency graph and the similar graph. We propose to construct the similar graph by using the similar probability, which utilize the label similarity among examples probably. The adjacency graph was utilized by a common manifold learning method, which has effective improve the classification accuracy of hyperspectral data. The experiments indicate that the couple graph Laplacian which unite both the adjacency graph and the similar graph, produce superior classification results than other manifold Learning based graph Laplacian and Sparse representation based graph Laplacian in label propagation framework.

Sign in / Sign up

Export Citation Format

Share Document