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

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Wang, X. P.^1¹ 

[1] Chongqing Geomatics Center, Chongqing, 401121, China^1

关键词: Graph;    Label Propagation;    Semi-Supervised method;    Classification;    Hyperspectral Remote Sensing;   

DOI  :  10.5194/isprs-archives-XLII-3-1795-2018

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

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.

【 授权许可】

CC BY