Probabilistic class structure regularized sparse representation graph for semi-supervised hyperspectral image classification

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• 作者：Yuanjie Shao^a ; ^{shaoyuanjie1@gmail.com}Author Vitae ; Nong Sang^a ; ^{nsang@hust.edu.cn}Author Vitae ; Changxin Gao^a ; ^{cgao@hust.edu.cn}Author Vitae ; Li Ma^b ; ^{maryparisster@gmail.com}Author Vitae
• 关键词：Graph ; Probabilistic class structure ; Sparse representation (SR) ; Semi-supervised learning (SSL) ; Hyperspectral image (HSI) classification
• 刊名：Pattern Recognition
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：63
• 期：Complete
• 页码：102-114
• 全文大小：1479 K
• 卷排序：63

文摘

An effective method is introduced to estimate the probabilistic class structure Sparse representation based edge weighting method is employed in the graph based SSL. Probabilistic class structure information is incorporated into the Sparse representation model. The proposed graph construction method is superior to several traditional methods.