HYPERSPECTRAL IMAGE SEGMENTATION WITH LOW-RANK REPRESENTATION AND SPECTRAL CLUSTERING

被引：0

作者：

Sumarsono, Alex ^{[1
]}

Du, Qian ^{[1
]}

Younan, Nicolas ^{[1
]}

机构：

[1] Mississippi State Univ, Dept Elect & Comp Engn, Mississippi State, MS 39762 USA

来源：

2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS) | 2015年

关键词：

Low-rank representation; low-rank subspace representation; spectral clustering; majority voting; image segmentation; hyperspectral imagery;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Hyperspectral image segmentation is considered in this paper. A low-rank representation method is applied first to extract major data information, followed by a spectral clustering method based on data graph. Segmentation accuracy can be further improved by a post-processing step using non-local majority voting. Experimental results demonstrate that the proposed method can improve segmentation accuracy for complicated image scenes.

引用

页数：4

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