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Multimedia Systems

, Volume 22, Issue 3, pp 355–366 | Cite as

Spectral–spatial co-clustering of hyperspectral image data based on bipartite graph

  • Wei Liu
  • Shaozi Li
  • Xianming Lin
  • YunDong Wu
  • Rongrong JiEmail author
Regular Paper

Abstract

The high dimensionality of hyperspectral images are usually coupled with limited data available, which degenerates the performances of clustering techniques based only on pixel spectral. To improve the performances of clustering, incorporation of spectral and spatial is needed. As an attempt in this direction, in this paper, we propose an unsupervised co-clustering framework to address both the pixel spectral and spatial constraints, in which the relationship among pixels is formulated using an undirected bipartite graph. The optimal partitions are obtained by spectral clustering on the bipartite graph. Experiments on four hyperspectral data sets are performed to evaluate the effectiveness of the proposed framework. Results also show our method achieves similar or better performance when compared to the other clustering methods.

Keywords

Hyperspectral images Clustering Bipartite graph 

Notes

Acknowledgments

This work is supported by the Nature Science Foundation of China (No. 61373076) and National Outstanding Youth Science Foundation of China (No. 61422210).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Wei Liu
    • 1
  • Shaozi Li
    • 1
  • Xianming Lin
    • 1
  • YunDong Wu
    • 2
  • Rongrong Ji
    • 1
    Email author
  1. 1.Xiamen UniversityXiamenChina
  2. 2.Jimei UniversityXiamenChina

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