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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 11
3496-3498

Subspace clustering algorithm fused three-dimensional spatial spectral features of hyperspectral images

Li Wenzhoua
Deng Xiuqina
Liu Fuchunb
a. School of Applied Mathematics, b. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2018.07.0482

Abstract

In order to improve the clustering accuracy of hyperspectral images, this paper proposed a new sparse subspace clustering model combined three-dimensional spatial spectral features with subspace clustering algorithms. While focusing on the spectral information of hyperspectral images, it also paid attention to spatial context information. Firstly, the model extracted three kinds of three-dimensional spatial spectral features from the pixels of the hyperspectral image. Then it used features to weight the coefficient matrix of the subspace clustering model so that the pixel points could sparsely represent the pixel point which they were most similar, thereby it obtained the better coefficient matrix. Finally, it used the coefficient matrix to obtain better clustering results with spectral clustering. This paper experimented the algorithm on four classical hyperspectral datasets, and compared the experimental results with six clustering algorithms. The results show that the proposed algorithm achieves higher clustering accuracy on the four datasets than the other algorithms. The algorithm can achieve at most 8.62% accuracy than the algorithms based on 3D spatial spectral features like M3DF3 and 3DF-SSC algorithm, and at most 25.18% than the algorithms which improves the subspace clustering algorithm by using spatial context information like L2-SSC and SS-LRSC algorithm.

Foundation Support

国家自然科学基金资助项目(61673122)
广东省公益研究与能力建设专项资金资助项目(2015A030402006)
广东工业大学研究生创新及竞赛项目(2017YJSCX039)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0482
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 11
Section: Technology of Graphic & Image
Pages: 3496-3498
Serial Number: 1001-3695(2019)11-067-3496-03

Publish History

[2019-11-05] Printed Article

Cite This Article

李文洲, 邓秀勤, 刘富春. 融合高光谱影像三维空谱特征的子空间聚类算法 [J]. 计算机应用研究, 2019, 36 (11): 3496-3498. (Li Wenzhou, Deng Xiuqin, Liu Fuchun. Subspace clustering algorithm fused three-dimensional spatial spectral features of hyperspectral images [J]. Application Research of Computers, 2019, 36 (11): 3496-3498. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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