Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 4
1239-1245,1262

Locality sensitive discriminative broad learning system for hyperspectral image classification

Cao Helinga,b,c
Song Changlonga
Chu Yonghea
a. School of Information Science & Engineering, b. Henan International Joint Laboratory of Grain Information Processing, c. Key Laboratory of Grain Information Processing & Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
DOI: 10.19734/j.issn.1001-3695.2022.07.0391

Abstract

Recently, BLS has been widely used in HSI classification with its excellent learning performance and generalization ability. However, BLS only focuses on the separability of various samples, ignoring the relative relationship between samples and the discriminative information. To some extent, it limits the performance of BLS. Therefore, this paper proposed a local sensitive discriminative broad learning system(LSDBLS) method. LSDBLS considered the discriminative information of labeled samples and the local manifold structure of data samples by introducing local sensitive discriminant analysis, and constructed intra-class and inter-class graphs by labeled samples to representation the relative relationship between data samples. On this basis, it introduced the intra-class graph and the inter-class graph into the objective function of the broad learning system. By minimizing the intra-class graph and maximizing the inter-class graph, it aggregated the samples of the same class as much as possible, and the samples of different classes were as much as possible, so as to enhance the discriminative ability of LSDBLS for data features. Experimental results on three HSI datasets show that LSDBLS achieves good performance.

Foundation Support

国家自然科学基金资助项目(6220071360,61602154)
河南省高等学校重点科研项目(22A520024)
河南工业大学青年骨干教师培育项目
河南省重大公益专项(201300311200)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.07.0391
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 4
Section: Technology of Graphic & Image
Pages: 1239-1245,1262
Serial Number: 1001-3695(2023)04-045-1239-07

Publish History

[2022-10-19] Accepted Paper
[2023-04-05] Printed Article

Cite This Article

曹鹤玲, 宋昌隆, 楚永贺. 基于局部敏感判别宽度学习的高光谱图像分类 [J]. 计算机应用研究, 2023, 40 (4): 1239-1245,1262. (Cao Heling, Song Changlong, Chu Yonghe. Locality sensitive discriminative broad learning system for hyperspectral image classification [J]. Application Research of Computers, 2023, 40 (4): 1239-1245,1262. )

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.

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