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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 2
573-577

Real-time classification algorithm of remote sensing images based on ant colony optimization algorithm and independent feature sets

Zhao Fang1
Suo Yan2
Peng Ziran3
1. Computer & Information Engineering College, Xinxiang University, Xinxiang Henan 453003, China
2. Xinlian College of Henan Normal University, Xinxiang Henan 453000, China
3. School of Information Science & Engineering, Central South University, Changsha 410083, China
DOI: 10.19734/j.issn.1001-3695.2018.06.0574

Abstract

In order to improve the accuracy and efficiency of real-time classification of remote sensing images, this paper proposed a real-time classification algorithm of remote sensing images based on the ant colony optimization algorithm and independent feature sets. Firstly, it abstracted wavelet features and color features of remote sensing images, and the features formed the feature vectors. Then, it adopted the ant colony optimization algorithm to optimize the feature space, and it selected the significant feature set of each class independently to reduce the dimension of each feature sub-space. Lastly, it trained extreme learning machine for each class independently to realize the remote sensing images classification. Simulation experimental results based on the public remote sensing image dataset show that the proposed algorithm realizes a good classification accuracy and computational efficiency.

Foundation Support

国家自然科学基金资助项目(61272121)
河南省科技攻关计划项目(172102210445)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.06.0574
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Technology of Graphic & Image
Pages: 573-577
Serial Number: 1001-3695(2020)02-057-0573-05

Publish History

[2020-02-05] Printed Article

Cite This Article

赵芳, 索岩, 彭子然. 基于蚁群优化与独立特征集的遥感图像实时分类算法 [J]. 计算机应用研究, 2020, 37 (2): 573-577. (Zhao Fang, Suo Yan, Peng Ziran. Real-time classification algorithm of remote sensing images based on ant colony optimization algorithm and independent feature sets [J]. Application Research of Computers, 2020, 37 (2): 573-577. )

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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