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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 8
2526-2529

3D-deep capsule network classification for fused hyperspectral and LiDAR data

Zhang Xiongshan1a,1b,2a,2b
Zhao Genping1a,1b,2a,2b
Cheng Lianglun1a,1b
1. a. School of Computers, b. Guangdong Provincial Key Laboratory of Cyber-Physical System, Guangdong University of Technology, Guangzhou 510006, China
2. a. Key Laboratory of Beibu Gulf Environment Change & Resource Use of Ministry of Education, b. Guangxi Key Laboratory of Earth Surface Processes & Intelligent Simulation, Nanning Normal University, Nanning 530001, China
DOI: 10.19734/j.issn.1001-3695.2020.09.0398

Abstract

As the advantages of both hyperspectral and LiDAR imaging, this paper explored the two source remote sensing data for classification of a urban area by deploying a 3D-deep capsule network(3D-DCN). 3D-DCN used a two-layer 3D-CNN structure at the beginning to realize non-linear feature mapping for the fused data. And it followed a capsule network to gene-rate vectors to represent features and realize encapsulation, convolution and classification. In addition, this paper proposed a nonlinear activation function named e-squash function to be used in the capsule convolution layer. The classification experiments on the urban datasets show that the LiDAR data can improve greatly the hyperspectral image classification result and the 3D-DCN with proposed activation function is of more potential than the state-in-art methods in the classification of the urban data.

Foundation Support

国家自然科学基金资助项目(61701123)
国家高分地球观测主要项目(83-Y40G33-9001-18/20)
广东省信息物理融合重点实验室项目(2016B030301008)
广东省农业科学与技术创新团队项目(2019KJ147)
广东省科技计划资助项目(2016B010127005)
广西北部湾环境演变与资源利用教育部重点实验室(南宁师范大学)和广西地表过程与智能模拟重点实验室(南宁师范大学)开放或系统基金资助项目(NNNU-KLOP-K1936)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.09.0398
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 8
Section: Technology of Graphic & Image
Pages: 2526-2529
Serial Number: 1001-3695(2021)08-052-2526-04

Publish History

[2021-08-05] Printed Article

Cite This Article

张雄山, 赵艮平, 程良伦. 基于3D深度胶囊网络的高光谱和LiDAR数据融合分类 [J]. 计算机应用研究, 2021, 38 (8): 2526-2529. (Zhang Xiongshan, Zhao Genping, Cheng Lianglun. 3D-deep capsule network classification for fused hyperspectral and LiDAR data [J]. Application Research of Computers, 2021, 38 (8): 2526-2529. )

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  • 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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