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An Enhanced Semi-Supervised Support Vector Machine Algorithm for Spectral-Spatial Hyperspectral Image Classification

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Abstract

Hyperspectral image classification has become an important issue in remote sensing due to the significant amount of spectral information in HSI. The costly and time-consuming annotation task of HSIs makes the number of labeled samples is limited. To address the above problem, we propose an enhanced semi-supervised support vector machine algorithm for spectral-spatial HSI classification. To fully capture the spectral and spatial information of HSI, we use local binary pattern to obtain spatial feature. The captured spatial features are concatenated with the spectral features to yield the hybrid spectral-spatial features. Self-training mechanism is then adopted to gradually select confident unlabeled samples with their pseudo-labels and add them to the labeled set. To further improve the classification performance of the semi-supervised support vector machine, we choose a cuckoo search algorithm based on the chaotic catfish effect to find its optimal combination of parameters. The experimental results on two publicly available HSI datasets show that the proposed model achieves excellent classification accuracy for each category in hyperspectral images, and also has superior overall accuracy compared with other comparative algorithms. Adequate experiments and analysis illustrate the promising potential and prospect of our proposed model for HSI classification.

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Funding

This research was funded by the National Natural Science Foundation of China (nos. U1813222, 42075129); Hebei Province Natural Science Foundation (no. E2021202179), Key Research and Development Project from Hebei Province (nos. 19210404D, 20351802D, 21351803D).

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Authors and Affiliations

  1. School of Computer and Communication Engineering, Changsha University of Science and Technology, 410114, Changsha, China

    Ziping He, Kewen Xia, Jiangnan Zhang, Sijie Wang & Zhixian Yin

  2. School of Electronics and Information Engineering, Hebei University of Technology, 300401, Tianjin, China

    Ziping He

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Correspondence to Ziping He, Kewen Xia, Jiangnan Zhang, Sijie Wang or Zhixian Yin.

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Additional information

Ziping He received a PhD degree from the School of Electronics and Information Engineering at Hebei University of Technology, Tianjin, China in 2023. She is currently a lecturer at School of Computer and Communication Engineering in Changsha University of Science and Technology. From October 2021 to November 2022, she is a visiting PhD student with the machine learning group at Helmholtz–Zentrum and Dresden–Rossendorf (HZDR), Germany, supported by the China Scholarship Council. Her research interests include semi-supervised learning, machine learning, deep learning, and hyperspectral image processing.

Kewen Xia received the PhD degree in Electronics from Xi’an Jiaotong University (XJTU), China in 2003. His postdoctoral research was finished in Computer Department of XJTU in 2006. From 2010 to 2011, he worked as a research scholar of Electronics in University of Illinois at Urbana-Champaign, United States Now he is a professor and PhD candidate supervisor with the School of Electronics and Information Engineering, Hebei University of Technology, China. His research interests cover computational intelligence and wireless communication technology.

Jiangnan Zhang received BEng degree in College of Information Science and Engineering from Shanxi Agricultural University, Shanxi, China in 2017. She is now a Doctoral student in Hebei University of Technology, Tianjin, China. Her research interests are image processing, data mining, and communication technology.

Sijie Wang received BSc degree in school of electronic and information engineering from city collage of Hebei University of Technology, Tianjin, China in 2016. Now she is a doctoral student in Hebei University of Technology, Tianjin, China. Her research interests include image processing and data mining.

Zhixian Yin received his BSc degree in Tangshan University, Tangshan, China in 2012. He received MSc Degree in School of Information Science and Technology from Shijiazhuang Tiedao University, Shijiazhuang, China in 2018. He is now a Doctoral student in Hebei University of Technology, Tianjin, China. His research includes image processing and intelligent information processing.

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Ziping He, Xia, K., Zhang, J. et al. An Enhanced Semi-Supervised Support Vector Machine Algorithm for Spectral-Spatial Hyperspectral Image Classification. Pattern Recognit. Image Anal. 34, 199–211 (2024). https://doi.org/10.1134/S1054661824010085

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