Hyperspectral Image Classification via Spatial Window-Based Multiview Intact Feature Learning

Yue Zhao, Yiu Ming Cheung, Xinge You, Qinmu Peng*, Jiangtao Peng, Peipei Yuan, Yufeng Shi

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

7 Citations (Scopus)


Due to the high dimensionality of hyperspectral images (HSIs), more training samples are needed in general for better classification performance. However, surface materials cannot always provide sufficient training samples in practice. HSI classification with small size training samples is still a challenging problem. Multiview learning is a feasible way to improve the classification accuracy in the case of small training samples by combining information from different views. This article proposes a new spatial window-based multiview intact feature learning method (SWMIFL) for HSI classification. In the proposed SWMIFL, multiple features that reflect different information of the original image are extracted and spatial windows are imposed on training samples to select unlabeled samples. Then, multiview intact feature learning is performed to learn the intact feature of the training and unlabeled samples. Considering that neighboring samples are likely to belong to the same class, labels of spatial neighboring samples are determined by two factors including the labels of training samples that locate in the spatial window and the labels learned from the intact feature. Finally, unlabeled samples that have same labels under these two factors are treated as new training samples. Experimental results demonstrate that the proposed SWMIFL-based classification method outperforms several well-known HSI classification methods on three real-world data sets.

Original languageEnglish
Pages (from-to)2294-2306
Number of pages13
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number3
Early online date15 Jul 2020
Publication statusPublished - Mar 2021

Scopus Subject Areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

User-Defined Keywords

  • Hyperspectral image (HSI) classification
  • multiview intact feature learning
  • small size training samples
  • spatial window


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