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Fusion of Multidimensional CNN and Handcrafted Features for Small-Sample Hyperspectral Image Classification
| Content Provider | MDPI |
|---|---|
| Author | Tang, Haojin Li, Yanshan Huang, Zhiquan Zhang, Li Xie, Weixin |
| Copyright Year | 2022 |
| Description | Hyperspectral image (HSI) classification has attracted widespread concern in recent years. However, due to the complexity of the HSI gathering environment, it is difficult to obtain a great number of HSI labeled samples. Therefore, how to effectively extract the spatial–spectral feature with small-scale training samples is the crucial point of HSI classification. In this paper, a novel fusion framework for small-sample HSI classification is proposed to fully combine the advantages of multidimensional CNN and handcrafted features. Firstly, a 3D fuzzy histogram of oriented gradients (3D-FHOG) descriptor is proposed to fully extract the handcrafted spatial–spectral feature of HSI pixels, which is suggested to be more robust by overcoming the local spatial–spectral feature uncertainty. Secondly, a multidimensional Siamese network (MDSN), which is updated by minimizing both contrastive loss and classification loss, is designed to effectively exploit the CNN-based spatial–spectral features from multiple dimensions. Finally, the proposed MDSN combined with 3D-FHOG is utilized for small-sample HSI classification to verify the effectiveness of our proposed fusion framework. The experimental results on three public data sets indicate that the proposed MDSN combined with 3D-FHOG is significantly better than the representative handcrafted feature-based and CNN-based methods, which in turn demonstrates the superiority of the proposed fusion framework. |
| Starting Page | 3796 |
| e-ISSN | 20724292 |
| DOI | 10.3390/rs14153796 |
| Journal | Remote Sensing |
| Issue Number | 15 |
| Volume Number | 14 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-08-06 |
| Access Restriction | Open |
| Subject Keyword | Remote Sensing Imaging Science Small-sample Hyperspectral Image Classification Spatial–spectral Feature Extraction Multidimensional Cnn Handcrafted Feature |
| Content Type | Text |
| Resource Type | Article |
