Hyperspectral Image Classification via JCR and SVM Models With Decision Fusion
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| Authors | Chunjuan Bo, Huchuan Lu, Dong Kai Wang |
| Journal/Conference Name | IEEE Geoscience and Remote Sensing Letters |
| Paper Category | ECE |
| Paper Abstract | In this letter, we propose a novel hyperspectral image (HSI) classification method based on the joint collaborative representation (JCR) and support vector machine (SVM) models with decision fusion. First, motivated by the joint model, we adopt a JCR model to deal with HSI classification and develop an effective method to learn contextual basis vectors for the JCR model. Second, the mid-features are first extracted based on representation coefficients obtained by the JCR method and then used to train a multiclass SVM classifier. After that, we exploit a multiplicative fusion rule to combine the JCR and SVM models. We conduct numerous experiments to evaluate our method in comparison with other algorithms. The experimental results on three standard data sets demonstrate that our method achieves better performance than other competing ones. |
| Date of publication | 2016 |
| Code Programming Language | MATLAB |
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