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Fusion of PolSAR and PolInSAR data for land cover classification |
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| Authors: | M. Shimoni D. Borghys R. Heremans C. Perneel M. Acheroy |
| Affiliation: | 1. Signal and Image Centre, Electrical Engineering Department of the Belgian Royal Military Academy, Brussels, 30, Ave de la Renaissance, Belgium;2. Mathematical Department of the Belgian Royal Military Academy, Brussels, 30, Ave de la Renaissance, Belgium;3. Computer, Informatics, System and Sensor Department of the Royal Military Academy, Brussels, 30, Ave de la Renaissance, Belgium |
| Abstract: | The main research goal of this study is to investigate the complementarity and fusion of different frequencies (L- and P-band), polarimetric SAR (PolSAR) and polarimetric interferometric (PolInSAR) data for land cover classification. A large feature set was derived from each of these four modalities and a two-level fusion method was developed: Logistic regression (LR) as ‘feature-level fusion’ and the neural-network (NN) method for higher level fusion. For comparison, a support vector machine (SVM) was also applied. NN and SVM were applied on various combinations of the feature sets. |
| Keywords: | PolSAR PolInSAR Fusion Neural network architecture Land cover classification Feature extraction |
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