Multi-feature adaptive classifiers for SAR image segmentation

We propose a multifeature scheme for terrain classification in SAR image analysis. Different neural classifiers, trained on different features of the same sample space, are combined by using a non-linear ensemble method. The feature extraction modules are chosen in order to discover the textural and contextual characteristics within the neighbourhood of each pixel. Comparisons with classical data fusion techniques and consensus schema are reported. We propose a multifeature scheme for terrain classification in SAR image analysis. Different neural classifiers, trained on different features of the same sample space, are combined by using a non-linear ensemble method. The feature extraction modules are chosen in order to discover the textural and contextual characteristics within the neighbourhood of each pixel. Comparisons with classical data fusion techniques and consensus schema are reported.