Texture fusion and feature selection applied to SAR imagery

The discrimination ability of four different methods for texture computation in ERS SAR imagery is examined and compared. Feature selection methodology and discriminant analysis are applied to find the optimal combination of texture features. By combining features derived from different texture models, the classification accuracy increased significantly.