Very-High Resolution Image Classification using Morphological Operators and SVM

An extensive analysis based on the use of different morphological filters for the classification of very-high resolution panchromatic images is presented. Feature selection on high-dimensional input space is performed using recursive feature elimination, a support vector machines specific method performing backward elimination based on margin-estimation criterion. Experimental results on an eight-classes image of Las Vegas (USA) confirmed the effectiveness of the analysis pointing out the relevancy of the most contributing morphological features which resulted in high classification accuracy using panchromatic imagery.