Abstract
Mathematical morphology has shown to be an effective tool to extract spatial information for remote-sensing image classification. Its application is performed by means of a structuring element (SE), whose shape and size play a fundamental role for appropriately extracting structures in complex regions such as urban areas. In this letter, we propose a novel method, which automatically tailors both the shape and the size of the SE according to the considered classification task. For this purpose, the SE design is formulated as an optimization problem within a particle swarm optimization framework. The experiments conducted on two real images suggest that better accuracies can be achieved with respect to the common procedure for finding the best regular SE, which, so far, is heuristically done.