Robust Autodual Morphological Profiles for the Classification of High-Resolution Satellite Images

Morphological profiles are widely used for the classification of high-resolution remote sensing images. Images are degraded by morphological operators with different sizes. Profiles, such as the variation of intensities of the pixels, are extracted during the degradation. In this paper, two issues with morphological profiles are addressed. First, we propose using the topographic map of the image, which is autodual and does not require any structural element, for the degradation of the image. Second, we propose extracting other profiles that are more robust than the intensity variations. Classification experiments are carried out on two IKONOS remote sensing images with a 1-m resolution and one Pléiades 1-A image with a 2-m resolution. The efficiencies of the new profiles are validated by the experimental results.