Graph of Visual Words for Semantic Annotation of Remote Sensing Images

Nowadays semantic image annotation is becoming more than ever a very challenging issue since it helps improving image interpretation and retrieval. Currently, most semantic annotation methods represent images as lists of keywords or histogram of visual words, and do not consider the spatial distribution of regions, nor any prior knowledge concerning objects in a scene. This obviously leads to weak and limited representation of image content. In this paper, we propose a new method for semantic image annotation that simultaneously handles all the available information of the image (contextual, spatial, and spectral). We use a remote sensing ontology as semantic resource and develop an annotation process producing a graph representing objects of a scene as well as their spatial relations.