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Semantic Strategic Satellite Image Retrieval

Large amounts of spatial data are becoming available today due to the rapid development of remote sensing techniques. Several retrieval systems are proposed to retrieve necessary, interested and effective information such as key-word based image retrieval and content based image retrieval. However, the results of these approaches are generally unsatisfactory, unpredictable and don't match human perception due to the well gap between visual features and semantic concepts [1]. In this paper, we propose a new approach allowing semantic satellite image retrieval, describing the semantic image content and managing uncertain information. It's based on ontology model which represents spatial knowledge in order to provide semantic understanding of image content. Our retrieval system is based on two modules: ontological model merging and semantic strategic image retrieval. The first module allows developing ontological models which represent spatial knowledge of the satellite image, and managing uncertain information. The second module allows retrieving satellite images basing on their ontological model. In order to improve the quality of retrieval system and to facilitate the retrieval process, we propose two retrieval strategies which are the opportunist strategy and the hypothetic strategy. Our approach attempts to improve the quality of image retrieval, to reduce the semantic gap between visual features and semantic concepts and to provide an automatic solution for efficient satellite image retrieval.