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The paper presents an information theory approach for change detection, using Earth observation images. Correlation coefficient and Kullback-Leibler divergence are used as similarity measures allowing to find out where did change occur. Further, for an image characterization method, rate distortion theory is implemented to delimitate image complex regions,(More)
In natural hazards management applications Earth Observation (EO) image processing methods are based on segmentation and classification. The result primary consists of thematic maps which are readily interpretable. We propose a complete EO image processing chain, which generates an end product with increased information content organized in thematic layers.(More)
In this paper we present the result of data analytics techniques applied to a database comprising of 32 SLC SM TerraSAR-X images, acquired over the area of Bucharest, Romania. The methodology follows a two step approach. The first stage consists of a coarse identification of potentially changed areas using a supervised learning image annotation tool with(More)
Base Image Retrieval approach. The results include detailed semantic categories for rapid mapping. Each data mining scenario includes three stages: Data Annotations, Data Query and Quantitative analysis of the results. In the end, based on query results, a semantic map of affected regions can be developed. In addition to the traditional approach the(More)
Natural hazards such as floods, avalanches, volcanic eruptions or earthquakes inflict losses to human settlements and manmade infrastructure and have negative impact on the local economy and environment. The growing number of satellite missions and space services facilitates the access to information for researches and decision makers. Space imagery offers(More)