A new comprehensive approach for earth observation scene classification using joint image and text analysis

The amount of data available on the internet provides massive additional information for the Earth Observation (EO) imagery. Periodical news, various reports and measurements, pictures or online encyclopedias are just few examples of the existent information. Occasionally, this data offers new perspectives for EO image understanding and interpretation. However, current image analysis do not benefit from the advantage given by external sources. To overcome these drawbacks, the present paper proposes an approach that goes beyond traditional information mining by using a joint image and text analysis. Fast Compression Distance (FCD) is computed to measure the similarities inside a collection of very high resolution images and text files. The main purpose is to discover common patterns within the data, without any a priori assumption, parameter-free, relying on data compression-based techniques. A hierarchical clustering is performed in order to learn about the dependencies between different types of data.