A spatial data model for remote sensing image retrieval
2013 21st Signal Processing and Communications Applications Conference, SIU 2013
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Given a query region, our aim is to discover and retrieve regions with similar spatial arrangement and characteristics in other areas of the same large image or in other images. A Markov random field is constructed by representing regions as variables and connecting the vertices that are spatially close by edges. Then, a maximum entropy distribution is assumed over the query region process and retrieval of the similar region processes on the target image is achieved according to their probability. Experiments using WorldView-2 images show that statistical modelling of compound structures enable high-level and large-scale retrieval applications. © 2013 IEEE.
Markov random field
Markov Random Fields
Maximum entropy distribution
Remote sensing image retrieval
Spatial data model
Published Version (Please cite this version)http://dx.doi.org/10.1109/SIU.2013.6531469
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