A spatial data model for remote sensing image retrieval
Author
Akçay, H. Gökhan
Aksoy, Selim
Date
2013Source Title
2013 21st Signal Processing and Communications Applications Conference, SIU 2013
Publisher
IEEE
Language
Turkish
Type
Conference PaperItem Usage Stats
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Abstract
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.
Keywords
Image retrievalMarkov random field
Spatial arrangements
Compound structures
Markov Random Fields
Maximum entropy distribution
Remote sensing image retrieval
Retrieval applications
Spatial arrangements
Spatial data model
Statistical modelling
Markov processes
Probability distributions
Signal processing
Image retrieval
Permalink
http://hdl.handle.net/11693/27995Published Version (Please cite this version)
http://dx.doi.org/10.1109/SIU.2013.6531469Collections
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