A spatial data model for remote sensing image retrieval

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A spatial data model for remote sensing image retrieval [Uzaktan algilama görüntülerinde erişim için uzamsal bir veri modeli].pdf (13.86 MB)

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2013

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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.

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2013 21st Signal Processing and Communications Applications Conference, SIU 2013

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IEEE

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Keywords

Image retrieval, Markov 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

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http://hdl.handle.net/11693/27995

Published Version (Please cite this version)

http://dx.doi.org/10.1109/SIU.2013.6531469

Collections

Scholarly Publications - Computer Engineering

Language

Turkish

Type

Conference Paper