A spatial data model for remote sensing image retrieval
Signal Processing and Communications Applications Conference（2013）
摘要
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.
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关键词
Markov processes,geophysical image processing,image representation,image retrieval,remote sensing,statistical analysis,Markov random field,WorldView-2 images,compound structure statistical modelling,high-level retrieval applications,large-scale retrieval applications,maximum entropy distribution,query region process,region representation,remote sensing image retrieval,spatial data model,Image retrieval,Markov random field,spatial arrangements
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