Title :
A spatial data model for remote sensing image retrieval
Author :
Akcay, H.G. ; Aksoy, Selim
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Bilkent Univ., Ankara, Turkey
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.
Keywords :
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; Compounds; Data models; Image retrieval; Markov processes; Remote sensing; Spatial databases; Image retrieval; Markov random field; spatial arrangements;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2013 21st
Conference_Location :
Haspolat
Print_ISBN :
978-1-4673-5562-9
Electronic_ISBN :
978-1-4673-5561-2
DOI :
10.1109/SIU.2013.6531469
