A spatial data model for remote sensing image retrieval
Date
2013
Authors
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
2013 21st Signal Processing and Communications Applications Conference, SIU 2013
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
Language
Turkish
Type
Journal Title
Journal ISSN
Volume Title
Series
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.
Course
Other identifiers
Book Title
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