Detection of compound structures using multiple hierarchical segmentations

Date
2014
Advisor
Instructor
Source Title
2014 22nd Signal Processing and Communications Applications Conference (SIU)
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
2062 - 2065
Language
Turkish
Type
Conference Paper
Journal Title
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Volume Title
Abstract

In this paper, we present a method for automatic compound structure detection in high-resolution images. Given a query compound structure, our aim is to detect coherent regions with similar spatial arrangement and characteristics in multiple hierarchical segmentations. A Markov random field is constructed by representing query 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 selection of similar region processes among a set of region hierarchies is achieved by maximizing the query model. Experiments using WorldView-2 images show the efficiency of probabilistic modeling of compound structures. © 2014 IEEE.

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Keywords
Markov processes, Signal processing, Compound structures, Context modeling, Hierarchical segmentation, High resolution image, Markov Random Fields, Maximum entropy distribution, Probabilistic modeling, Spatial arrangements, Query processing
Citation
Published Version (Please cite this version)