Detection of compound structures using multiple hierarchical segmentations
Author
Akçay, Hüseyin Gökhan
Aksoy, Selim
Date
2014Source Title
2014 22nd Signal Processing and Communications Applications Conference (SIU)
Publisher
IEEE
Pages
2062 - 2065
Language
Turkish
Type
Conference PaperItem Usage Stats
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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.
Keywords
Markov processesSignal processing
Compound structures
Context modeling
Hierarchical segmentation
High resolution image
Markov Random Fields
Maximum entropy distribution
Probabilistic modeling
Spatial arrangements
Query processing