Title :
Detection of compound structures using multiple hierarchical segmentations
Author :
Akcay, H.G. ; Aksoy, Selim
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Bilkent Univ., Ankara, Turkey
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.
Keywords :
Markov processes; geophysical image processing; image representation; image resolution; image segmentation; maximum entropy methods; probability; random processes; Markov random field; WorldView-2 imaging; automatic compound structure detection; coherent region detection; high-resolution imaging; maximum entropy distribution; multiple hierarchical segmentation; probabilistic modeling; query compound structure; query region representation; Compounds; Conferences; Geoscience and remote sensing; Image segmentation; Joining processes; Markov processes; Signal processing; Compound structure detection; Markov random field; context modeling; spatial arrangements;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
DOI :
10.1109/SIU.2014.6830666
