Akçay, Hüseyin GökhanAksoy, Selim2016-02-082016-02-082014http://hdl.handle.net/11693/27119Date of Conference: 23-25 April 2014In 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.TurkishMarkov processesSignal processingCompound structuresContext modelingHierarchical segmentationHigh resolution imageMarkov Random FieldsMaximum entropy distributionProbabilistic modelingSpatial arrangementsQuery processingConference Paper10.1109/SIU.2014.6830666