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      • Department of Computer Engineering
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      Detection of compound structures using hierarchical clustering of statistical and structural features

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      Author
      Akçay, H. Gokhan
      Aksoy, Selim
      Date
      2011
      Source Title
      2011 IEEE International Geoscience and Remote Sensing Symposium
      Publisher
      IEEE
      Pages
      2385 - 2388
      Language
      English
      Type
      Conference Paper
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      Abstract
      We describe a new procedure that combines statistical and structural characteristics of simple primitive objects to discover compound structures in images. The statistical information that is modeled using spectral, shape, and position data of individual objects, and structural information that is modeled in terms of spatial alignments of neighboring object groups are encoded in a graph structure that contains the primitive objects at its vertices, and the edges connect the potentially related objects. Experiments using WorldView-2 data show that hierarchical clustering of these vertices can find high-level compound structures that cannot be obtained using traditional techniques. © 2011 IEEE.
      Keywords
      alignment detection
      graph-based representation
      hierarchical clustering
      Object detection
      Compound structures
      Graph structures
      Graph-based representations
      Hier-archical clustering
      Individual objects
      Object Detection
      Object groups
      Position data
      Spatial alignment
      Statistical information
      Structural characteristics
      Structural feature
      Structural information
      Traditional techniques
      Alignment
      Remote sensing
      Geology
      Permalink
      http://hdl.handle.net/11693/28331
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/IGARSS.2011.6049690
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      • Department of Computer Engineering 1368
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