Detection of compound structures using hierarchical clustering of statistical and structural features
Author
Akçay, H. Gokhan
Aksoy, Selim
Date
2011Source Title
2011 IEEE International Geoscience and Remote Sensing Symposium
Publisher
IEEE
Pages
2385 - 2388
Language
English
Type
Conference PaperItem Usage Stats
163
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126
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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 detectiongraph-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/11693/28331Published Version (Please cite this version)
http://dx.doi.org/10.1109/IGARSS.2011.6049690Collections
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