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This work was supported by NASA EPSCoR. Content Based Retrieval for Remotely Sensed Imagery
 

Summary: This work was supported by NASA EPSCoR.
Content Based Retrieval for Remotely Sensed Imagery
Badrinarayan Raghunathan and Scott T. Acton
The Oklahoma Imaging Laboratory
School of Electrical and Computer Engineering
Oklahoma State University
Stillwater, OK 74078
Email: raghuna@fajita.ecen.okstate.edu,sacton@ceat.okstate.edu
Abstract
We present a framework for content based retrieval (CBR)
of remotely sensed imagery. The main focus of our
research is the segmentation step in CBR. A bank of gabor
filters is used to extract regions of homogeneous texture.
These filter responses are utilized in a multiscale
clustering technique to yield the final segmentation. Novel
area morphological filters are utilized for the purpose of
scaling. The resultant segmentation yields regions that are
homogeneous in terms of texture and are significant in
terms of scale. These regions are used for the purpose of
extracting shape and textural features (on a global and

  

Source: Acton, Scott - Department of Electrical and Computer Engineering, University of Virginia

 

Collections: Computer Technologies and Information Sciences