Automated Feature Generation in Large-Scale Geospatial Libraries for Content-Based Indexing

We describe a method for indexing and retrieving high-resolution image regions in large geospatial data libraries. An automated feature extraction method is used that generates a unique and specific structural description of each segment of a tessellated input image file. These tessellated regions a...

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Bibliographic Details
Published in:Photogrammetric engineering and remote sensing 2006-05, Vol.72 (5), p.531-540
Main Authors: Tobin, Kenneth W., Bhaduri, Budhendra L., Bright, Eddie A., Cheriyadat, Anil, Karnowski, Thomas P., Palathingal, Paul J., Potok, Thomas E., Price, Jeffery R.
Format: Article
Language:English
Subjects:
Animal, plant and microbial ecology
Applied geophysics
Biological and medical sciences
Earth sciences
Earth, ocean, space
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Internal geophysics
Teledetection and vegetation maps
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Summary:We describe a method for indexing and retrieving high-resolution image regions in large geospatial data libraries. An automated feature extraction method is used that generates a unique and specific structural description of each segment of a tessellated input image file. These tessellated regions are then merged into similar groups, or sub-regions, and indexed to provide flexible and varied retrieval in a query-by-example environment. The methods of tessellation, feature extraction, sub-region clustering, indexing, and retrieval are described and demonstrated using a geospatial library representing a 153 km2 region of land in East Tennessee at 0.5 m per pixel resolution.
ISSN:0099-1112
2374-8079
DOI:10.14358/PERS.72.5.531