Very large scale multidimensional data management and retrieval for USGS and NIMA imagery

Authors:
Aidong Zhang;Wei Wang;David M. Mark
Affiliations:
State University of New York at Buffalo, Buffalo, NY;State University of New York at Buffalo, Buffalo, NY;State University of New York at Buffalo, Buffalo, NY
Venue:
dg.o '04 Proceedings of the 2004 annual national conference on Digital government research
Year:
2004

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Abstract

Content-based image retrieval using low-level features such as color, texture and shape has been well studied. Various image querying systems have been built based on the low-level features for general or specific image retrieval tasks. The application of these approaches in geographic images have been explored, e.g. [1]. However, retrieving images based on low-level features may not be satisfactory. With the enormous growth of GIS images, it is an urgent need to build image retrieval systems which support both low-level (feature-based) and high-level (semantics-based) querying and browsing of images.