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Proceedings Paper

Content-based retrieval of remote-sensed images using vector quantization
Author(s): Asha Vellaikal; C.-C. Jay Kuo; Son K. Dao
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Paper Abstract

A new approach of using the VQ codewords as the remote sensed image features for content- based retrieval is proposed in this research. Different distortion measures are tried in the VQ stage to enhance the performance of the codewords as 'content descriptors' including classification accuracy. A system based approach has been taken to ensure that the features satisfy the different criteria imposed by a whole system. We implemented two main types of queries--query by class and query by value. The performance with respect to the former query was satisfactory while that for the latter query was excellent.

Paper Details

Date Published: 16 June 1995
PDF: 12 pages
Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); doi: 10.1117/12.211973
Show Author Affiliations
Asha Vellaikal, Univ. of Southern California and Hughes Research Lab. (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)
Son K. Dao, Hughes Research Lab. (United States)

Published in SPIE Proceedings Vol. 2488:
Visual Information Processing IV
Friedrich O. Huck; Richard D. Juday, Editor(s)

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