Content-based retrieval of remote-sensed images using vector quantization

Asha Vellaikal; C.-C. Jay Kuo; Son K. Dao

doi:10.1117/12.211973

16 June 1995 Content-based retrieval of remote-sensed images using vector quantization

Asha Vellaikal, C.-C. Jay Kuo, Son K. Dao

Proceedings Volume 2488, Visual Information Processing IV; (1995) https://doi.org/10.1117/12.211973
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

Asha Vellaikal, C.-C. Jay Kuo, and Son K. Dao "Content-based retrieval of remote-sensed images using vector quantization", Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); https://doi.org/10.1117/12.211973

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