Retrieval of multi- and hyperspectral images using an interactive relevance feedback form of content-based image retrieval

Irwin E. Alber; Morton S. Farber; Nancy Yeager; Ziyou Xiong; William M. Pottenger

doi:10.1117/12.421092

27 March 2001 Retrieval of multi- and hyperspectral images using an interactive relevance feedback form of content-based image retrieval

Irwin E. Alber, Morton S. Farber, Nancy Yeager, Ziyou Xiong, William M. Pottenger

Author Affiliations +

Proceedings Volume 4384, Data Mining and Knowledge Discovery: Theory, Tools, and Technology III; (2001) https://doi.org/10.1117/12.421092
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

This paper demonstrates the capability of a set of image search algorithms and display tools to search large databases for multi- and hyperspectral image cubes most closely matching a particular query cube. An interactive search and analysis tool is presented and tested based on a relevance feedback approach that uses the human-in-the-loop to enhance a content-based image retrieval process to rapidly find the desired set of image cubes.

Citation Download Citation

Irwin E. Alber, Morton S. Farber, Nancy Yeager, Ziyou Xiong, and William M. Pottenger "Retrieval of multi- and hyperspectral images using an interactive relevance feedback form of content-based image retrieval", Proc. SPIE 4384, Data Mining and Knowledge Discovery: Theory, Tools, and Technology III, (27 March 2001); https://doi.org/10.1117/12.421092

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