27 March 2001 Retrieval of multi- and hyperspectral images using an interactive relevance feedback form of content-based image retrieval
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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.
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Irwin E. Alber, Morton S. Farber, Nancy Yeager, Ziyou Xiong, 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); doi: 10.1117/12.421092; https://doi.org/10.1117/12.421092
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