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Proceedings Paper

A new approach for fast indexing of hyperspectral image data for knowledge retrieval and mining
Author(s): Robert Clowers; Sumeet Dua
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Paper Abstract

Multispectral sensors produce images with a few relatively broad wavelength bands. Hyperspectral remote sensors, on the other hand, collect image data simultaneously in dozens or hundreds of narrow and adjacent spectral bands. These measurements make it possible to derive a continuous spectrum for each image cell, generating an image cube across multiple spectral components. Hyperspectral imaging has sound applications in a variety of areas such as mineral exploration, hazardous waste remediation, mapping habitat, invasive vegetation, eco system monitoring, hazardous gas detection, mineral detection, soil degradation, and climate change. This image has a strong potential for transforming the imaging paradigms associated with several design and manufacturing processes. In this paper, we describe a novel approach for fast indexing of multi-dimensional hyperspectral image data, especially for data mining applications. The index exploits the spectral and spatial relationships embedded in these image sets. The index will be employed for knowledge retrieval applications that require fast information interpretation approaches. The index can also be deployed in real-time mission-critical domains, as it is shown to exhibit speed with high degrees of dimensionality associated with the data. The strength of this index in terms of degree of false dismissals and false alarms will also be demonstrated. The paper will highlight some common applications of this imaging computational paradigm and will conclude with directions for future improvement and investigation.

Paper Details

Date Published: 17 November 2005
PDF: 9 pages
Proc. SPIE 5999, Intelligent Systems in Design and Manufacturing VI, 59990E (17 November 2005); doi: 10.1117/12.630195
Show Author Affiliations
Robert Clowers, Louisiana Tech Univ. (United States)
Sumeet Dua, Louisiana Tech Univ. (United States)


Published in SPIE Proceedings Vol. 5999:
Intelligent Systems in Design and Manufacturing VI
Bhaskaran Gopalakrishnan, Editor(s)

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