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Proceedings Paper

Autocorrelogram approach for estimating the spectral-spatial variability of hyperspectral images
Author(s): Dimitry Y. Frolov
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Paper Abstract

The amount of information contained in a single hyperspectral image is overwhelming for the human operator. As a result, assessing the spatial and spectral variability of a hyperspectral image is very difficult. The existing techniques mainly rely on different preprocessing algorithms that reduce the high-dimensionality of the hyperspectral data down to a few images that can be visualized using traditional RGB or RGBI combinations. The proposed auto-correlogram approach provides a simple framework for reducing a hyperspectral image cube to a single grayscale image that is easy to interpret and screen for spectral anomalies.

Paper Details

Date Published: 27 October 1999
PDF: 8 pages
Proc. SPIE 3753, Imaging Spectrometry V, (27 October 1999); doi: 10.1117/12.366307
Show Author Affiliations
Dimitry Y. Frolov, MicroImages, Inc. (United States)

Published in SPIE Proceedings Vol. 3753:
Imaging Spectrometry V
Michael R. Descour; Sylvia S. Shen, Editor(s)

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